Chapter 8: Trendlines and Regression Analysis

Common Mathematical Functions Used in Predictive Analytical Models:

2

Modeling Relationships and Trends in Data

Create charts to better understand data sets.

For cross-sectional data, use a scatter chart.

For time series data, use a line chart.

Right click on data series and choose Add trendline from pop-up menu

Check the boxes Display Equation on chart and Display R-squared value on chart

Excel Trendline Tool

3

R2 (coefficient of determination) is a measure of the “fit” of the line to the data. The value of R2 will be between 0 and 1. A value of 1.0 indicates a perfect fit and all data points would lie on the line; the larger the value of R2 the better the fit.

Example 8.1: Modeling a Price-Demand Function

Scatter chart with the linear demand function

Sales = 20,512 – 9.5116(Price)

4

Predicted Sales decreases by 9.5116 per $1 increase

in Price.

Regression analysis is a tool for building mathematical and statistical models that characterize relationships between a dependent (ratio) variable and k independent, or explanatory variables (ratio or categorical), all of which are numerical.

Simple linear regression involves a single independent variable; the k = 1 case.

Multiple regression involves two or more independent variables; the k > 1 case

Regression Analysis

5

Finds a linear relationship between:

– one dependent variable Y and

– one independent variable X

First prepare a scatter plot to verify the data has a linear trend.

Use alternative approaches if the data is not linear.

Simple Linear Regression

6

Example 8.3: Home Market Value Data

Size of a house is typically related to its market value.

X = Square Footage

Y = Market Value ($)

The scatter plot of the full data set (42 homes) indicates a linear trend.

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Finding the Best-Fitting Regression Line

8

Predicted Market Value = 32,673 + 35.036(Square Feet)

The estimated market value of a home with 2,200 square feet would be: $32,673 + $35.036(2,200) = $109,752

Example 8.4: Using Excel to Find the Best Regression Line

The regression model explains variation in market value due to size of the home.

It provides better estimates of market value than simply using its average.

9

Least-Squares Regression

Note: The error term ε is assumed to be normally distributed with a zero mean and a constant unknown standard deviation σ.

10

Residuals are the observed errors associated with estimating the value of the dependent variable using the regression line:

Residuals

11

The best-fitting line minimizes the sum of squares of residuals (RSS = residual sum of squares):

Least Squares Regression

12

Data > Data Analysis >

Regression

Input Y Range (with header)

Input X Range (with header)

Check Labels

Excel outputs a table with many useful regression statistics. The regression

equation is shown by the column “Coefficients”

Simple Linear Regression With Excel

13

Home Market Value Regression Results

14

Predicted home market value increases by $35.04 per

1 square foot increase in Home Size

Multiple R: If k = 1, R = | r |, where r is the sample correlation coefficient. The value of r varies from -1 to +1 (r is negative if slope is negative)

R Square: coefficient of determination, R2, which

varies from 0 (no fit) to 1 (perfect fit). If k =1, R2 = r2

Adjusted R Square: adjusts R2 for sample size and number of X variables

Standard Error s: the estimated standard deviation of the error term ε; variability between observed and predicted Y values. This is formally called the standard error (of the estimate), s = SYX.

Regression Statistics

15

Example 8.6: Interpreting Regression Statistics for Simple Linear Regression

53.47 % of the variation in home market values can be explained by home size.

The standard error s = $7287.7

16

Example 8.7: Testing Significance of the X Variable

17

(8.7)

Example 8.8: Hypothesis Test for the significance of Home Size (Square Feet)

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Coefficients Standard Error t Stat P-value Lower 95% Upper 95%
Intercept 32673.2 8831.95 3.6994 0.0006496 14823.18 50523.29
Square Feet 35.0364 5.1673 6.7803 3.798E-08 24.5927 45.4800

Residual = Actual Y value − Predicted Y value

Standard residual = residual / (standard deviation)

Rule of thumb: Standard residuals outside of ±3 show potential outliers.

Excel provides a table and a plot of residuals.

Residual Analysis and Regression Assumptions

This point has a standard residual of 4.53

19

Linearity

examine scatter diagram (should appear linear)

examine residual plot (should appear random)

Normality of Errors

view a histogram of standard residuals

regression is robust to departures from normality

examine the normality plot in Excel’s Regression

Homoscedasticity (a constant variance of the error term ε): variation about the regression line is constant

examine the residual plot

Independence of Errors: successive observations should not be related.

This is important when one of the independent variable is time.

Checking Assumptions

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Examples of Diagnostic Scatter Charts of Residuals when the Regression Assumptions Are Not Met

21

Linearity – linear trend in scatterplot

– no pattern in residual plot

Example 8.11: Checking Regression Assumptions for the Home Market Value Data

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Normality of Errors – residual histogram appears slightly skewed but is not a serious departure. Excel’s normal probability plot looks OK.

Example 8.11 Continued

23

Constant Error Variance – residual plot shows no serious difference in the spread of the data for different X values.

Example 8.11 Continued

Independence of Errors – Because the data is cross-sectional, we can assume this assumption holds.

24

The Need for Variable Transformation; file UN11

25

ppgdp Residual Plot

499 3677.2 4473 4321.8999999999996 13750.1 9162.1 3030.7 22851.5 57118.9 45158.8 5637.6 22461.599999999999 18184.099999999999 670.4 14497.3 5702 43814.8 4495.8 741.1 92624.7 2047.2 1977.9 4477.7 7402.9 10715.6 32647.599999999999 6365.1 519.70000000000005 176.6 797.2 1206.5999999999999 46360.9 3244 57047.9 450.8 727.4 11887.7 4354 6222.8 736.6 2665.1 12212.1 7703.8 1154.0999999999999 13819.5 5704.4 28364.3 18838.8 200.6 55830.2 1282.5999999999999 7020.8 5195.3999999999996 706.1 4072.6 2653.7 3425.6 16852.400000000001 429.1 14135.4 324.60000000000002 3545.7 44501.7 39545.9 24669 12468.8 579.1 2680.3 39857.1 1333.2 26503.8 35292.699999999997 7429 2882.3 427.5 539.4 2996 612.70000000000005 2026.2 31823.7 12884 39278 1406.4 2949.3 5227.1000000000004 888.5 46220.3 29311.599999999999 33877.1 4899 43140.9 4445.3 9166.7000000000007 801.8 1468.2 45430.400000000001 865.4 1047.5999999999999 10663 9283.7000000000007 980.7 218.6 11320.8 10975.5 105095.4 49990.2 421.9 357.4 8372.7999999999993 4684.5 598.79999999999995 19599.2 3069.4 1131.0999999999999 7488.3 9100.7000000000007 2678.2 1625.8 2246.6999999999998 6509.8 2865 407.5 876.2 5124.7 6190.1 534.70000000000005 20321.099999999999 46909.7 35319.5 32372.1 1131.9000000000001 357.7 1239.8 504 84588.7 20791 1003.2 10821.8 1819.5 7614 1428.4 2771.1 5410.7 2140.1 12263.2 21437.599999999999 26461 72397.899999999994 21052.2 7522.4 10351.4 532.29999999999995 6677.1 3343.3 1283.3 15835.9 1032.7 5123.2 11450.6 351.7 43783.1 15976 23109.8 1193.5 114.8 7254.8 30542.799999999999 2375.3000000000002 6171.7 1824.9 7018 3311.2 48906.2 68880.2 2931.5 816 516 4434.5 4612.8 524.6 3543.1 15205.1 4222.1000000000004 10095.1 4587.5 3187.2 509 3035 39624.699999999997 36326.800000000003 46545.9 11952.4 1427.3 2963.5 13502.7 1182.7 1437.2 1237.8 573.1 2.8060619532387685 -1.5352000086793103 -0.89272548514221617 2.0954376205294913 -0.73775425831892294 -0.71262170489870202 -1.3458952580720365 -0.77540740167088429 0.59953364866214143 -0.38632366342129698 -0.84944522614334694 -0.58188857373310232 -0.16581653858598022 -0.99945132480312893 -1.1388354797477789 -1.5163837040073971 5.965326591540232E-2 -0.35499562947917829 1.9238118679765552 1.5471173855349225 -0.85437828634387891 0.11440333657504498 -1.9005750324397477 -0.32393583132048676 -1.0348922850509064 -0.14882235514948672 -1.4281570684740383 2.5887245853538952 0.87874153807370314 -0.73039230295781143 1.1477130877635835 -2.8429839240102783E-3 -0.79506726627703506 0.24826085251846997 1.2595190127581355 2.5823733143544665 -0.96537194195235387 -1.4795348195238625 -0.68571226412536834 1.5876678175167451 1.3494014423487206 -0.25618122026659584 -1.1193036572411807 1.0830324990657987 -1.2345326801165175 -1.5443068770954986 -0.81193598503945341 -1.073858797244267 2.3135098071926907 0.49428079809384085 0.45214593997371066 4.6832684080966303E-2 -0.5216005846606917 2.7626914755113652 -0.65454277494399138 -0.45696348548279841 -0.89725402994336312 2.3415541286742005 1.0788243694297179 -1.0234203378378446 0.68047919764079268 -0.46240948322709619 0.12164176832509033 7.500059749682797E-2 -0.35522702151422614 0.41622977409113115 1.5296260514233895 -1.5641119872092539 -0.44503751292696747 0.85276570736624269 -0.78949284736763081 0.16885050512692468 -0.76910033865358818 0.75435427787555742 1.8677731514884517 1.7163552062557308 -0.89200604717323939 7.0162818997188126E-4 -0.11705052182299269 -1.0221963937800616 -1.335479170150385 0.17742479345612971 -0.59489107182084533 -1.0285009708339357 -1.4235858291993628 1.3855303208156702 0.39865623948725459 0.66938823731124941 -0.617464568408022 -0.75908870828018804 -0.37891909072150143 -0.14661219575038098 -0.40347445331756315 1.4707549486233278 0.3690872211605476 0.5273705821085779 -0.52920913821135551 -0.6013766951497086 -1.3305760748700208 -1.1167291413624987 -9.5518245318886308E-2 1.8670860090319312 -0.40551909876710468 -1.3315725707165376 1.8693196231248199 -0.41466468752645325 1.3285938886940216 2.801529165436742 -0.33788815554940399 -1.3599551135311387 2.9582566723252248 -1.2665174706576792 1.3048098344105714 1.219296241160102 -1.3482020737054226 -0.65958719339477856 0.21482078924283465 -1.6758678116247678 -0.65999204929229505 -1.3395250459108095 -0.90319951611437954 1.5481329272226287 -1.2108634171078112 4.1136222559623903E-2 0.32024096920001099 -0.57379524644673729 -0.62740857578280096 0.11772476993017067 4.3708405643127612E-2 -6.6414444111977389E-3 -0.64167814986926475 3.7585387688007295 2.2927758600448498 -1.1737779906947758 1.4778752755272708 -0.36636650665729142 5.520200698016442E-2 -0.83149269419938676 1.1503327603897269 -0.52517826419472602 0.66681317487155978 -0.23120536904241806 -0.59470857043910819 -5.9404444629131525E-2 -1.3703517313615285 -1.179668056143236 -0.57386292729649191 1.343632976537565 -1.1150051777456438 -1.5091104913321947 -1.3175507689315422 2.1211279266413636 -1.0571695699272006 0.69211144720277584 0.35116834782301476 -3.1985269636250369E-2 1.4601463377722537 -1.4519117942603128 -0.47136404328191395 1.5613467015209825 -0.40936148954592722 -1.2945004986541606 -0.96113890527778145 0.90129374086947012 3.1087632450923106 -0.56267669200890547 -0.69619955688469126 -0.86687540726305379 -0.98534803712454577 1.1055056209414991 -0.68725694731624909 0.10208388725612982 0.31263515726594426 0.56302713154329975 -0.31207077043051834 1.0209507852061872E-2 2.3376061438647175 -1.6389579168539254 -1.5022503175241138 0.70288144029902178 0.7185072876183467 -1.0591779429803052 -1.1337570985569647 -0.83275524289806269 -0.71506020122038016 0.62411449680802811 2.7393820653716801 -1.5977576098548845 -0.20247691889582975 -0.14804669920870106 0.38907909053485179 -0.75230081645241675 -0.86822203746306048 0.66695358839479857 -0.35467383248715256 -1.3900519802340745 1.8060948735485218 3.1617118376182671 -5.0566015856357449E-2ppgdp

Residuals

fertility

fertility 499 3677.2 4473 4321.8999999999996 13750.1 9162.1 3030.7 22851.5 57118.9 45158.8 5637.6 22461.599999999999 18184.099999999999 670.4 14497.3 5702 43814.8 4495.8 741.1 92624.7 2047.2 1977.9 4477.7 7402.9 10715.6 32647.599999999999 6365.1 519.70000000000005 176.6 797.2 1206.5999999999999 46360.9 3244 57047.9 450.8 727.4 11887.7 4354 6222.8 736.6 2665.1 12212.1 7703.8 1154.0999999999999 13819.5 5704.4 28364.3 18838.8 200.6 55830.2 1282.5999999999999 7020.8 5195.3999999999996 706.1 4072.6 2653.7 3425.6 16852.400000000001 429.1 14135.4 324.60000000000002 3545.7 44501.7 39545.9 24669 12468.8 579.1 2680.3 39857.1 1333.2 26503.8 35292.699999999997 7429 2882.3 427.5 539.4 2996 612.70000000000005 2026.2 31823.7 12884 39278 1406.4 2949.3 5227.1000000000004 888.5 46220.3 29311.599999999999 33877.1 4899 43140.9 4445.3 9166.7000000000007 801.8 1468.2 45430.400000000001 865.4 1047.5999999999999 10663 9283.7000000000007 980.7 218.6 11320.8 10975.5 105095.4 49990.2 421.9 357.4 8372.7999999999993 4684.5 598.79999999999995 19599.2 3069.4 1131.0999999999999 7488.3 9100.7000000000007 2678.2 1625.8 2246.6999999999998 6509.8 2865 407.5 876.2 5124.7 6190.1 534.70000000000005 20321.099999999999 46909.7 35319.5 32372.1 1131.9000000000001 357.7 1239.8 504 84588.7 20791 1003.2 10821.8 1819.5 7614 1428.4 2771.1 5410.7 2140.1 12263.2 21437.599999999999 26461 72397.899999999994 21052.2 7522.4 10351.4 532.29999999999995 6677.1 3343.3 1283.3 15835.9 1032.7 5123.2 11450.6 351.7 43783.1 15976 23109.8 1193.5 114.8 7254.8 30542.799999999999 2375.3000000000002 6171.7 1824.9 7018 3311.2 48906.2 68880.2 2931.5 816 516 4434.5 4612.8 524.6 3543.1 15205.1 4222.1000000000004 10095.1 4587.5 3187.2 509 3035 39624.699999999997 36326.800000000003 46545.9 11952.4 1427.3 2963.5 13502.7 1182.7 1437.2 1237.8 573.1 5.968 1.5249999999999999 2.1419999999999999 5.1349999999999998 2 2.1720000000000002 1.7350000000000001 1.671 1.9490000000000001 1.3460000000000001 2.1480000000000001 1.877 2.4300000000000002 2.157 1.575 1.4790000000000001 1.835 2.6789999999999998 5.0780000000000003 1.76 2.258 3.2290000000000001 1.1339999999999999 2.617 1.8 1.984 1.546 5.75 4.0510000000000002 2.4220000000000002 4.2869999999999999 1.6910000000000001 2.2789999999999999 1.6 4.423 5.7370000000000001 1.8320000000000001 1.5589999999999999 2.2930000000000001 4.742 4.4420000000000002 2.5308062840941101 1.8120000000000001 4.2240000000000002 1.5009999999999999 1.4510000000000001 1.458 1.5009999999999999 5.4850000000000003 1.885 3.589 3 2.4900000000000002 5.9180000000000001 2.3929999999999998 2.6360000000000001 2.1709999999999998 4.9800000000000004 4.2430000000000003 1.702 3.8479999999999999 2.6019999999999999 1.875 1.9870000000000001 2.0329999999999999 3.1949999999999998 4.6890000000000001 1.528 1.4570000000000001 3.988 1.54 2.2170000000000001 2.1709999999999998 3.84 5.032 4.8769999999999998 2.19 3.1589999999999998 2.996 1.137 1.43 2.0979999999999999 2.5379999999999998 2.0550000000000002 1.587 4.5350000000000001 2.097 2.9089999999999998 1.476 2.262 1.4179999999999999 2.8889999999999998 2.4809999999999999 4.6230000000000002 3.5 2.2509999999999999 2.621 2.5430000000000001 1.506 1.764 3.0510000000000002 5.0380000000000003 2.41 1.4950000000000001 1.6830000000000001 1.163 4.4930000000000003 5.968 2.5720000000000001 1.6679999999999999 6.117 1.284 4.3844662585282403 4.3609999999999998 1.59 2.2269999999999999 3.3069999999999999 1.45 2.4460000000000002 1.63 2.1829999999999998 4.7130000000000001 1.9390000000000001 3.0550000000000002 3.3 2.5870000000000002 1.9 1.794 2.0910000000000002 2.1349999999999998 2.5 6.9249999999999998 5.431 1.988 1.948 2.1459999999999999 3.2010000000000001 2 4.2699999999999996 2.4089999999999998 3.7989999999999999 2.8580000000000001 2.41 3.05 1.415 1.3120000000000001 1.7569999999999999 2.2040000000000002 1.389 1.4279999999999999 1.5289999999999999 5.282 1.907 3.7629999999999999 3.488 2.6389999999999998 4.6050000000000004 1.5620000000000001 2.34 4.7279999999999998 1.367 1.3720000000000001 1.4770000000000001 4.0410000000000004 6.2830000000000004 2.383 1.504 2.2349999999999999 1.9950000000000001 4.2249999999999996 2.266 3.1739999999999999 1.925 1.536 2.7719999999999998 3.1619999999999999 5.4989999999999997 1.397 1.528 3.8639999999999999 3.7829999999999999 1.6319999999999999 1.909 2.0219999999999998 2.3159999999999998 3.7 5.9009999999999998 1.4830000000000001 1.7070000000000001 1.867 2.077 2.0430000000000001 2.2639999999999998 3.75 2.391 1.75 4.9379999999999997 6.3 3.109

Variable Transformation; file UN11

26

ln(ppgdp) Residual Plot

6.2126060957515188 8.2099068719895989 8.405814603432848 8.371450399362784 9.5288013757955436 9.1228306890345792 8.0165488949239982 10.036772039682001 10.952890339124952 10.717940445722775 8.6372137220128131 10.019562463511157 9.8083028648573372 6.5078745491678731 9.5817177041734567 8.6485722694726181 10.687726938832723 8.4108989065983195 6.6081355689573131 11.436311123726746 7.6242282848455787 7.5897909547873637 8.406864800720653 8.9096270943145814 9.2794559026068608 10.393526625111543 8.7585852217871807 6.2532517220143964 5.1738872881698592 6.6811055883386397 7.0955617660066617 10.74421171055257 8.0845624152353039 10.951646544796773 6.1110237821656215 6.5894765325528883 9.3832595311074911 8.3788502417944919 8.7359752452129662 6.6020450040109653 7.8879968593481156 9.4101825424881262 8.9494689926010018 7.0510760984263587 9.5338359172170968 8.6489930858626121 10.252886591155431 9.8436738518342715 5.3013128755278354 10.930070220601412 7.1566445467147624 8.8566324506408556 8.5555288976818105 6.5597568705223015 8.3120368951164139 7.8837101715776026 8.1390319178354176 9.7322483588722797 6.0616899919974792 9.5564375682769942 5.7825936550804906 8.1734908806863054 10.703282669671836 10.585217301576824 10.113302673639005 9.4309848030892969 6.3614751742317441 7.8936840075385621 10.593055836478793 7.1953373464335844 10.185043397920472 10.471431422668699 8.913146539151807 7.9663438655209271 6.0579542883768145 6.2904574107056295 8.0050333446371109 6.417875419731609 7.613917396619577 10.367966574201658 9.46374151045109 10.578419844675169 7.2487885269309125 7.9893231330409886 8.5616119099628634 6.7895346475947056 10.741174374503975 10.285738621092536 10.430494548880466 8.4967863816385751 10.672226782034295 8.399602637234107 9.1233326313435779 6.6868592002084064 7.2917924396766809 10.723936763469254 6.7631918277907843 6.9542571126335568 9.2745350840181793 9.1360154532143234 6.888266602398275 5.3872435757424384 9.3343970206381623 9.3034207949921939 11.56262378806705 10.819582265199772 6.0447683191302932 5.878855602725328 9.032743635617944 8.4520144653912421 6.3949276525454728 9.8832440280590692 8.0292373817409946 7.0309458895373353 8.9210970814574466 9.1161066126234367 7.8929002060614657 7.3937552813124716 7.7172177519234308 8.7810640127644799 7.9603236291488395 6.0100409326809174 6.7755943753797983 8.5418272657079104 8.7307065206370034 6.2817058419546861 9.9194150340855014 10.755979756077155 10.472190498332305 10.385052219700158 7.0316529156383742 5.879694646264972 7.1227053552678186 6.2225762680713688 11.34555596693313 9.9422754797433885 6.9109501698786566 9.2893178971596093 7.5063170170522149 8.937743936942443 7.2643102157202932 7.926999632266674 8.5961337534888447 7.6686078358960952 9.4143581868518975 9.9729016686204481 10.183427229849748 11.189932572428278 9.9547603467135506 8.9256405149628666 9.2448770552464179 6.2772072401787113 8.8064390405316999 8.1147136221484395 7.157190164250415 9.6700347934801432 6.9399320106773583 8.5415345228023956 9.3457974093561873 5.8627785394799368 10.687003177158442 9.6788428750956506 10.048012048968754 7.084645445778885 4.7431914838854663 8.8894185977432674 10.326884257608627 7.7728790242810479 8.7277296056912128 7.5092804699947697 8.8562335561431595 8.1050659404345229 10.797659456791925 11.140124042697861 7.9832695164042695 6.7044143549641069 6.2461067654815627 8.3971701488165067 8.4365903268841382 6.2626360674327737 8.1727573291355231 9.6293861768737905 8.3480879135848998 9.2198054365918818 8.4310904923628254 8.0668980673902784 6.2324480165505225 8.0179667034935989 10.587207940173004 10.500311039860483 10.74819420148998 9.3886873740147259 7.2635398266357232 7.994126281227893 9.5106449444291865 7.0755552392570715 7.2704520552393639 7.1210908893052611 6.3510602215576917 1.8106849777263925 -1.3938154881382361 -0.65533572053759448 2.3163554955085583 -0.10098662231564681 -0.18072362277537968 -1.303714187105425 -0.11500079841647204 0.73107192281384159 -1.7617367945772067E-2 -0.50584821781884459 8.0327773261949398E-2 0.50232851785326238 -1.817222998101963 -0.49317391387238563 -1.1678049342509489 0.45264763998237623 -0.11518301205384818 1.1659475211200041 0.84183469447228032 -1.0239869573333529 -7.4341085735734502E-2 -1.6626845072265248 0.13207167582053447 -0.45560241982442284 0.41921795496896053 -1.0325873719231204 1.6178887876833628 -0.75041068107096187 -1.4448047444952734 0.67719399553835391 0.34367309247958855 -0.71753991159189212 0.38130066256384021 0.20269514186927573 1.8133773018674875 -0.35923517625796442 -1.2550559610365053 -0.29960751640367178 0.82617084314620293 1.323572412656099 0.35626570759254328 -0.64822289520559839 0.58660902725046338 -0.59686477042465436 -1.1955439916282029 -0.19399105161015862 -0.40473840555956864 0.76260422367314273 0.65292147211730112 1.7070611995273044E-2 0.48221040510836755 -0.21449988635242612 1.9759485363968858 -0.46248602491035129 -0.48508570517468907 -0.79176410055861934 3.0051681345239158 -7.8960824807481345E-3 -0.38184978848433015 -0.57595999321613167 -0.33939655795044255 0.50229354090355027 0.54108278310341174 0.29445482550881286 1.0333586274490965 0.62399670490260206 -1.5869010627121463 1.5943353899703583E-2 0.44006350029545827 -0.15405970957864579 0.70052567938850396 -0.31174596344382932 0.77015434473179223 0.77878745760049384 0.76795953829813346 -0.85585482602936613 -0.87103025618021057 -0.29238060140356525 -0.44363149120408574 -0.71132937583511491 0.64786777086982017 -0.97679213660585384 -1.0005965184046191 -1.1137278916854976 0.73543066690245773 0.74778968096443288 1.2773800533613917 -6.5858729268853722E-2 -0.478925335948714 2.6036199781548808E-2 8.7812322193507431E-2 0.12858762494617171 0.75976299337629705 1.1874015300394447E-2 0.89110086859821491 -1.1949041638066249 -1.1544271326641669 -0.75265375370570475 -0.58054792661155319 -0.68734696665015704 0.36888870313154687 0.18846583363853675 -0.74574211014650693 0.84315949051802996 -0.13759063328038335 0.23161101419085384 1.6037307547830988 0.16341459866051267 -1.1006878032117122 2.07274013989253 -0.5972014678068216 1.3536200326225956 0.71112655359015609 -0.88781593835256323 -0.1298931327469206 0.19161291246085321 -1.9749001884813231 -0.77832543082439409 -0.93464857387901823 -0.89057872343246292 0.43007702569448991 -1.8692135097029317 0.34200391466820301 0.70412541785918403 -1.5274671925928494 4.1227689907380682E-2 0.45397030032793984 0.57499637206881182 0.56496308936286876 -1.1494350289680764 2.5612510344752373 1.8380253726922859 -2.1631326515859839 0.97355863392771758 0.30140314692129522 -0.52328118943161739 -0.24948712872528755 0.91489784040529987 -5.849344561222658E-2 0.29383265529496816 -0.23624248880275678 -0.26932135761056841 -0.20446779048822439 -0.75695131520413383 -0.51360596241875034 6.1938126187259579E-2 1.1330586455995459 -0.44785515382627072 -1.0469986159208178 -0.74804430121572185 1.1647432845320331 -0.6419138580854522 0.78515644909639182 -8.359105785848131E-2 0.62559033358789984 0.89869006294789866 -1.1511776112974472 0.12553506241179591 0.35376158260003621 -1.5801154964828257E-2 -0.63594789264862128 -0.30203101878641481 0.42442493117037294 1.2145206033373031 -0.11445934298590199 -0.1021060870020718 -0.95481061928252275 -0.60272052733714521 0.87173543799323028 -0.25203694404176691 0.19017405052611869 0.61081532604077737 0.43417304158787617 -0.28735028522512396 -0.69035128963742043 1.3624582955699021 -1.4056960313843956 -1.2502521054854374 -0.26229210506594214 0.84114857653069519 -0.40661533064111821 -0.92413126987820049 -0.27059087707103613 -0.46566247941284278 0.6925066622455871 1.7559886877926356 -1.5548350229485624 0.26231715150867729 0.36843354427473329 0.7321425819172136 -0.14486944336888374 -1.2416450526865703 0.69738184963220107 0.27875481710283267 -1.8722117844792674 1.4366411279464586 2.7060242639127301 -0.96246146814189615ln(ppgdp)

Residuals

fertility

fertility6.2126060957515188 8.2099068719895989 8.405814603432848 8.371450399362784 9.5288013757955436 9.1228306890345792 8.0165488949239982 10.036772039682001 10.952890339124952 10.717940445722775 8.6372137220128131 10.019562463511157 9.8083028648573372 6.5078745491678731 9.5817177041734567 8.6485722694726181 10.687726938832723 8.4108989065983195 6.6081355689573131 11.436311123726746 7.6242282848455787 7.5897909547873637 8.406864800720653 8.9096270943145814 9.2794559026068608 10.393526625111543 8.7585852217871807 6.2532517220143964 5.1738872881698592 6.6811055883386397 7.0955617660066617 10.74421171055257 8.0845624152353039 10.951646544796773 6.1110237821656215 6.5894765325528883 9.3832595311074911 8.3788502417944919 8.7359752452129662 6.6020450040109653 7.8879968593481156 9.4101825424881262 8.9494689926010018 7.0510760984263587 9.5338359172170968 8.6489930858626121 10.252886591155431 9.8436738518342715 5.3013128755278354 10.930070220601412 7.1566445467147624 8.8566324506408556 8.5555288976818105 6.5597568705223015 8.3120368951164139 7.8837101715776026 8.1390319178354176 9.7322483588722797 6.0616899919974792 9.5564375682769942 5.7825936550804906 8.1734908806863054 10.703282669671836 10.585217301576824 10.113302673639005 9.4309848030892969 6.3614751742317441 7.8936840075385621 10.593055836478793 7.1953373464335844 10.185043397920472 10.471431422668699 8.913146539151807 7.9663438655209271 6.0579542883768145 6.2904574107056295 8.0050333446371109 6.417875419731609 7.613917396619577 10.367966574201658 9.46374151045109 10.578419844675169 7.2487885269309125 7.9893231330409886 8.5616119099628634 6.7895346475947056 10.741174374503975 10.285738621092536 10.430494548880466 8.4967863816385751 10.672226782034295 8.399602637234107 9.1233326313435779 6.6868592002084064 7.2917924396766809 10.723936763469254 6.7631918277907843 6.9542571126335568 9.2745350840181793 9.1360154532143234 6.888266602398275 5.3872435757424384 9.3343970206381623 9.3034207949921939 11.56262378806705 10.819582265199772 6.0447683191302932 5.878855602725328 9.032743635617944 8.4520144653912421 6.3949276525454728 9.8832440280590692 8.0292373817409946 7.0309458895373353 8.9210970814574466 9.1161066126234367 7.8929002060614657 7.3937552813124716 7.7172177519234308 8.7810640127644799 7.9603236291488395 6.0100409326809174 6.7755943753797983 8.5418272657079104 8.7307065206370034 6.2817058419546861 9.9194150340855014 10.755979756077155 10.472190498332305 10.385052219700158 7.0316529156383742 5.879694646264972 7.1227053552678186 6.2225762680713688 11.34555596693313 9.9422754797433885 6.9109501698786566 9.2893178971596093 7.5063170170522149 8.937743936942443 7.2643102157202932 7.926999632266674 8.5961337534888447 7.6686078358960952 9.4143581868518975 9.9729016686204481 10.183427229849748 11.189932572428278 9.9547603467135506 8.9256405149628666 9.2448770552464179 6.2772072401787113 8.8064390405316999 8.1147136221484395 7.157190164250415 9.6700347934801432 6.9399320106773583 8.5415345228023956 9.3457974093561873 5.8627785394799368 10.687003177158442 9.6788428750956506 10.048012048968754 7.084645445778885 4.7431914838854663 8.8894185977432674 10.326884257608627 7.7728790242810479 8.7277296056912128 7.5092804699947697 8.8562335561431595 8.1050659404345229 10.797659456791925 11.140124042697861 7.9832695164042695 6.7044143549641069 6.2461067654815627 8.3971701488165067 8.4365903268841382 6.2626360674327737 8.1727573291355231 9.6293861768737905 8.3480879135848998 9.2198054365918818 8.4310904923628254 8.0668980673902784 6.2324480165505225 8.0179667034935989 10.587207940173004 10.500311039860483 10.74819420148998 9.3886873740147259 7.2635398266357232 7.994126281227893 9.5106449444291865 7.0755552392570715 7.2704520552393639 7.1210908893052611 6.3510602215576917 5.968 1.5249999999999999 2.1419999999999999 5.1349999999999998 2 2.1720000000000002 1.7350000000000001 1.671 1.9490000000000001 1.3460000000000001 2.1480000000000001 1.877 2.4300000000000002 2.157 1.575 1.4790000000000001 1.835 2.6789999999999998 5.0780000000000003 1.76 2.258 3.2290000000000001 1.1339999999999999 2.617 1.8 1.984 1.546 5.75 4.0510000000000002 2.4220000000000002 4.2869999999999999 1.6910000000000001 2.2789999999999999 1.6 4.423 5.7370000000000001 1.8320000000000001 1.5589999999999999 2.2930000000000001 4.742 4.4420000000000002 2.5308062840941101 1.8120000000000001 4.2240000000000002 1.5009999999999999 1.4510000000000001 1.458 1.5009999999999999 5.4850000000000003 1.885 3.589 3 2.4900000000000002 5.9180000000000001 2.3929999999999998 2.6360000000000001 2.1709999999999998 4.9800000000000004 4.2430000000000003 1.702 3.8479999999999999 2.6019999999999999 1.875 1.9870000000000001 2.0329999999999999 3.1949999999999998 4.6890000000000001 1.528 1.4570000000000001 3.988 1.54 2.2170000000000001 2.1709999999999998 3.84 5.032 4.8769999999999998 2.19 3.1589999999999998 2.996 1.137 1.43 2.0979999999999999 2.5379999999999998 2.0550000000000002 1.587 4.5350000000000001 2.097 2.9089999999999998 1.476 2.262 1.4179999999999999 2.8889999999999998 2.4809999999999999 4.6230000000000002 3.5 2.2509999999999999 2.621 2.5430000000000001 1.506 1.764 3.0510000000000002 5.0380000000000003 2.41 1.4950000000000001 1.6830000000000001 1.163 4.4930000000000003 5.968 2.5720000000000001 1.6679999999999999 6.117 1.284 4.3844662585282403 4.3609999999999998 1.59 2.2269999999999999 3.3069999999999999 1.45 2.4460000000000002 1.63 2.1829999999999998 4.7130000000000001 1.9390000000000001 3.0550000000000002 3.3 2.5870000000000002 1.9 1.794 2.0910000000000002 2.1349999999999998 2.5 6.9249999999999998 5.431 1.988 1.948 2.1459999999999999 3.2010000000000001 2 4.2699999999999996 2.4089999999999998 3.7989999999999999 2.8580000000000001 2.41 3.05 1.415 1.3120000000000001 1.7569999999999999 2.2040000000000002 1.389 1.4279999999999999 1.5289999999999999 5.282 1.907 3.7629999999999999 3.488 2.6389999999999998 4.6050000000000004 1.5620000000000001 2.34 4.7279999999999998 1.367 1.3720000000000001 1.4770000000000001 4.0410000000000004 6.2830000000000004 2.383 1.504 2.2349999999999999 1.9950000000000001 4.2249999999999996 2.266 3.1739999999999999 1.925 1.536 2.7719999999999998 3.1619999999999999 5.4989999999999997 1.397 1.528 3.8639999999999999 3.7829999999999999 1.6319999999999999 1.909 2.0219999999999998 2.3159999999999998 3.7 5.9009999999999998 1.4830000000000001 1.7070000000000001 1.867 2.077 2.0430000000000001 2.2639999999999998 3.75 2.391 1.75 4.9379999999999997 6.3 3.109

Variable Transformation; file UN11

27

ppgdp Residual Plot

499 3677.2 4473 4321.8999999999996 13750.1 9162.1 3030.7 22851.5 57118.9 45158.8 5637.6 22461.599999999999 18184.099999999999 670.4 14497.3 5702 43814.8 4495.8 741.1 92624.7 2047.2 1977.9 4477.7 7402.9 10715.6 32647.599999999999 6365.1 519.70000000000005 176.6 797.2 1206.5999999999999 46360.9 3244 57047.9 450.8 727.4 11887.7 4354 6222.8 736.6 2665.1 12212.1 7703.8 1154.0999999999999 13819.5 5704.4 28364.3 18838.8 200.6 55830.2 1282.5999999999999 7020.8 5195.3999999999996 706.1 4072.6 2653.7 3425.6 16852.400000000001 429.1 14135.4 324.60000000000002 3545.7 44501.7 39545.9 24669 12468.8 579.1 2680.3 39857.1 1333.2 26503.8 35292.699999999997 7429 2882.3 427.5 539.4 2996 612.70000000000005 2026.2 31823.7 12884 39278 1406.4 2949.3 5227.1000000000004 888.5 46220.3 29311.599999999999 33877.1 4899 43140.9 4445.3 9166.7000000000007 801.8 1468.2 45430.400000000001 865.4 1047.5999999999999 10663 9283.7000000000007 980.7 218.6 11320.8 10975.5 105095.4 49990.2 421.9 357.4 8372.7999999999993 4684.5 598.79999999999995 19599.2 3069.4 1131.0999999999999 7488.3 9100.7000000000007 2678.2 1625.8 2246.6999999999998 6509.8 2865 407.5 876.2 5124.7 6190.1 534.70000000000005 20321.099999999999 46909.7 35319.5 32372.1 1131.9000000000001 357.7 1239.8 504 84588.7 20791 1003.2 10821.8 1819.5 7614 1428.4 2771.1 5410.7 2140.1 12263.2 21437.599999999999 26461 72397.899999999994 21052.2 7522.4 10351.4 532.29999999999995 6677.1 3343.3 1283.3 15835.9 1032.7 5123.2 11450.6 351.7 43783.1 15976 23109.8 1193.5 114.8 7254.8 30542.799999999999 2375.3000000000002 6171.7 1824.9 7018 3311.2 48906.2 68880.2 2931.5 816 516 4434.5 4612.8 524.6 3543.1 15205.1 4222.1000000000004 10095.1 4587.5 3187.2 509 3035 39624.699999999997 36326.800000000003 46545.9 11952.4 1427.3 2963.5 13502.7 1182.7 1437.2 1237.8 573.1 0.73367060008076335 -0.59505905508598511 -0.24637750753361176 0.62626567191123272 -0.21079835644876599 -0.17981548360433197 -0.47330555750360292 -0.28832426852870385 0.25035627141619443 -0.25412209005231912 -0.23050308650933582 -0.17644992185959918 3.3734813192667135E-2 -0.28209825614567874 -0.44130000533176578 -0.60295093608505623 4.0693473089380094E-2 -2.241786930410461E-2 0.57489474535550311 0.54704594069753676 -0.22087716165148064 0.13603769927891252 -0.88231349826434613 -1.3189202619627638E-2 -0.35023307198256248 -6.6317500421754216E-3 -0.55120026358892193 0.6966910309199954 0.34260229311512713 -0.16479914960509856 0.41079151841262118 -1.2440949934485857E-2 -0.19818108904107146 5.2246225830625825E-2 0.43353570145220544 0.69675985129851736 -0.31945003722538601 -0.56540913261592041 -0.15860808717031105 0.50638571951374489 0.46268645634122096 7.3223040091969782E-3 -0.37740783234066022 0.39539735817174559 -0.49703469634572317 -0.62203719647034261 -0.36277801783074581 -0.44067330849353747 0.64592511703502264 0.20249694469232227 0.23393134193755993 0.11910388686277085 -8.7722987243567307E-2 0.72758280336503711 -0.14006573576074244 -5.928366233705018E-2 -0.24469077401483208 0.73631987562126688 0.39174440092088525 -0.36781499863139233 0.29285394391310815 -6.2249689861008095E-2 6.9970805691265681E-2 7.2339759288123862E-2 -7.1825396158602728E-2 0.24325391783311801 0.49337751489099224 -0.60428789859162424 -0.23441223284327745 0.33991576592629524 -0.32895266648590493 0.13410982475022037 -0.19973686009706659 0.31949302190858142 0.56227338780461977 0.5322426628361987 -0.24080107107984761 9.8790988782048839E-2 6.1685630664423785E-2 -0.57260506276483514 -0.55599647237524707 0.12369007430458689 -0.11117575892067222 -0.30495115817251828 -0.53780429897173687 0.46345749049485963 0.20116794396453297 0.33860289716571779 -0.28860505851418317 -0.18708457602995809 -0.22467075885274956 5.2481900456297081E-2 -4.6750527870483172E-2 0.4817027033659631 0.2109047883966324 0.26316501909307932 -8.5071057103729197E-2 -0.11323658325105246 -0.52915324942936426 -0.38651448973092783 6.8137120366548176E-2 0.56111932204818893 -5.1597238594529471E-2 -0.53297513012515418 0.64234271266377829 -0.34600497656325369 0.44891361646474359 0.73208058304255696 -1.9643076816582616E-2 -0.49411725610580148 0.75945116504151811 -0.5882861745504534 0.45418948742071041 0.42705793514904489 -0.51052485898166267 -0.15549795394136878 0.16777026390254268 -0.66852494368587601 -0.13866241780378519 -0.49666637220222937 -0.24547352767946884 0.49655593767036121 -0.38633333269851899 0.11598000927766039 0.20508619128829564 -0.10184148667708715 -0.18830632627378563 5.2849182702113695E-2 7.5898249990677846E-2 6.3626316490237866E-2 -0.12934373869032068 0.88081014089466514 0.64770041045449278 -0.36555600991688608 0.55829962416282808 -6.1278092204811951E-2 0.1163836266321685 -0.24368004354608142 0.41370037161582229 -9.3635674591643903E-2 0.29243278253810456 2.2894077368538657E-2 -0.11796136075204189 8.0828131198345199E-2 -0.57351230770806638 -0.5460704172409675 -0.19760787207678798 0.54488062302011031 -0.49336667511018317 -0.61760110465091 -0.5174953876589059 0.61193747455263581 -0.33783645976355081 0.30441370544152546 0.20539409607254289 8.9875830811140589E-2 0.48039428890133906 -0.55484937532923251 -7.9615541109127164E-2 0.49910699532174596 -0.25408840787951575 -0.56268152376897485 -0.40883308097005716 0.35154941785921601 0.78079215420125103 -0.10852063315949445 -0.30725319341970053 -0.22743118610554081 -0.29839883922580779 0.40316644142740876 -0.16152368021440411 0.13382936715671345 0.14574595330793416 0.14428834572541183 -5.8577998162239187E-3 0.10202304800833129 0.65201588658103704 -0.67422271323894112 -0.58258798385762778 0.29924911423704748 0.31195808047146789 -0.39780118166319195 -0.36435527432746506 -0.24090016976244066 -0.16699020691851452 0.28577717690085591 0.72249285459319146 -0.630197623330922 -7.866392047906412E-2 -2.6100400793229506E-2 0.19524087781188915 -0.20971247561943862 -0.22518428315372185 0.29668828472277919 -3.501188677583067E-2 -0.48544825278766268 0.55475411387379725 0.79610430693150014 8.2391932256846045E-2ppgdp

Residuals

ln(ferility)

ln(ferility) 499 3677.2 4473 4321.8999999999996 13750.1 9162.1 3030.7 22851.5 57118.9 45158.8 5637.6 22461.599999999999 18184.099999999999 670.4 14497.3 5702 43814.8 4495.8 741.1 92624.7 2047.2 1977.9 4477.7 7402.9 10715.6 32647.599999999999 6365.1 519.70000000000005 176.6 797.2 1206.5999999999999 46360.9 3244 57047.9 450.8 727.4 11887.7 4354 6222.8 736.6 2665.1 12212.1 7703.8 1154.0999999999999 13819.5 5704.4 28364.3 18838.8 200.6 55830.2 1282.5999999999999 7020.8 5195.3999999999996 706.1 4072.6 2653.7 3425.6 16852.400000000001 429.1 14135.4 324.60000000000002 3545.7 44501.7 39545.9 24669 12468.8 579.1 2680.3 39857.1 1333.2 26503.8 35292.699999999997 7429 2882.3 427.5 539.4 2996 612.70000000000005 2026.2 31823.7 12884 39278 1406.4 2949.3 5227.1000000000004 888.5 46220.3 29311.599999999999 33877.1 4899 43140.9 4445.3 9166.7000000000007 801.8 1468.2 45430.400000000001 865.4 1047.5999999999999 10663 9283.7000000000007 980.7 218.6 11320.8 10975.5 105095.4 49990.2 421.9 357.4 8372.7999999999993 4684.5 598.79999999999995 19599.2 3069.4 1131.0999999999999 7488.3 9100.7000000000007 2678.2 1625.8 2246.6999999999998 6509.8 2865 407.5 876.2 5124.7 6190.1 534.70000000000005 20321.099999999999 46909.7 35319.5 32372.1 1131.9000000000001 357.7 1239.8 504 84588.7 20791 1003.2 10821.8 1819.5 7614 1428.4 2771.1 5410.7 2140.1 12263.2 21437.599999999999 26461 72397.899999999994 21052.2 7522.4 10351.4 532.29999999999995 6677.1 3343.3 1283.3 15835.9 1032.7 5123.2 11450.6 351.7 43783.1 15976 23109.8 1193.5 114.8 7254.8 30542.799999999999 2375.3000000000002 6171.7 1824.9 7018 3311.2 48906.2 68880.2 2931.5 816 516 4434.5 4612.8 524.6 3543.1 15205.1 4222.1000000000004 10095.1 4587.5 3187.2 509 3035 39624.699999999997 36326.800000000003 46545.9 11952.4 1427.3 2963.5 13502.7 1182.7 1437.2 1237.8 573.1 1.7864118629014598 0.42199441005937488 0.76173997202555699 1.6360798433805215 0.69314718055994529 0.77564840207168906 0.55100741339882253 0.51342224961325666 0.66731642052542384 0.2971372312225361 0.76453717664661835 0.62967475760437175 0.88789125735245711 0.76871836740701938 0.45425527227759638 0.39136618372866283 0.60704448150653356 0.98544359056247166 1.6249174832824866 0.56531380905006046 0.81447946572747032 1.1721724917761382 0.12575120530556025 0.96202862354800878 0.58778666490211906 0.68511500886268106 0.43567095016523022 1.7491998548092591 1.3989637642205535 0.88459364513090055 1.4555871876158399 0.52532006991644331 0.8237367502635472 0.47000362924573563 1.4868181988861897 1.7469364256197339 0.60540826625193855 0.44404459007563946 0.82986100387576744 1.5564589876432138 1.4911047254722358 0.92853794133402046 0.5944312076207876 1.4407825464039603 0.40613155265132483 0.37225297390205087 0.37706563358646639 0.40613155265132483 1.7020170937271937 0.63392782089997413 1.2778736121654701 1.0986122886681098 0.91228271047661635 1.7779985539780179 0.87254780892623618 0.96926261664026081 0.7751878908961547 1.6054298910365616 1.4452705662201879 0.53180403015118238 1.34755353280346 0.95628038009031346 0.62860865942237409 0.68662596356967986 0.70951253464620956 1.161587087829498 1.5452193401074492 0.42395969074432877 0.37637952721306783 1.383289852099592 0.43178241642553783 0.79615493063417442 0.7751878908961547 1.3454723665996355 1.6158175193981394 1.5845302767279155 0.78390154382840938 1.1502555218199482 1.097278065654973 0.12839321476839899 0.35767444427181588 0.74098450997410537 0.9313763692921958 0.72027584794819799 0.46184544154427198 1.5118250835670999 0.74050775191978291 1.0678093795130645 0.38933572617828072 0.81624937769392869 0.3492474281099357 1.0609104214840981 0.9086617047096639 1.5310438450060884 1.2527629684953681 0.81137456192459512 0.96355592434126924 0.93334448643998269 0.40945712937770185 0.56758395758459956 1.1154694057345327 1.6170091779304185 0.87962674750256364 0.40212620684264982 0.52057791520866903 0.15100287353652742 1.5025206300880229 1.7864118629014598 0.94468380637537297 0.51162530393655492 1.8110717802604279 0.24998020526776946 1.4780678985817615 1.4727013888606293 0.46373401623214022 0.80065538827523053 1.1960414339996557 0.37156355643248301 0.89445403726498074 0.48858001481867092 0.78070007756780679 1.5503246479415937 0.66217237626051473 1.1167795926235586 1.1939224684724346 0.95049890320389219 0.64185388617239469 0.58444776363660444 0.73764242044649664 0.75846664668058783 0.91629073187415511 1.9351380520734023 1.6921232790527083 0.68712910823438234 0.66680320522034331 0.76360564420850674 1.163463260987726 0.69314718055994529 1.451613827240533 0.87921172363273425 1.3347378742054885 1.0501220795076758 0.87962674750256364 1.1151415906193203 0.34712953109520095 0.27155269052189734 0.56360780920496012 0.79027389129066816 0.32858406377220672 0.3562748639173926 0.42461392694692518 1.6643048138749406 0.64553132661828205 1.3252165116113002 1.2493285060467332 0.97040005752118697 1.5271426697072703 0.44596705141749426 0.85015092936961001 1.553502280103797 0.31261855774181252 0.31626952930369356 0.39001300354924279 1.3964921860963366 1.83784757342081 0.86836019811660503 0.4081282255276481 0.80424122806553211 0.69064405034182685 1.441019260809137 0.81801616260581456 1.1549926221042173 0.65492596773974754 0.42918163472548043 1.0195690813276568 1.1512047387872804 1.7045662575256777 0.33432708027482477 0.42395969074432877 1.3517029163502716 1.3305173456508921 0.48980625654191517 0.64657954474361057 0.7040871205982796 0.8398415597107487 1.3083328196501789 1.7751218280750316 0.39406706315579509 0.53473744381230359 0.62433286455958559 0.73092454489397518 0.71441931583548512 0.81713316034093642 1.3217558399823195 0.87171168847618763 0.55961578793542266 1.5969603909229877 1.8405496333974869 1.1343011310766167

Variable Transformation; file UN11

28

ln(ppgdp) Residual Plot

6.2126060957515188 8.2099068719895989 8.405814603432848 8.371450399362784 9.5288013757955436 9.1228306890345792 8.0165488949239982 10.036772039682001 10.952890339124952 10.717940445722775 8.6372137220128131 10.019562463511157 9.8083028648573372 6.5078745491678731 9.5817177041734567 8.6485722694726181 10.687726938832723 8.4108989065983195 6.6081355689573131 11.436311123726746 7.6242282848455787 7.5897909547873637 8.406864800720653 8.9096270943145814 9.2794559026068608 10.393526625111543 8.7585852217871807 6.2532517220143964 5.1738872881698592 6.6811055883386397 7.0955617660066617 10.74421171055257 8.0845624152353039 10.951646544796773 6.1110237821656215 6.5894765325528883 9.3832595311074911 8.3788502417944919 8.7359752452129662 6.6020450040109653 7.8879968593481156 9.4101825424881262 8.9494689926010018 7.0510760984263587 9.5338359172170968 8.6489930858626121 10.252886591155431 9.8436738518342715 5.3013128755278354 10.930070220601412 7.1566445467147624 8.8566324506408556 8.5555288976818105 6.5597568705223015 8.3120368951164139 7.8837101715776026 8.1390319178354176 9.7322483588722797 6.0616899919974792 9.5564375682769942 5.7825936550804906 8.1734908806863054 10.703282669671836 10.585217301576824 10.113302673639005 9.4309848030892969 6.3614751742317441 7.8936840075385621 10.593055836478793 7.1953373464335844 10.185043397920472 10.471431422668699 8.913146539151807 7.9663438655209271 6.0579542883768145 6.2904574107056295 8.0050333446371109 6.417875419731609 7.613917396619577 10.367966574201658 9.46374151045109 10.578419844675169 7.2487885269309125 7.9893231330409886 8.5616119099628634 6.7895346475947056 10.741174374503975 10.285738621092536 10.430494548880466 8.4967863816385751 10.672226782034295 8.399602637234107 9.1233326313435779 6.6868592002084064 7.2917924396766809 10.723936763469254 6.7631918277907843 6.9542571126335568 9.2745350840181793 9.1360154532143234 6.888266602398275 5.3872435757424384 9.3343970206381623 9.3034207949921939 11.56262378806705 10.819582265199772 6.0447683191302932 5.878855602725328 9.032743635617944 8.4520144653912421 6.3949276525454728 9.8832440280590692 8.0292373817409946 7.0309458895373353 8.9210970814574466 9.1161066126234367 7.8929002060614657 7.3937552813124716 7.7172177519234308 8.7810640127644799 7.9603236291488395 6.0100409326809174 6.7755943753797983 8.5418272657079104 8.7307065206370034 6.2817058419546861 9.9194150340855014 10.755979756077155 10.472190498332305 10.385052219700158 7.0316529156383742 5.879694646264972 7.1227053552678186 6.2225762680713688 11.34555596693313 9.9422754797433885 6.9109501698786566 9.2893178971596093 7.5063170170522149 8.937743936942443 7.2643102157202932 7.926999632266674 8.5961337534888447 7.6686078358960952 9.4143581868518975 9.9729016686204481 10.183427229849748 11.189932572428278 9.9547603467135506 8.9256405149628666 9.2448770552464179 6.2772072401787113 8.8064390405316999 8.1147136221484395 7.157190164250415 9.6700347934801432 6.9399320106773583 8.5415345228023956 9.3457974093561873 5.8627785394799368 10.687003177158442 9.6788428750956506 10.048012048968754 7.084645445778885 4.7431914838854663 8.8894185977432674 10.326884257608627 7.7728790242810479 8.7277296056912128 7.5092804699947697 8.8562335561431595 8.1050659404345229 10.797659456791925 11.140124042697861 7.9832695164042695 6.7044143549641069 6.2461067654815627 8.3971701488165067 8.4365903268841382 6.2626360674327737 8.1727573291355231 9.6293861768737905 8.3480879135848998 9.2198054365918818 8.4310904923628254 8.0668980673902784 6.2324480165505225 8.0179667034935989 10.587207940173004 10.500311039860483 10.74819420148998 9.3886873740147259 7.2635398266357232 7.994126281227893 9.5106449444291865 7.0755552392570715 7.2704520552393639 7.1210908893052611 6.3510602215576917 0.40784455052790092 -0.54283247322373751 -0.16250466654320006 0.70471666728028692 1.5290119690146708E-3 -6.6507549398076016E-5 -0.45387353352405002 -7.2969904477447556E-2 0.2706979764430093 -0.1481510330829815 -0.11177318394486224 3.9717643486564924E-2 0.25417176250742846 -0.54868414792307563 -0.22640129019499805 -0.48259125618318177 0.15549749570361471 6.2252164308221669E-2 0.3282840167818124 0.26883587721893898 -0.27167061175699891 7.888872872736874E-2 -0.79827588511939407 0.14214863482991003 -0.15548336518918915 0.17262449092595411 -0.41549733017803653 0.37905227523244367 -0.19477392722961406 -0.3969240974443905 0.25992395369924548 8.5473892507772709E-2 -0.1670552104573807 7.312753343396533E-2 8.7208131955557766E-2 0.44643774371423639 -0.11635886437227561 -0.48578571024578354 -2.5990928284407744E-2 0.25856386191510383 0.45959425184392932 0.2123479067654197 -0.21719554037918076 0.23590411595211158 -0.28444371175972039 -0.50161729398451049 -0.16455843733765496 -0.22026084979815919 0.13467558547477743 0.23258219414074288 9.4863663222713113E-2 0.26775447083487869 1.9051355976275164E-2 0.47134345043225134 -7.1122861885415833E-2 -6.3135843443891004E-2 -0.2043207239981315 0.95595572152516284 3.5441015195993408E-2 -0.15408930707146618 -0.12009076478639757 -1.6090068011292091E-2 0.18028403993942077 0.21384412830956245 0.13897368502954366 0.44970623710019386 0.19749022553638595 -0.60637269135134031 -9.4778557216746828E-2 0.2082951083521829 -0.12389535748305203 0.29980237486767813 -4.3963045575813986E-2 0.3301914585618182 0.20521411816702728 0.22208984761479234 -0.22336484687618707 -0.18579029394527757 8.992089877325915E-3 -0.38939206225361073 -0.34742086152570034 0.26679458296903225 -0.23254597383460707 -0.29024490973217454 -0.43012581826163576 0.25276839745170498 0.30003239099754841 0.53299059957184181 -0.11549689424761389 -8.9150476454901706E-2 -0.10551041186229326 0.13537897544440858 0.13305077233064977 0.25071796190040652 9.7748876706410304E-2 0.36732843355919531 -0.30095767126857598 -0.29158997623424598 -0.33483224723295835 -0.20539973095347253 -0.12313497703659215 6.7468195869053282E-2 0.14773775827371094 -0.33617950091094345 0.25026562480995496 -0.27323030957928895 8.9185758144570526E-2 0.33870820720063821 0.15030738288540546 -0.40304904309775014 0.47027233942520019 -0.36821524363059799 0.47581536899223642 0.26365298993807706 -0.35376996709978464 2.3547587662120062E-2 0.16554668759545899 -0.7623289544951628 -0.17243329198076429 -0.35793178877606141 -0.23582792114831341 0.12979600531438029 -0.59977203426597092 0.22070994798706778 0.33697912114196926 -0.41375441150628633 3.1151253444757443E-2 0.14703933434420324 0.24144710704154604 0.24422065747338162 -0.29261120674261742 0.48760820406256311 0.50208283385255248 -0.68937288507316674 0.35152536204853446 0.15763854791495036 -7.0442225625999777E-2 -4.8079939466696975E-2 0.34103845582346404 6.5156132858059324E-2 0.17403084559532167 2.6691021956819494E-2 -5.1933197922517937E-3 3.8184727653630901E-2 -0.36819551963553754 -0.3280701972888157 7.5952464258013386E-3 0.44275869519486766 -0.27479679499577225 -0.46028794813455265 -0.32581910398760566 0.2991196147679589 -0.19572404539564148 0.34067036696086506 6.6431581659919692E-2 0.30803836123023565 0.29924076522325804 -0.45016323484933185 0.12062352822809463 0.10246826418642807 -0.13907835513730787 -0.34426757476238146 -0.19405078501904788 0.19856763877674233 0.15489133812783029 4.4294023651141656E-2 -0.11816724459970113 -0.25111588050291644 -0.16691596428366495 0.33105776803600029 -1.2924286137393604E-2 0.16844796224789405 0.22615147954587755 7.1348612337216899E-2 7.7943182542945522E-3 -0.12548459776127596 0.33293860172954837 -0.59170825522088899 -0.49390976328647956 -1.6500698078016907E-2 0.35799494250225949 -0.18097579199479147 -0.28962316529430521 -5.1539490784188291E-2 -7.9167183866154067E-2 0.31388169304699987 0.40066476535591944 -0.610520185024788 6.2367968912100835E-2 0.13396271532446891 0.29190333963216197 -6.2234382901104057E-3 -0.34373345420351176 0.31223005342271026 0.17633241900669205 -0.64019179372311563 0.43752564305704156 0.65017475191810514 -0.2155854387158056ln(ppgdp)

Residuals

ln(ferility)

ln(ferility) 6.2126060957515188 8.2099068719895989 8.405814603432848 8.371450399362784 9.5288013757955436 9.1228306890345792 8.0165488949239982 10.036772039682001 10.952890339124952 10.717940445722775 8.6372137220128131 10.019562463511157 9.8083028648573372 6.5078745491678731 9.5817177041734567 8.6485722694726181 10.687726938832723 8.4108989065983195 6.6081355689573131 11.436311123726746 7.6242282848455787 7.5897909547873637 8.406864800720653 8.9096270943145814 9.2794559026068608 10.393526625111543 8.7585852217871807 6.2532517220143964 5.1738872881698592 6.6811055883386397 7.0955617660066617 10.74421171055257 8.0845624152353039 10.951646544796773 6.1110237821656215 6.5894765325528883 9.3832595311074911 8.3788502417944919 8.7359752452129662 6.6020450040109653 7.8879968593481156 9.4101825424881262 8.9494689926010018 7.0510760984263587 9.5338359172170968 8.6489930858626121 10.252886591155431 9.8436738518342715 5.3013128755278354 10.930070220601412 7.1566445467147624 8.8566324506408556 8.5555288976818105 6.5597568705223015 8.3120368951164139 7.8837101715776026 8.1390319178354176 9.7322483588722797 6.0616899919974792 9.5564375682769942 5.7825936550804906 8.1734908806863054 10.703282669671836 10.585217301576824 10.113302673639005 9.4309848030892969 6.3614751742317441 7.8936840075385621 10.593055836478793 7.1953373464335844 10.185043397920472 10.471431422668699 8.913146539151807 7.9663438655209271 6.0579542883768145 6.2904574107056295 8.0050333446371109 6.417875419731609 7.613917396619577 10.367966574201658 9.46374151045109 10.578419844675169 7.2487885269309125 7.9893231330409886 8.5616119099628634 6.7895346475947056 10.741174374503975 10.285738621092536 10.430494548880466 8.4967863816385751 10.672226782034295 8.399602637234107 9.1233326313435779 6.6868592002084064 7.2917924396766809 10.723936763469254 6.7631918277907843 6.9542571126335568 9.2745350840181793 9.1360154532143234 6.888266602398275 5.3872435757424384 9.3343970206381623 9.3034207949921939 11.56262378806705 10.819582265199772 6.0447683191302932 5.878855602725328 9.032743635617944 8.4520144653912421 6.3949276525454728 9.8832440280590692 8.0292373817409946 7.0309458895373353 8.9210970814574466 9.1161066126234367 7.8929002060614657 7.3937552813124716 7.7172177519234308 8.7810640127644799 7.9603236291488395 6.0100409326809174 6.7755943753797983 8.5418272657079104 8.7307065206370034 6.2817058419546861 9.9194150340855014 10.755979756077155 10.472190498332305 10.385052219700158 7.0316529156383742 5.879694646264972 7.1227053552678186 6.2225762680713688 11.34555596693313 9.9422754797433885 6.9109501698786566 9.2893178971596093 7.5063170170522149 8.937743936942443 7.2643102157202932 7.926999632266674 8.5961337534888447 7.6686078358960952 9.4143581868518975 9.9729016686204481 10.183427229849748 11.189932572428278 9.9547603467135506 8.9256405149628666 9.2448770552464179 6.2772072401787113 8.8064390405316999 8.1147136221484395 7.157190164250415 9.6700347934801432 6.9399320106773583 8.5415345228023956 9.3457974093561873 5.8627785394799368 10.687003177158442 9.6788428750956506 10.048012048968754 7.084645445778885 4.7431914838854663 8.8894185977432674 10.326884257608627 7.7728790242810479 8.7277296056912128 7.5092804699947697 8.8562335561431595 8.1050659404345229 10.797659456791925 11.140124042697861 7.9832695164042695 6.7044143549641069 6.2461067654815627 8.3971701488165067 8.4365903268841382 6.2626360674327737 8.1727573291355231 9.6293861768737905 8.3480879135848998 9.2198054365918818 8.4310904923628254 8.0668980673902784 6.2324480165505225 8.0179667034935989 10.587207940173004 10.500311039860483 10.74819420148998 9.3886873740147259 7.2635398266357232 7.994126281227893 9.5106449444291865 7.0755552392570715 7.2704520552393639 7.1210908893052611 6.3510602215576917 1.7864118629014598 0.42199441005937488 0.76173997202555699 1.6360798433805215 0.69314718055994529 0.77564840207168906 0.55100741339882253 0.51342224961325666 0.66731642052542384 0.2971372312225361 0.76453717664661835 0.62967475760437175 0.88789125735245711 0.76871836740701938 0.45425527227759638 0.39136618372866283 0.60704448150653356 0.98544359056247166 1.6249174832824866 0.56531380905006046 0.81447946572747032 1.1721724917761382 0.12575120530556025 0.96202862354800878 0.58778666490211906 0.68511500886268106 0.43567095016523022 1.7491998548092591 1.3989637642205535 0.88459364513090055 1.4555871876158399 0.52532006991644331 0.8237367502635472 0.47000362924573563 1.4868181988861897 1.7469364256197339 0.60540826625193855 0.44404459007563946 0.82986100387576744 1.5564589876432138 1.4911047254722358 0.92853794133402046 0.5944312076207876 1.4407825464039603 0.40613155265132483 0.37225297390205087 0.37706563358646639 0.40613155265132483 1.7020170937271937 0.63392782089997413 1.2778736121654701 1.0986122886681098 0.91228271047661635 1.7779985539780179 0.87254780892623618 0.96926261664026081 0.7751878908961547 1.6054298910365616 1.4452705662201879 0.53180403015118238 1.34755353280346 0.95628038009031346 0.62860865942237409 0.68662596356967986 0.70951253464620956 1.161587087829498 1.5452193401074492 0.42395969074432877 0.37637952721306783 1.383289852099592 0.43178241642553783 0.79615493063417442 0.7751878908961547 1.3454723665996355 1.6158175193981394 1.5845302767279155 0.78390154382840938 1.1502555218199482 1.097278065654973 0.12839321476839899 0.35767444427181588 0.74098450997410537 0.9313763692921958 0.72027584794819799 0.46184544154427198 1.5118250835670999 0.74050775191978291 1.0678093795130645 0.38933572617828072 0.81624937769392869 0.3492474281099357 1.0609104214840981 0.9086617047096639 1.5310438450060884 1.2527629684953681 0.81137456192459512 0.96355592434126924 0.93334448643998269 0.40945712937770185 0.56758395758459956 1.1154694057345327 1.6170091779304185 0.87962674750256364 0.40212620684264982 0.52057791520866903 0.15100287353652742 1.5025206300880229 1.7864118629014598 0.94468380637537297 0.51162530393655492 1.8110717802604279 0.24998020526776946 1.4780678985817615 1.4727013888606293 0.46373401623214022 0.80065538827523053 1.1960414339996557 0.37156355643248301 0.89445403726498074 0.48858001481867092 0.78070007756780679 1.5503246479415937 0.66217237626051473 1.1167795926235586 1.1939224684724346 0.95049890320389219 0.64185388617239469 0.58444776363660444 0.73764242044649664 0.75846664668058783 0.91629073187415511 1.9351380520734023 1.6921232790527083 0.68712910823438234 0.66680320522034331 0.76360564420850674 1.163463260987726 0.69314718055994529 1.451613827240533 0.87921172363273425 1.3347378742054885 1.0501220795076758 0.87962674750256364 1.1151415906193203 0.34712953109520095 0.27155269052189734 0.56360780920496012 0.79027389129066816 0.32858406377220672 0.3562748639173926 0.42461392694692518 1.6643048138749406 0.64553132661828205 1.3252165116113002 1.2493285060467332 0.97040005752118697 1.5271426697072703 0.44596705141749426 0.85015092936961001 1.553502280103797 0.31261855774181252 0.31626952930369356 0.39001300354924279 1.3964921860963366 1.83784757342081 0.86836019811660503 0.4081282255276481 0.80424122806553211 0.69064405034182685 1.441019260809137 0.81801616260581456 1.1549926221042173 0.65492596773974754 0.42918163472548043 1.0195690813276568 1.1512047387872804 1.7045662575256777 0.33432708027482477 0.42395969074432877 1.3517029163502716 1.3305173456508921 0.48980625654191517 0.64657954474361057 0.7040871205982796 0.8398415597107487 1.3083328196501789 1.7751218280750316 0.39406706315579509 0.53473744381230359 0.62433286455958559 0.73092454489397518 0.71441931583548512 0.81713316034093642 1.3217558399823195 0.87171168847618763 0.55961578793542266 1.5969603909229877 1.8405496333974869 1.1343011310766167

Variable Transformation; file UN11

29

A linear regression model with more than one independent variable is called a multiple linear regression model.

Multiple Linear Regression

Note: The error term ε is assumed to be normally distributed with

a zero mean and a constant unknown standard deviation σ.

30

We estimate the regression coefficients β0, β1, β2,…, βk by finding b0, b1, b2,… bk, then we use the estimated regression equation:

The estimated regression coefficient bj (j = 1,2,…,k) represents the expected change in the dependent variable Y when the associated independent variable Xj is increased by one unit while the values of all other independent variables are held constant.

Estimated Multiple Regression Equation

31

ANOVA Table for Multiple Regression

32

Testing for Significance

33

Example: Adding House Age to Predict Market Value

Although House Age is found insignificant, both adjusted R Square and Standard Error improve.

34

SUMMARY OUTPUT
Regression Statistics
Multiple R 0.7455
R Square 0.5558
Adjusted R Square 0.5330
Standard Error 7211.8485
Observations 42
ANOVA
df SS MS F Significance F
Regression 2 2537650171 1268825085 24.3954 0.0000
Residual 39 2028419591 52010758.75
Total 41 4566069762
Coefficients Standard Error t Stat P-value Lower 95% Upper 95%
Intercept 47331.38154 13884.34664 3.408974347 0.0015 19247.6396 75415.1234
House Age -825.1612203 607.3128421 -1.358708664 0.1820 -2053.5674 403.2450
Square Feet 40.91106845 6.696523994 6.109299165 0.0000 27.3661 54.4561

Predict student graduation rates using several indicators:

Example 8.12: Interpreting Regression Results for the Colleges and Universities Data

35

Regression model

The value of R2 indicates that 53.44% of the variation in Graduation% is explained by the four independent variables.

All independent variables are statistically significant at α = 0.05.

Example 8.12 Continued

36

Model Building Issues

37

Construct a model with all available independent variables. Check for significance of the independent variables by examining the p-values.

Identify the independent variable having the largest p-value that exceeds the chosen level of significance.

Remove the variable identified in step 2 from the model and evaluate adjusted R2 and Standard Error

(Don’t remove all variables with p-values that exceed α at the same time, but remove only one at a time.)

In general, continue until all variables are significant and/or adjusted R2 and Standard Error cannot be improved.

Systematic Model Building Approach

38

Banking Data (Predicting Customer Average Bank Balance)

Example 8.13: Identifying the Best Regression Model

Home Value has the largest p-value; drop and re-run the regression.

39

Banking Data regression after removing Home Value

Example 8.13 Continued

Adjusted R2 and Standard Error improve. All X variables are significant.

40

Income and Wealth are highly correlated!

Remove one of them.

Multicollinearity

41

Colleges and Universities correlation matrix; none exceed the recommended threshold of ±0.7

Banking Data correlation matrix; large correlations exist

Example 8.14: Identifying Potential Multicollinearity

42

If we remove Wealth from the model, adjusted R2 = 0.9201 and s = 2458, but we discover that Education is no longer significant.

Dropping Education and leaving only Age and Income in the model results in adjusted R2 = 0.9202 and s = 2457.

However, if we remove Income from the model instead of Wealth, adjusted R2 = 0.9345, s = 2226, and all remaining variables (Age, Education, and Wealth) are significant:

Example 8.14 Continued

43

The regression analysis tool in XLMiner has some advanced options not available in Regression tool of Data Analysis of Excel.

Best-subsets regression evaluates either all possible regression models for a set of independent variables or the best subsets of models for a fixed number of independent variables.

Advanced Techniques for Regression Modeling using XLMiner

44

In XLMiner regression models are evaluated by minimizing Mallow’s statistic Cp.

Backward Elimination begins with all independent variables in the model and deletes one at a time until the best model is identified.

Forward Selection begins with a model having no independent variables and successively adds one at a time until no additional variable makes a significant contribution.

Stepwise Selection is similar to Forward Selection except that at each step, the procedure considers dropping variables that are not statistically significant.

Sequential Replacement replaces variables sequentially, retaining those that improve performance. These options might terminate with a different model.

Exhaustive Search looks at all combinations of variables to find the one with the best fit, but it can be time consuming for large numbers of variables.

Best-Subsets Procedures

45

Click the Predict button in the Data Mining group and choose Multiple Linear Regression.

Enter the range of the data (including headers)

Move the appropriate variables to the boxes on the right.

Example 8.19: Using XLMiner for Regression on the file: Banking Data

46

Select the output options and check the Summary report box. Before clicking Finish, click on the Best subsets button.

Select the best subsets option:

Example 8.19 Continued

47

Regression output (all variables):

Best subsets results:

Example 8.19 Continued

The strongly correlated Income and Wealth are kept together!

If you click “Choose Subset,” XLMiner will create a new worksheet

with the results for this model.

48

Identifying the best regression model often requires experimentation and trial and error.

The independent variables selected should make sense in attempting to explain the dependent variable

Logic should guide your model development. In many applications, behavioral, economic, or physical theory might suggest that certain variables should belong in a model.

Additional variables increase R2 and, therefore, help to explain a larger proportion of the variation.

Even though a variable with a large p-value is not statistically significant, it could simply be the result of sampling error and a modeler might wish to keep it.

Good models are as simple as possible (the principle of parsimony).

Practical Issues in Regression Modeling

49

Regression analysis requires numerical data.

Categorical data can be included as independent variables, but must be coded numeric using dummy variables.

For categorical variables with 2 levels, one dummy variable (coded as 0 or 1), is needed.

For categorical variables with m levels, m – 1 dummy variables are needed.

Regression with Categorical Variables

50

Employee Salaries provides data for 35 employees

Predict Salary using Age and MBA (coded as yes=1, no=0)

Example 8.15: A Model with Categorical Variables

51

Example 8.15 Continued

52

Interactions

53

Define an interaction between Age and MBA and re-run the regression.

Example 8.16: Incorporating Interaction Terms in a Regression Model

The MBA variable becomes insignificant; drop it and re-run.

54

Example 8.16 Continued

55

Example 8.17: A Regression Model with Multiple Levels of Categorical Variables

The Excel file Surface Finish provides measurements of the surface finish of 35 parts produced on a lathe, along with the revolutions per minute (RPM) of the spindle and one of four types of cutting tools used.

56

Because we have a continuous independent variable RPM, and a categorical independent variable Cutting Tool with m = 4 levels, we define a regression model of the form:

Example 8.17 Continued

57

Note. There are m – 1 dummies defined.

Add 3 columns to the data, one for each of the three tool type variables

Dummy variables can be created in XLMiner by using Transform > Transform Categorical Data > Create Dummies

Example 8.17 Continued

58

Regression results:

Example 8.17 Continued

59

Curvilinear models may be appropriate when scatter charts or residual plots show nonlinear relationships.

A second order polynomial might be used

Here β1 represents the linear effect of X on Y and β2 represents the curvilinear effect.

This model is linear in the β parameters so we can use linear regression methods.

Regression Models with Nonlinear Terms

60

The U-shape of the residual plot (a second-order polynomial trendline was fit to the residual data) suggests that a linear relationship is not appropriate.

Example 8.18: Modeling Beverage Sales Using Curvilinear Regression

61

Example 8.18 Continued

62

Regression Statistics

Multiple R0.439989

R Square0.19359

Adjusted R Square0.189497

Standard Error1.206005

Observations199

ANOVA

dfSSMSFSignificance F

Regression168.7847768.7847747.292727.9E-11

Residual197286.52621.454447

Total198355.3109

CoefficientsStandard Errort StatP-valueLower 95%Upper 95%

Intercept3.1779120.10477330.331463.69E-762.9712913.384532

ppgdp-3.2E-054.65E-06-6.876977.9E-11-4.1E-05-2.3E-05

UNdata

region group fertility ppgdp lifeExpF pctUrban
Afghanistan Asia other 5.968 499 49.49 23
Albania Europe other 1.525 3677.2 80.4 53
Algeria Africa africa 2.142 4473 75 67
Angola Africa africa 5.135 4321.9 53.17 59
Anguilla Caribbean other 2 13750.1 81.1 100
Argentina Latin Amer other 2.172 9162.1 79.89 93
Armenia Asia other 1.735 3030.7 77.33 64
Aruba Caribbean other 1.671 22851.5 77.75 47
Australia Oceania oecd 1.949 57118.9 84.27 89
Austria Europe oecd 1.346 45158.8 83.55 68
Azerbaijan Asia other 2.148 5637.6 73.66 52
Bahamas Caribbean other 1.877 22461.6 78.85 84
Bahrain Asia other 2.43 18184.1 76.06 89
Bangladesh Asia other 2.157 670.4 70.23 29
Barbados Caribbean other 1.575 14497.3 80.26 45
Belarus Europe other 1.479 5702 76.37 75
Belgium Europe oecd 1.835 43814.8 82.81 97
Belize Latin Amer other 2.679 4495.8 77.81 53
Benin Africa africa 5.078 741.1 58.66 42
Bermuda Caribbean other 1.76 92624.7 82.3 100
Bhutan Asia other 2.258 2047.2 69.84 35
Bolivia Latin Amer other 3.229 1977.9 69.4 67
Bosnia and Herzegovina Europe other 1.134 4477.7 78.4 49
Botswana Africa africa 2.617 7402.9 51.34 62
Brazil Latin Amer other 1.8 10715.6 77.41 87
Brunei Darussalam Asia other 1.984 32647.6 80.64 76
Bulgaria Europe other 1.546 6365.1 77.12 72
Burkina Faso Africa africa 5.75 519.7 57.02 27
Burundi Africa africa 4.051 176.6 52.58 11
Cambodia Asia other 2.422 797.2 65.1 20
Cameroon Africa africa 4.287 1206.6 53.56 59
Canada North America oecd 1.691 46360.9 83.49 81
Cape Verde Africa africa 2.279 3244 77.7 62
Cayman Islands Caribbean other 1.6 57047.9 83.8 100
Central African Republic Africa africa 4.423 450.8 51.3 39
Chad Africa africa 5.737 727.4 51.61 28
Chile Latin Amer oecd 1.832 11887.7 82.35 89
China Asia other 1.559 4354 75.61 48
Colombia Latin Amer other 2.293 6222.8 77.69 75
Comoros Africa africa 4.742 736.6 63.18 28
Congo Africa africa 4.442 2665.1 59.33 63
Cook Islands Oceania other 2.5308062841 12212.1 76.2454672362 76
Costa Rica Latin Amer other 1.812 7703.8 81.99 65
Cote dIvoire Africa africa 4.224 1154.1 57.71 51
Croatia Europe other 1.501 13819.5 80.37 58
Cuba Caribbean other 1.451 5704.4 81.33 75
Cyprus Asia other 1.458 28364.3 82.14 71
Czech Republic Europe oecd 1.501 18838.8 81 74
Democratic Republic of the Congo Africa africa 5.485 200.6 50.56 36
Denmark Europe oecd 1.885 55830.2 81.37 87
Djibouti Africa africa 3.589 1282.6 60.04 76
Dominica Caribbean other 3 7020.8 78.2 67
Dominican Republic Caribbean other 2.49 5195.4 76.57 70
East Timor Asia other 5.918 706.1 64.2 29
Ecuador Latin Amer other 2.393 4072.6 78.91 68
Egypt Africa africa 2.636 2653.7 75.52 44
El Salvador Latin Amer other 2.171 3425.6 77.09 65
Equatorial Guinea Africa africa 4.98 16852.4 52.91 40
Eritrea Africa africa 4.243 429.1 64.41 22
Estonia Europe oecd 1.702 14135.4 79.95 70
Ethiopia Africa africa 3.848 324.6 61.59 17
Fiji Oceania other 2.602 3545.7 72.27 52
Finland Europe oecd 1.875 44501.7 83.28 85
France Europe oecd 1.987 39545.9 84.9 86
French Polynesia Oceania other 2.033 24669 78.07 51
Gabon Africa africa 3.195 12468.8 64.32 86
Gambia Africa africa 4.689 579.1 60.3 59
Georgia Asia other 1.528 2680.3 77.31 53
Germany Europe oecd 1.457 39857.1 82.99 74
Ghana Africa africa 3.988 1333.2 65.8 52
Greece Europe oecd 1.54 26503.8 82.58 62
Greenland NorthAtlantic other 2.217 35292.7 71.6 84
Grenada Caribbean other 2.171 7429 77.72 40
Guatemala Latin Amer other 3.84 2882.3 75.1 50
Guinea Africa africa 5.032 427.5 56.39 36
Guinea-Bissau Africa africa 4.877 539.4 50.4 30
Guyana Latin Amer other 2.19 2996 73.45 29
Haiti Caribbean other 3.159 612.7 63.87 54
Honduras Latin Amer other 2.996 2026.2 75.92 52
Hong Kong Asia other 1.137 31823.7 86.35 100
Hungary Europe oecd 1.43 12884 78.47 68
Iceland Europe other 2.098 39278 83.77 94
India Asia other 2.538 1406.4 67.62 30
Indonesia Asia other 2.055 2949.3 71.8 45
Iran Asia other 1.587 5227.1 75.28 71
Iraq Asia other 4.535 888.5 72.6 66
Ireland Europe oecd 2.097 46220.3 83.17 62
Israel Asia oecd 2.909 29311.6 84.19 92
Italy Europe oecd 1.476 33877.1 84.62 69
Jamaica Caribbean other 2.262 4899 75.98 52
Japan Asia oecd 1.418 43140.9 87.12 67
Jordan Asia other 2.889 4445.3 75.17 79
Kazakhstan Asia other 2.481 9166.7 72.84 59
Kenya Africa africa 4.623 801.8 59.16 23
Kiribati Oceania other 3.5 1468.2 63.1 44
Kuwait Asia other 2.251 45430.4 75.89 98
Kyrgyzstan Asia other 2.621 865.4 72.36 35
Laos Asia other 2.543 1047.6 69.42 34
Latvia Europe other 1.506 10663 78.51 68
Lebanon Asia other 1.764 9283.7 75.07 87
Lesotho Africa africa 3.051 980.7 48.11 28
Liberia Africa africa 5.038 218.6 58.59 48
Libya Africa africa 2.41 11320.8 77.86 78
Lithuania Europe other 1.495 10975.5 78.28 67
Luxembourg Europe oecd 1.683 105095.4 82.67 85
Macao Asia other 1.163 49990.2 83.8 100
Madagascar Africa africa 4.493 421.9 68.61 31
Malawi Africa africa 5.968 357.4 55.17 20
Malaysia Asia other 2.572 8372.8 76.86 73
Maldives Asia other 1.668 4684.5 78.7 41
Mali Africa africa 6.117 598.8 53.14 37
Malta Europe other 1.284 19599.2 82.29 95
Marshall Islands Oceania other 4.3844662585 3069.4 70.6 72
Mauritania Africa africa 4.361 1131.1 60.95 42
Mauritius Africa africa 1.59 7488.3 76.89 42
Mexico Latin Amer oecd 2.227 9100.7 79.64 78
Micronesia Oceania other 3.307 2678.2 70.17 23
Moldova Europe other 1.45 1625.8 73.48 48
Mongolia Asia other 2.446 2246.7 72.83 63
Montenegro Europe other 1.63 6509.8 77.37 61
Morocco Africa africa 2.183 2865 74.86 59
Mozambique Africa africa 4.713 407.5 51.81 39
Myanmar Asia other 1.939 876.2 67.87 34
Namibia Africa africa 3.055 5124.7 63.04 39
Nauru Oceania other 3.3 6190.1 57.1 100
Nepal Asia other 2.587 534.7 70.05 19
Neth Antilles Caribbean other 1.9 20321.1 79.86 93
Netherlands Europe oecd 1.794 46909.7 82.79 83
New Caledonia Oceania other 2.091 35319.5 80.49 57
New Zealand Oceania oecd 2.135 32372.1 82.77 86
Nicaragua Latin Amer other 2.5 1131.9 77.45 58
Niger Africa africa 6.925 357.7 55.77 17
Nigeria Africa africa 5.431 1239.8 53.38 51
North Korea Asia other 1.988 504 72.12 60
Norway Europe oecd 1.948 84588.7 83.47 80
Oman Asia other 2.146 20791 76.44 73
Pakistan Asia other 3.201 1003.2 66.88 36
Palau Oceania other 2 10821.8 72.1 84
Palestinian Territory Asia other 4.27 1819.5 74.81 74
Panama Latin Amer other 2.409 7614 79.07 75
Papua New Guinea Oceania other 3.799 1428.4 65.52 13
Paraguay Latin Amer other 2.858 2771.1 74.91 62
Peru Latin Amer other 2.41 5410.7 76.9 77
Philippines Asia other 3.05 2140.1 72.57 49
Poland Europe oecd 1.415 12263.2 80.56 61
Portugal Europe oecd 1.312 21437.6 82.76 61
Puerto Rico Caribbean other 1.757 26461 83.2 99
Qatar Asia other 2.204 72397.9 78.24 96
Republic of Korea Asia other 1.389 21052.2 83.95 83
Romania Europe other 1.428 7522.4 77.95 58
Russian Federation Europe other 1.529 10351.4 75.01 73
Rwanda Africa africa 5.282 532.3 57.13 19
Saint Lucia Caribbean other 1.907 6677.1 77.54 28
Samoa Oceania other 3.763 3343.3 76.02 20
Sao Tome and Principe Africa africa 3.488 1283.3 66.48 63
Saudi Arabia Asia other 2.639 15835.9 75.57 82
Senegal Africa africa 4.605 1032.7 60.92 43
Serbia Europe other 1.562 5123.2 77.05 56
Seychelles Africa africa 2.34 11450.6 78 56
Sierra Leone Africa africa 4.728 351.7 48.87 39
Singapore Asia other 1.367 43783.1 83.71 100
Slovakia Europe oecd 1.372 15976 79.53 55
Slovenia Europe oecd 1.477 23109.8 82.84 49
Solomon Islands Oceania other 4.041 1193.5 70 19
Somalia Africa africa 6.283 114.8 53.38 38
South Africa Africa africa 2.383 7254.8 54.09 62
Spain Europe other 1.504 30542.8 84.76 78
Sri Lanka Asia other 2.235 2375.3 78.4 14
St Vincent and Grenadines Caribbean other 1.995 6171.7 74.73 50
Sudan Africa africa 4.225 1824.9 63.82 41
Suriname Latin Amer other 2.266 7018 74.18 70
Swaziland Africa africa 3.174 3311.2 48.54 21
Sweden Europe oecd 1.925 48906.2 83.65 85
Switzerland Europe oecd 1.536 68880.2 84.71 74
Syria Asia other 2.772 2931.5 77.72 56
Tajikistan Asia other 3.162 816 71.23 26
Tanzania Africa africa 5.499 516 60.31 27
TFYR Macedonia Europe other 1.397 4434.5 77.14 59
Thailand Asia other 1.528 4612.8 77.76 34
Togo Africa africa 3.864 524.6 59.4 44
Tonga Oceania other 3.783 3543.1 75.38 24
Trinidad and Tobago Caribbean other 1.632 15205.1 73.82 14
Tunisia Africa africa 1.909 4222.1 77.05 68
Turkey Asia oecd 2.022 10095.1 76.61 70
Turkmenistan Asia other 2.316 4587.5 69.4 50
Tuvalu Oceania other 3.7 3187.2 65.1 51
Uganda Africa africa 5.901 509 55.44 13
Ukraine Europe other 1.483 3035 74.58 69
United Arab Emirates Asia other 1.707 39624.7 78.02 84
United Kingdom Europe oecd 1.867 36326.8 82.42 80
United States North America oecd 2.077 46545.9 81.31 83
Uruguay Latin Amer other 2.043 11952.4 80.66 93
Uzbekistan Asia other 2.264 1427.3 71.9 36
Vanuatu Oceania other 3.75 2963.5 73.58 26
Venezuela Latin Amer other 2.391 13502.7 77.73 94
Viet Nam Asia other 1.75 1182.7 77.44 31
Yemen Asia other 4.938 1437.2 67.66 32
Zambia Africa africa 6.3 1237.8 50.04 36
Zimbabwe Africa africa 3.109 573.1 52.72 39

Ferility-ppgdp

ppgdp fertility SUMMARY OUTPUT
Afghanistan 499 5.968
Albania 3677.2 1.525 Regression Statistics
Algeria 4473 2.142 Multiple R 0.439989055
Angola 4321.9 5.135 R Square 0.1935903686
Anguilla 13750.1 2 Adjusted R Square 0.1894969186
Argentina 9162.1 2.172 Standard Error 1.2060047574
Armenia 3030.7 1.735 Observations 199
Aruba 22851.5 1.671
Australia 57118.9 1.949 ANOVA
Austria 45158.8 1.346 df SS MS F Significance F
Azerbaijan 5637.6 2.148 Regression 1 68.7847730399 68.7847730399 47.2927171482 0.0000000001
Bahamas 22461.6 1.877 Residual 197 286.5261525659 1.454447475
Bahrain 18184.1 2.43 Total 198 355.3109256058
Bangladesh 670.4 2.157
Barbados 14497.3 1.575 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0%
Belarus 5702 1.479 Intercept 3.1779116422 0.1047727783 30.3314629275 3.69486423775359E-76 2.9712914427 3.3845318417 2.9712914427 3.3845318417
Belgium 43814.8 1.835 ppgdp -0.0000320112 0.0000046548 -6.8769700558 0.0000000001 -0.0000411909 -0.0000228315 -0.0000411909 -0.0000228315
Belize 4495.8 2.679
Benin 741.1 5.078
Bermuda 92624.7 1.76
Bhutan 2047.2 2.258 RESIDUAL OUTPUT PROBABILITY OUTPUT
Bolivia 1977.9 3.229
Bosnia and Herzegovina 4477.7 1.134 Observation Predicted fertility Residuals Percentile fertility
Botswana 7402.9 2.617 1 3.1619380468 2.8060619532 0.2512562814 1.134
Brazil 10715.6 1.8 2 3.0602000087 -1.5352000087 0.7537688442 1.137
Brunei Darussalam 32647.6 1.984 3 3.0347254851 -0.8927254851 1.256281407 1.163
Bulgaria 6365.1 1.546 4 3.0395623795 2.0954376205 1.7587939698 1.284
Burkina Faso 519.7 5.75 5 2.7377542583 -0.7377542583 2.2613065327 1.312
Burundi 176.6 4.051 6 2.8846217049 -0.7126217049 2.7638190955 1.346
Cambodia 797.2 2.422 7 3.0808952581 -1.3458952581 3.2663316583 1.367
Cameroon 1206.6 4.287 8 2.4464074017 -0.7754074017 3.7688442211 1.372
Canada 46360.9 1.691 9 1.3494663513 0.5995336487 4.2713567839 1.389
Cape Verde 3244 2.279 10 1.7323236634 -0.3863236634 4.7738693467 1.397
Cayman Islands 57047.9 1.6 11 2.9974452261 -0.8494452261 5.2763819095 1.415
Central African Republic 450.8 4.423 12 2.4588885737 -0.5818885737 5.7788944724 1.418
Chad 727.4 5.737 13 2.5958165386 -0.1658165386 6.2814070352 1.428
Chile 11887.7 1.832 14 3.1564513248 -0.9994513248 6.783919598 1.43
China 4354 1.559 15 2.7138354797 -1.1388354797 7.2864321608 1.45
Colombia 6222.8 2.293 16 2.995383704 -1.516383704 7.7889447236 1.451
Comoros 736.6 4.742 17 1.7753467341 0.0596532659 8.2914572864 1.457
Congo 2665.1 4.442 18 3.0339956295 -0.3549956295 8.7939698492 1.458
Cook Islands 12212.1 2.5308062841 19 3.154188132 1.923811868 9.2964824121 1.476
Costa Rica 7703.8 1.812 20 0.2128826145 1.5471173855 9.7989949749 1.477
Cote dIvoire 1154.1 4.224 21 3.1123782863 -0.8543782863 10.3015075377 1.479
Croatia 13819.5 1.501 22 3.1145966634 0.1144033366 10.8040201005 1.483
Cuba 5704.4 1.451 23 3.0345750324 -1.9005750324 11.3065326633 1.495
Cyprus 28364.3 1.458 24 2.9409358313 -0.3239358313 11.8090452261 1.501
Czech Republic 18838.8 1.501 25 2.8348922851 -1.0348922851 12.3115577889 1.501
Democratic Republic of the Congo 200.6 5.485 26 2.1328223551 -0.1488223551 12.8140703518 1.504
Denmark 55830.2 1.885 27 2.9741570685 -1.4281570685 13.3165829146 1.506
Djibouti 1282.6 3.589 28 3.1612754146 2.5887245854 13.8190954774 1.525
Dominica 7020.8 3 29 3.1722584619 0.8787415381 14.3216080402 1.528
Dominican Republic 5195.4 2.49 30 3.152392303 -0.730392303 14.824120603 1.528
East Timor 706.1 5.918 31 3.1392869122 1.1477130878 15.3266331658 1.529
Ecuador 4072.6 2.393 32 1.6938429839 -0.0028429839 15.8291457286 1.536
Egypt 2653.7 2.636 33 3.0740672663 -0.7950672663 16.3316582915 1.54
El Salvador 3425.6 2.171 34 1.3517391475 0.2482608525 16.8341708543 1.546
Equatorial Guinea 16852.4 4.98 35 3.1634809872 1.2595190128 17.3366834171 1.559
Eritrea 429.1 4.243 36 3.1546266856 2.5823733144 17.8391959799 1.562
Estonia 14135.4 1.702 37 2.797371942 -0.965371942 18.3417085427 1.575
Ethiopia 324.6 3.848 38 3.0385348195 -1.4795348195 18.8442211055 1.587
Fiji 3545.7 2.602 39 2.9787122641 -0.6857122641 19.3467336683 1.59
Finland 44501.7 1.875 40 3.1543321825 1.5876678175 19.8492462312 1.6
France 39545.9 1.987 41 3.0925985577 1.3494014423 20.351758794 1.63
French Polynesia 24669 2.033 42 2.7869875044 -0.2561812203 20.8542713568 1.632
Gabon 12468.8 3.195 43 2.9313036572 -1.1193036572 21.3567839196 1.668
Gambia 579.1 4.689 44 3.1409675009 1.0830324991 21.8592964824 1.671
Georgia 2680.3 1.528 45 2.7355326801 -1.2345326801 22.3618090452 1.683
Germany 39857.1 1.457 46 2.9953068771 -1.5443068771 22.864321608 1.691
Ghana 1333.2 3.988 47 2.269935985 -0.811935985 23.3668341709 1.702
Greece 26503.8 1.54 48 2.5748587972 -1.0738587972 23.8693467337 1.707
Greenland 35292.7 2.217 49 3.1714901928 2.3135098072 24.3718592965 1.735
Grenada 7429 2.171 50 1.3907192019 0.4942807981 24.8743718593 1.75
Guatemala 2882.3 3.84 51 3.13685406 0.45214594 25.3768844221 1.757
Guinea 427.5 5.032 52 2.9531673159 0.0468326841 25.8793969849 1.76
Guinea-Bissau 539.4 4.877 53 3.0116005847 -0.5216005847 26.3819095477 1.764
Guyana 2996 2.19 54 3.1553085245 2.7626914755 26.8844221106 1.794
Haiti 612.7 3.159 55 3.0475427749 -0.6545427749 27.3869346734 1.8
Honduras 2026.2 2.996 56 3.0929634855 -0.4569634855 27.8894472362 1.812
Hong Kong 31823.7 1.137 57 3.0682540299 -0.8972540299 28.391959799 1.832
Hungary 12884 1.43 58 2.6384458713 2.3415541287 28.8944723618 1.835
Iceland 39278 2.098 59 3.1641756306 1.0788243694 29.3969849246 1.867
India 1406.4 2.538 60 2.7254203378 -1.0234203378 29.8994974874 1.875
Indonesia 2949.3 2.055 61 3.1675208024 0.6804791976 30.4020100503 1.877
Iran 5227.1 1.587 62 3.0644094832 -0.4624094832 30.9045226131 1.885
Iraq 888.5 4.535 63 1.7533582317 0.1216417683 31.4070351759 1.9
Ireland 46220.3 2.097 64 1.9119994025 0.0750005975 31.9095477387 1.907
Israel 29311.6 2.909 65 2.3882270215 -0.3552270215 32.4120603015 1.909
Italy 33877.1 1.476 66 2.7787702259 0.4162297741 32.9145728643 1.925
Jamaica 4899 2.262 67 3.1593739486 1.5296260514 33.4170854271 1.939
Japan 43140.9 1.418 68 3.0921119872 -1.5641119872 33.9195979899 1.948
Jordan 4445.3 2.889 69 1.9020375129 -0.4450375129 34.4221105528 1.949
Kazakhstan 9166.7 2.481 70 3.1352342926 0.8527657074 34.9246231156 1.984
Kenya 801.8 4.623 71 2.3294928474 -0.7894928474 35.4271356784 1.987
Kiribati 1468.2 3.5 72 2.0481494949 0.1688505051 35.9296482412 1.988
Kuwait 45430.4 2.251 73 2.9401003387 -0.7691003387 36.432160804 1.995
Kyrgyzstan 865.4 2.621 74 3.0856457221 0.7543542779 36.9346733668 2
Laos 1047.6 2.543 75 3.1642268485 1.8677731515 37.4371859296 2
Latvia 10663 1.506 76 3.1606447937 1.7163552063 37.9396984925 2.022
Lebanon 9283.7 1.764 77 3.0820060472 -0.8920060472 38.4422110553 2.033
Lesotho 980.7 3.051 78 3.1582983718 0.0007016282 38.9447236181 2.043
Liberia 218.6 5.038 79 3.1130505218 -0.1170505218 39.4472361809 2.055
Libya 11320.8 2.41 80 2.1591963938 -1.0221963938 39.9497487437 2.077
Lithuania 10975.5 1.495 81 2.7654791702 -1.3354791702 40.4522613065 2.091
Luxembourg 105095.4 1.683 82 1.9205752065 0.1774247935 40.9547738693 2.097
Macao 49990.2 1.163 83 3.1328910718 -0.5948910718 41.4572864322 2.098
Madagascar 421.9 4.493 84 3.0835009708 -1.0285009708 41.959798995 2.135
Malawi 357.4 5.968 85 3.0105858292 -1.4235858292 42.4623115578 2.142
Malaysia 8372.8 2.572 86 3.1494696792 1.3855303208 42.9648241206 2.146
Maldives 4684.5 1.668 87 1.6983437605 0.3986562395 43.4673366834 2.148
Mali 598.8 6.117 88 2.2396117627 0.6693882373 43.9698492462 2.157
Malta 19599.2 1.284 89 2.0934645684 -0.6174645684 44.472361809 2.171
Marshall Islands 3069.4 4.3844662585 90 3.0210887083 -0.7590887083 44.9748743719 2.171
Mauritania 1131.1 4.361 91 1.7969190907 -0.3789190907 45.4773869347 2.172
Mauritius 7488.3 1.59 92 3.0356121958 -0.1466121958 45.9798994975 2.183
Mexico 9100.7 2.227 93 2.8844744533 -0.4034744533 46.4824120603 2.19
Micronesia 2678.2 3.307 94 3.1522450514 1.4707549486 46.9849246231 2.204
Moldova 1625.8 1.45 95 3.1309127788 0.3690872212 47.4874371859 2.217
Mongolia 2246.7 2.446 96 1.7236294179 0.5273705821 47.9899497487 2.227
Montenegro 6509.8 1.63 97 3.1502091382 -0.5292091382 48.4924623116 2.235
Morocco 2865 2.183 98 3.1443766951 -0.6013766951 48.9949748744 2.251
Mozambique 407.5 4.713 99 2.8365760749 -1.3305760749 49.4974874372 2.258
Myanmar 876.2 1.939 100 2.8807291414 -1.1167291414 50 2.262
Namibia 5124.7 3.055 101 3.1465182453 -0.0955182453 50.5025125628 2.264
Nauru 6190.1 3.3 102 3.170913991 1.867086009 51.0050251256 2.266
Nepal 534.7 2.587 103 2.8155190988 -0.4055190988 51.5075376884 2.279
Neth Antilles 20321.1 1.9 104 2.8265725707 -1.3315725707 52.0100502513 2.293
Netherlands 46909.7 1.794 105 -0.1863196231 1.8693196231 52.5125628141 2.316
New Caledonia 35319.5 2.091 106 1.5776646875 -0.4146646875 53.0150753769 2.34
New Zealand 32372.1 2.135 107 3.1644061113 1.3285938887 53.5175879397 2.383
Nicaragua 1131.9 2.5 108 3.1664708346 2.8015291654 54.0201005025 2.391
Niger 357.7 6.925 109 2.9098881555 -0.3378881555 54.5226130653 2.393
Nigeria 1239.8 5.431 110 3.0279551135 -1.3599551135 55.0251256281 2.409
North Korea 504 1.988 111 3.1587433277 2.9582566723 55.527638191 2.41
Norway 84588.7 1.948 112 2.5505174707 -1.2665174707 56.0301507538 2.41
Oman 20791 2.146 113 3.0796564241 1.3048098344 56.5326633166 2.422
Pakistan 1003.2 3.201 114 3.1417037588 1.2192962412 57.0351758794 2.43
Palau 10821.8 2 115 2.9382020737 -1.3482020737 57.5376884422 2.446
Palestinian Territory 1819.5 4.27 116 2.8865871934 -0.6595871934 58.040201005 2.481
Panama 7614 2.409 117 3.0921792108 0.2148207892 58.5427135678 2.49
Papua New Guinea 1428.4 3.799 118 3.1258678116 -1.6758678116 59.0452261307 2.5
Paraguay 2771.1 2.858 119 3.1059920493 -0.6599920493 59.5477386935 2.5308062841
Peru 5410.7 2.41 120 2.9695250459 -1.3395250459 60.0502512563 2.538
Philippines 2140.1 3.05 121 3.0861995161 -0.9031995161 60.5527638191 2.543
Poland 12263.2 1.415 122 3.1648670728 1.5481329272 61.0552763819 2.572
Portugal 21437.6 1.312 123 3.1498634171 -1.2108634171 61.5577889447 2.587
Puerto Rico 26461 1.757 124 3.0138637774 0.0411362226 62.0603015075 2.602
Qatar 72397.9 2.204 125 2.9797590308 0.3202409692 62.5628140704 2.617
Republic of Korea 21052.2 1.389 126 3.1607952464 -0.5737952464 63.0653266332 2.621
Romania 7522.4 1.428 127 2.5274085758 -0.6274085758 63.567839196 2.636
Russian Federation 10351.4 1.529 128 1.6762752301 0.1177247699 64.0703517588 2.639
Rwanda 532.3 5.282 129 2.0472915944 0.0437084056 64.5728643216 2.679
Saint Lucia 6677.1 1.907 130 2.1416414444 -0.0066414444 65.0753768844 2.772
Samoa 3343.3 3.763 131 3.1416781499 -0.6416781499 65.5778894472 2.858
Sao Tome and Principe 1283.3 3.488 132 3.1664612312 3.7585387688 66.0804020101 2.889
Saudi Arabia 15835.9 2.639 133 3.13822414 2.29277586 66.5829145729 2.909
Senegal 1032.7 4.605 134 3.1617779907 -1.1737779907 67.0854271357 2.996
Serbia 5123.2 1.562 135 0.4701247245 1.4778752755 67.5879396985 3
Seychelles 11450.6 2.34 136 2.5123665067 -0.3663665067 68.0904522613 3.05
Sierra Leone 351.7 4.728 137 3.145797993 0.055202007 68.5929648241 3.051
Singapore 43783.1 1.367 138 2.8314926942 -0.8314926942 69.0954773869 3.055
Slovakia 15976 1.372 139 3.1196672396 1.1503327604 69.5979899497 3.109
Slovenia 23109.8 1.477 140 2.9341782642 -0.5251782642 70.1005025126 3.159
Solomon Islands 1193.5 4.041 141 3.1321868251 0.6668131749 70.6030150754 3.162
Somalia 114.8 6.283 142 3.089205369 -0.231205369 71.1055276382 3.174
South Africa 7254.8 2.383 143 3.0047085704 -0.5947085704 71.608040201 3.195
Spain 30542.8 1.504 144 3.1094044446 -0.0594044446 72.1105527638 3.201
Sri Lanka 2375.3 2.235 145 2.7853517314 -1.3703517314 72.6130653266 3.229
St Vincent and Grenadines 6171.7 1.995 146 2.4916680561 -1.1796680561 73.1155778894 3.3
Sudan 1824.9 4.225 147 2.3308629273 -0.5738629273 73.6180904523 3.307
Suriname 7018 2.266 148 0.8603670235 1.3436329765 74.1206030151 3.488
Swaziland 3311.2 3.174 149 2.5040051777 -1.1150051777 74.6231155779 3.5
Sweden 48906.2 1.925 150 2.9371104913 -1.5091104913 75.1256281407 3.589
Switzerland 68880.2 1.536 151 2.8465507689 -1.3175507689 75.6281407035 3.7
Syria 2931.5 2.772 152 3.1608720734 2.1211279266 76.1306532663 3.75
Tajikistan 816 3.162 153 2.9641695699 -1.0571695699 76.6331658291 3.763
Tanzania 516 5.499 154 3.0708885528 0.6921114472 77.135678392 3.783
TFYR Macedonia 4434.5 1.397 155 3.1368316522 0.3511683478 77.6381909548 3.799
Thailand 4612.8 1.528 156 2.6709852696 -0.0319852696 78.1407035176 3.84
Togo 524.6 3.864 157 3.1448536622 1.4601463378 78.6432160804 3.848
Tonga 3543.1 3.783 158 3.0139117943 -1.4519117943 79.1457286432 3.864
Trinidad and Tobago 15205.1 1.632 159 2.8113640433 -0.4713640433 79.648241206 3.988
Tunisia 4222.1 1.909 160 3.1666532985 1.5613467015 80.1507537688 4.041
Turkey 10095.1 2.022 161 1.7763614895 -0.4093614895 80.6532663317 4.051
Turkmenistan 4587.5 2.316 162 2.6665004987 -1.2945004987 81.1557788945 4.224
Tuvalu 3187.2 3.7 163 2.4381389053 -0.9611389053 81.6582914573 4.225
Uganda 509 5.901 164 3.1397062591 0.9012937409 82.1608040201 4.243
Ukraine 3035 1.483 165 3.1742367549 3.1087632451 82.6633165829 4.27
United Arab Emirates 39624.7 1.707 166 2.945676692 -0.562676692 83.1658291457 4.287
United Kingdom 36326.8 1.867 167 2.2001995569 -0.6961995569 83.6683417085 4.361
United States 46545.9 2.077 168 3.1018754073 -0.8668754073 84.1708542714 4.3844662585
Uruguay 11952.4 2.043 169 2.9803480371 -0.9853480371 84.6733668342 4.423
Uzbekistan 1427.3 2.264 170 3.1194943791 1.1055056209 85.175879397 4.442
Vanuatu 2963.5 3.75 171 2.9532569473 -0.6872569473 85.6783919598 4.493
Venezuela 13502.7 2.391 172 3.0719161127 0.1020838873 86.1809045226 4.535
Viet Nam 1182.7 1.75 173 1.6123648427 0.3126351573 86.6834170854 4.605
Yemen 1437.2 4.938 174 0.9729728685 0.5630271315 87.1859296482 4.623
Zambia 1237.8 6.3 175 3.0840707704 -0.3120707704 87.6884422111 4.689
Zimbabwe 573.1 3.109 176 3.1517904921 0.0102095079 88.1909547739 4.713
177 3.1613938561 2.3376061439 88.6934673367 4.728
178 3.0359579169 -1.6389579169 89.1959798995 4.742
179 3.0302503175 -1.5022503175 89.6984924623 4.877
180 3.1611185597 0.7028814403 90.2010050251 4.938
181 3.0644927124 0.7185072876 90.7035175879 4.98
182 2.691177943 -1.059177943 91.2060301508 5.032
183 3.0427570986 -1.1337570986 91.7085427136 5.038
184 2.8547552429 -0.8327552429 92.2110552764 5.078
185 3.0310602012 -0.7150602012 92.7135678392 5.135
186 3.0758855032 0.6241144968 93.216080402 5.282
187 3.1616179346 2.7393820654 93.7185929648 5.431
188 3.0807576099 -1.5977576099 94.2211055276 5.485
189 1.9094769189 -0.2024769189 94.7236180905 5.499
190 2.0150466992 -0.1480466992 95.2261306533 5.737
191 1.6879209095 0.3890790905 95.7286432161 5.75
192 2.7953008165 -0.7523008165 96.2311557789 5.901
193 3.1322220375 -0.8682220375 96.7336683417 5.918
194 3.0830464116 0.6669535884 97.2361809045 5.968
195 2.7456738325 -0.3546738325 97.7386934673 5.968
196 3.1400519802 -1.3900519802 98.2412060302 6.117
197 3.1319051265 1.8060948735 98.743718593 6.283
198 3.1382881624 3.1617118376 99.2462311558 6.3
199 3.1595660159 -0.0505660159 99.7487437186 6.925

ppgdp Residual Plot

499 3677.2 4473 4321.8999999999996 13750.1 9162.1 3030.7 22851.5 57118.9 45158.8 5637.6 22461.599999999999 18184.099999999999 670.4 14497.3 5702 43814.8 4495.8 741.1 92624.7 2047.2 1977.9 4477.7 7402.9 10715.6 32647.599999999999 6365.1 519.70000000000005 176.6 797.2 1206.5999999999999 46360.9 3244 57047.9 450.8 727.4 11887.7 4354 6222.8 736.6 2665.1 12212.1 7703.8 1154.0999999999999 13819.5 5704.4 28364.3 18838.8 200.6 55830.2 1282.5999999999999 7020.8 5195.3999999999996 706.1 4072.6 2653.7 3425.6 16852.400000000001 429.1 14135.4 324.60000000000002 3545.7 44501.7 39545.9 24669 12468.8 579.1 2680.3 39857.1 1333.2 26503.8 35292.699999999997 7429 2882.3 427.5 539.4 2996 612.70000000000005 2026.2 31823.7 12884 39278 1406.4 2949.3 5227.1000000000004 888.5 46220.3 29311.599999999999 33877.1 4899 43140.9 4445.3 9166.7000000000007 801.8 1468.2 45430.400000000001 865.4 1047.5999999999999 10663 9283.7000000000007 980.7 218.6 11320.8 10975.5 105095.4 49990.2 421.9 357.4 8372.7999999999993 4684.5 598.79999999999995 19599.2 3069.4 1131.0999999999999 7488.3 9100.7000000000007 2678.2 1625.8 2246.6999999999998 6509.8 2865 407.5 876.2 5124.7 6190.1 534.70000000000005 20321.099999999999 46909.7 35319.5 32372.1 1131.9000000000001 357.7 1239.8 504 84588.7 20791 1003.2 10821.8 1819.5 7614 1428.4 2771.1 5410.7 2140.1 12263.2 21437.599999999999 26461 72397.899999999994 21052.2 7522.4 10351.4 532.29999999999995 6677.1 3343.3 1283.3 15835.9 1032.7 5123.2 11450.6 351.7 43783.1 15976 23109.8 1193.5 114.8 7254.8 30542.799999999999 2375.3000000000002 6171.7 1824.9 7018 3311.2 48906.2 68880.2 2931.5 816 516 4434.5 4612.8 524.6 3543.1 15205.1 4222.1000000000004 10095.1 4587.5 3187.2 509 3035 39624.699999999997 36326.800000000003 46545.9 11952.4 1427.3 2963.5 13502.7 1182.7 1437.2 1237.8 573.1 2.8060619532387685 -1.5352000086793103 -0.89272548514221617 2.0954376205294913 -0.73775425831892294 -0.71262170489870202 -1.3458952580720365 -0.77540740167088429 0.59953364866214143 -0.38632366342129698 -0.84944522614334694 -0.58188857373310232 -0.16581653858598022 -0.99945132480312893 -1.1388354797477789 -1.5163837040073971 5.965326591540232E-2 -0.35499562947917829 1.9238118679765552 1.5471173855349225 -0.85437828634387891 0.11440333657504498 -1.9005750324397477 -0.32393583132048676 -1.0348922850509064 -0.14882235514948672 -1.4281570684740383 2.5887245853538952 0.87874153807370314 -0.73039230295781143 1.1477130877635835 -2.8429839240102783E-3 -0.79506726627703506 0.24826085251846997 1.2595190127581355 2.5823733143544665 -0.96537194195235387 -1.4795348195238625 -0.68571226412536834 1.5876678175167451 1.3494014423487206 -0.25618122026659584 -1.1193036572411807 1.0830324990657987 -1.2345326801165175 -1.5443068770954986 -0.81193598503945341 -1.073858797244267 2.3135098071926907 0.49428079809384085 0.45214593997371066 4.6832684080966303E-2 -0.5216005846606917 2.7626914755113652 -0.65454277494399138 -0.45696348548279841 -0.89725402994336312 2.3415541286742005 1.0788243694297179 -1.0234203378378446 0.68047919764079268 -0.46240948322709619 0.12164176832509033 7.500059749682797E-2 -0.35522702151422614 0.41622977409113115 1.5296260514233895 -1.5641119872092539 -0.44503751292696747 0.85276570736624269 -0.78949284736763081 0.16885050512692468 -0.76910033865358818 0.75435427787555742 1.8677731514884517 1.7163552062557308 -0.89200604717323939 7.0162818997188126E-4 -0.11705052182299269 -1.0221963937800616 -1.335479170150385 0.17742479345612971 -0.59489107182084533 -1.0285009708339357 -1.4235858291993628 1.3855303208156702 0.39865623948725459 0.66938823731124941 -0.617464568408022 -0.75908870828018804 -0.37891909072150143 -0.14661219575038098 -0.40347445331756315 1.4707549486233278 0.3690872211605476 0.5273705821085779 -0.52920913821135551 -0.6013766951497086 -1.3305760748700208 -1.1167291413624987 -9.5518245318886308E-2 1.8670860090319312 -0.40551909876710468 -1.3315725707165376 1.8693196231248199 -0.41466468752645325 1.3285938886940216 2.801529165436742 -0.33788815554940399 -1.3599551135311387 2.9582566723252248 -1.2665174706576792 1.3048098344105714 1.219296241160102 -1.3482020737054226 -0.65958719339477856 0.21482078924283465 -1.6758678116247678 -0.65999204929229505 -1.3395250459108095 -0.90319951611437954 1.5481329272226287 -1.2108634171078112 4.1136222559623903E-2 0.32024096920001099 -0.57379524644673729 -0.62740857578280096 0.11772476993017067 4.3708405643127612E-2 -6.6414444111977389E-3 -0.64167814986926475 3.7585387688007295 2.2927758600448498 -1.1737779906947758 1.4778752755272708 -0.36636650665729142 5.520200698016442E-2 -0.83149269419938676 1.1503327603897269 -0.52517826419472602 0.66681317487155978 -0.23120536904241806 -0.59470857043910819 -5.9404444629131525E-2 -1.3703517313615285 -1.179668056143236 -0.57386292729649191 1.343632976537565 -1.1150051777456438 -1.5091104913321947 -1.3175507689315422 2.1211279266413636 -1.0571695699272006 0.69211144720277584 0.35116834782301476 -3.1985269636250369E-2 1.4601463377722537 -1.4519117942603128 -0.47136404328191395 1.5613467015209825 -0.40936148954592722 -1.2945004986541606 -0.96113890527778145 0.90129374086947012 3.1087632450923106 -0.56267669200890547 -0.69619955688469126 -0.86687540726305379 -0.98534803712454577 1.1055056209414991 -0.68725694731624909 0.10208388725612982 0.31263515726594426 0.56302713154329975 -0.31207077043051834 1.0209507852061872E-2 2.3376061438647175 -1.6389579168539254 -1.5022503175241138 0.70288144029902178 0.7185072876183467 -1.0591779429803052 -1.1337570985569647 -0.83275524289806269 -0.71506020122038016 0.62411449680802811 2.7393820653716801 -1.5977576098548845 -0.20247691889582975 -0.14804669920870106 0.38907909053485179 -0.75230081645241675 -0.86822203746306048 0.66695358839479857 -0.35467383248715256 -1.3900519802340745 1.8060948735485218 3.1617118376182671 -5.0566015856357449E-2ppgdp

Residuals

Normal Probability Plot

0.25125628140703515 0.75376884422110546 1.2562814070351758 1.7587939698492461 2.2613065326633164 2.7638190954773867 3.266331658291457 3.7688442211055273 4.2713567839195976 4.7738693467336679 5.2763819095477382 5.7788944723618085 6.2814070351758788 6.7839195979899491 7.2864321608040195 7.7889447236180898 8.2914572864321592 8.7939698492462313 9.2964824120602998 9.7989949748743719 10.30150753768844 10.804020100502512 11.306532663316581 11.809045226130653 12.311557788944722 12.814070351758794 13.316582914572862 13.819095477386934 14.321608040201003 14.824120603015075 15.326633165829143 15.829145728643216 16.331658291457284 16.834170854271353 17.336683417085425 17.839195979899497 18.341708542713565 18.844221105527634 19.346733668341706 19.849246231155778 20.351758793969847 20.854271356783915 21.356783919597987 21.859296482412059 22.361809045226128 22.864321608040196 23.366834170854268 23.86934673366834 24.371859296482409 24.874371859296478 25.37688442211055 25.879396984924622 26.38190954773869 26.884422110552759 27.386934673366831 27.889447236180903 28.391959798994971 28.89447236180904 29.396984924623112 29.899497487437184 30.402010050251253 30.904522613065321 31.407035175879393 31.909547738693465 32.412060301507537 32.914572864321606 33.417085427135675 33.91959798994975 34.422110552763819 34.924623115577887 35.427135678391963 35.929648241206031 36.4321608040201 36.934673366834168 37.437185929648237 37.939698492462313 38.442211055276381 38.94472361809045 39.447236180904525 39.949748743718594 40.452261306532662 40.954773869346731 41.457286432160799 41.959798994974875 42.462311557788944 42.964824120603012 43.467336683417088 43.969849246231156 44.472361809045225 44.974874371859293 45.477386934673362 45.979899497487438 46.482412060301506 46.984924623115575 47.48743718592965 47.989949748743719 48.492462311557787 48.994974874371856 49.497487437185924 50 50.502512562814069 51.005025125628137 51.507537688442213 52.010050251256281 52.51256281407035 53.015075376884418 53.517587939698487 54.020100502512562 54.522613065326631 55.0251256281407 55.527638190954775 56.030150753768844 56.532663316582912 57.035175879396981 57.537688442211049 58.040201005025125 58.542713567839193 59.045226130653262 59.547738693467338 60.050251256281406 60.552763819095475 61.055276381909543 61.557788944723612 62.060301507537687 62.562814070351756 63.065326633165824 63.5678391959799 64.070351758793961 64.572864321608037 65.075376884422113 65.577889447236174 66.08040201005025 66.582914572864311 67.085427135678387 67.587939698492463 68.090452261306524 68.5929648241206 69.095477386934675 69.597989949748737 70.100502512562812 70.603015075376888 71.105527638190949 71.608040201005025 72.110552763819086 72.613065326633162 73.115577889447238 73.618090452261299 74.120603015075375 74.623115577889436 75.125628140703512 75.628140703517587 76.130653266331649 76.633165829145725 77.1356783919598 77.638190954773862 78.140703517587937 78.643216080402013 79.145728643216074 79.64824120603015 80.150753768844211 80.653266331658287 81.155778894472363 81.658291457286424 82.1608040201005 82.663316582914561 83.165829145728637 83.668341708542712 84.170854271356774 84.673366834170849 85.175879396984925 85.678391959798986 86.180904522613062 86.683417085427138 87.185929648241199 87.688442211055275 88.190954773869336 88.693467336683412 89.195979899497488 89.698492462311549 90.201005025125625 90.703517587939686 91.206030150753762 91.708542713567837 92.211055276381899 92.713567839195974 93.21608040201005 93.718592964824111 94.221105527638187 94.723618090452263 95.226130653266324 95.7286432160804 96.231155778894461 96.733668341708537 97.236180904522612 97.738693467336674 98.241206030150749 98.743718592964811 99.246231155778887 99.748743718592962 1.1339999999999999 1.137 1.163 1.284 1.3120000000000001 1.3460000000000001 1.367 1.3720000000000001 1.389 1.397 1.415 1.4179999999999999 1.4279999999999999 1.43 1.45 1.4510000000000001 1.4570000000000001 1.458 1.476 1.4770000000000001 1.4790000000000001 1.4830000000000001 1.4950000000000001 1.5009999999999999 1.5009999999999999 1.504 1.506 1.5249999999999999 1.528 1.528 1.5289999999999999 1.536 1.54 1.546 1.5589999999999999 1.5620000000000001 1.575 1.587 1.59 1.6 1.63 1.6319999999999999 1.6679999999999999 1.671 1.6830000000000001 1.6910000000000001 1.702 1.7070000000000001 1.7350000000000001 1.75 1.7569999999999999 1.76 1.764 1.794 1.8 1.8120000000000001 1.8320000000000001 1.835 1.867 1.875 1.877 1.885 1.9 1.907 1.909 1.925 1.9390000000000001 1.948 1.9490000000000001 1.984 1.9870000000000001 1.988 1.9950000000000001 2 2 2.0219999999999998 2.0329999999999999 2.0430000000000001 2.0550000000000002 2.077 2.0910000000000002 2.097 2.0979999999999999 2.1349999999999998 2.1419999999999999 2.1459999999999999 2.1480000000000001 2.157 2.1709999999999998 2.1709999999999998 2.1720000000000002 2.1829999999999998 2.19 2.2040000000000002 2.2170000000000001 2.2269999999999999 2.2349999999999999 2.2509999999999999 2.258 2.262 2.2639999999999998 2.266 2.2789999999999999 2.2930000000000001 2.3159999999999998 2.34 2.383 2.391 2.3929999999999998 2.4089999999999998 2.41 2.41 2.4220000000000002 2.4300000000000002 2.4460000000000002 2.4809999999999999 2.4900000000000002 2.5 2.5308062840941101 2.5379999999999998 2.5430000000000001 2.5720000000000001 2.5870000000000002 2.6019999999999999 2.617 2.621 2.6360000000000001 2.6389999999999998 2.6789999999999998 2.7719999999999998 2.8580000000000001 2.8889999999999998 2.9089999999999998 2.996 3 3.05 3.0510000000000002 3.0550000000000002 3.109 3.1589999999999998 3.1619999999999999 3.1739999999999999 3.1949999999999998 3.2010000000000001 3.2290000000000001 3.3 3.3069999999999999 3.488 3.5 3.589 3.7 3.75 3.7629999999999999 3.7829999999999999 3.7989999999999999 3.84 3.8479999999999999 3.8639999999999999 3.988 4.0410000000000004 4.0510000000000002 4.2240000000000002 4.2249999999999996 4.2430000000000003 4.2699999999999996 4.2869999999999999 4.3609999999999998 4.3844662585282403 4.423 4.4420000000000002 4.4930000000000003 4.5350000000000001 4.6050000000000004 4.6230000000000002 4.6890000000000001 4.7130000000000001 4.7279999999999998 4.742 4.8769999999999998 4.9379999999999997 4.9800000000000004 5.032 5.0380000000000003 5.0780000000000003 5.1349999999999998 5.282 5.431 5.4850000000000003 5.4989999999999997 5.7370000000000001 5.75 5.9009999999999998 5.9180000000000001 5.968 5.968 6.117 6.2830000000000004 6.3 6.9249999999999998Sample Percentile

fertility

ppgdp Residual Plot

499 3677.2 4473 4321.8999999999996 13750.1 9162.1 3030.7 22851.5 57118.9 45158.8 5637.6 22461.599999999999 18184.099999999999 670.4 14497.3 5702 43814.8 4495.8 741.1 92624.7 2047.2 1977.9 4477.7 7402.9 10715.6 32647.599999999999 6365.1 519.70000000000005 176.6 797.2 1206.5999999999999 46360.9 3244 57047.9 450.8 727.4 11887.7 4354 6222.8 736.6 2665.1 12212.1 7703.8 1154.0999999999999 13819.5 5704.4 28364.3 18838.8 200.6 55830.2 1282.5999999999999 7020.8 5195.3999999999996 706.1 4072.6 2653.7 3425.6 16852.400000000001 429.1 14135.4 324.60000000000002 3545.7 44501.7 39545.9 24669 12468.8 579.1 2680.3 39857.1 1333.2 26503.8 35292.699999999997 7429 2882.3 427.5 539.4 2996 612.70000000000005 2026.2 31823.7 12884 39278 1406.4 2949.3 5227.1000000000004 888.5 46220.3 29311.599999999999 33877.1 4899 43140.9 4445.3 9166.7000000000007 801.8 1468.2 45430.400000000001 865.4 1047.5999999999999 10663 9283.7000000000007 980.7 218.6 11320.8 10975.5 105095.4 49990.2 421.9 357.4 8372.7999999999993 4684.5 598.79999999999995 19599.2 3069.4 1131.0999999999999 7488.3 9100.7000000000007 2678.2 1625.8 2246.6999999999998 6509.8 2865 407.5 876.2 5124.7 6190.1 534.70000000000005 20321.099999999999 46909.7 35319.5 32372.1 1131.9000000000001 357.7 1239.8 504 84588.7 20791 1003.2 10821.8 1819.5 7614 1428.4 2771.1 5410.7 2140.1 12263.2 21437.599999999999 26461 72397.899999999994 21052.2 7522.4 10351.4 532.29999999999995 6677.1 3343.3 1283.3 15835.9 1032.7 5123.2 11450.6 351.7 43783.1 15976 23109.8 1193.5 114.8 7254.8 30542.799999999999 2375.3000000000002 6171.7 1824.9 7018 3311.2 48906.2 68880.2 2931.5 816 516 4434.5 4612.8 524.6 3543.1 15205.1 4222.1000000000004 10095.1 4587.5 3187.2 509 3035 39624.699999999997 36326.800000000003 46545.9 11952.4 1427.3 2963.5 13502.7 1182.7 1437.2 1237.8 573.1 2.8060619532387685 -1.5352000086793103 -0.89272548514221617 2.0954376205294913 -0.73775425831892294 -0.71262170489870202 -1.3458952580720365 -0.77540740167088429 0.59953364866214143 -0.38632366342129698 -0.84944522614334694 -0.58188857373310232 -0.16581653858598022 -0.99945132480312893 -1.1388354797477789 -1.5163837040073971 5.965326591540232E-2 -0.35499562947917829 1.9238118679765552 1.5471173855349225 -0.85437828634387891 0.11440333657504498 -1.9005750324397477 -0.32393583132048676 -1.0348922850509064 -0.14882235514948672 -1.4281570684740383 2.5887245853538952 0.87874153807370314 -0.73039230295781143 1.1477130877635835 -2.8429839240102783E-3 -0.79506726627703506 0.24826085251846997 1.2595190127581355 2.5823733143544665 -0.96537194195235387 -1.4795348195238625 -0.68571226412536834 1.5876678175167451 1.3494014423487206 -0.25618122026659584 -1.1193036572411807 1.0830324990657987 -1.2345326801165175 -1.5443068770954986 -0.81193598503945341 -1.073858797244267 2.3135098071926907 0.49428079809384085 0.45214593997371066 4.6832684080966303E-2 -0.5216005846606917 2.7626914755113652 -0.65454277494399138 -0.45696348548279841 -0.89725402994336312 2.3415541286742005 1.0788243694297179 -1.0234203378378446 0.68047919764079268 -0.46240948322709619 0.12164176832509033 7.500059749682797E-2 -0.35522702151422614 0.41622977409113115 1.5296260514233895 -1.5641119872092539 -0.44503751292696747 0.85276570736624269 -0.78949284736763081 0.16885050512692468 -0.76910033865358818 0.75435427787555742 1.8677731514884517 1.7163552062557308 -0.89200604717323939 7.0162818997188126E-4 -0.11705052182299269 -1.0221963937800616 -1.335479170150385 0.17742479345612971 -0.59489107182084533 -1.0285009708339357 -1.4235858291993628 1.3855303208156702 0.39865623948725459 0.66938823731124941 -0.617464568408022 -0.75908870828018804 -0.37891909072150143 -0.14661219575038098 -0.40347445331756315 1.4707549486233278 0.3690872211605476 0.5273705821085779 -0.52920913821135551 -0.6013766951497086 -1.3305760748700208 -1.1167291413624987 -9.5518245318886308E-2 1.8670860090319312 -0.40551909876710468 -1.3315725707165376 1.8693196231248199 -0.41466468752645325 1.3285938886940216 2.801529165436742 -0.33788815554940399 -1.3599551135311387 2.9582566723252248 -1.2665174706576792 1.3048098344105714 1.219296241160102 -1.3482020737054226 -0.65958719339477856 0.21482078924283465 -1.6758678116247678 -0.65999204929229505 -1.3395250459108095 -0.90319951611437954 1.5481329272226287 -1.2108634171078112 4.1136222559623903E-2 0.32024096920001099 -0.57379524644673729 -0.62740857578280096 0.11772476993017067 4.3708405643127612E-2 -6.6414444111977389E-3 -0.64167814986926475 3.7585387688007295 2.2927758600448498 -1.1737779906947758 1.4778752755272708 -0.36636650665729142 5.520200698016442E-2 -0.83149269419938676 1.1503327603897269 -0.52517826419472602 0.66681317487155978 -0.23120536904241806 -0.59470857043910819 -5.9404444629131525E-2 -1.3703517313615285 -1.179668056143236 -0.57386292729649191 1.343632976537565 -1.1150051777456438 -1.5091104913321947 -1.3175507689315422 2.1211279266413636 -1.0571695699272006 0.69211144720277584 0.35116834782301476 -3.1985269636250369E-2 1.4601463377722537 -1.4519117942603128 -0.47136404328191395 1.5613467015209825 -0.40936148954592722 -1.2945004986541606 -0.96113890527778145 0.90129374086947012 3.1087632450923106 -0.56267669200890547 -0.69619955688469126 -0.86687540726305379 -0.98534803712454577 1.1055056209414991 -0.68725694731624909 0.10208388725612982 0.31263515726594426 0.56302713154329975 -0.31207077043051834 1.0209507852061872E-2 2.3376061438647175 -1.6389579168539254 -1.5022503175241138 0.70288144029902178 0.7185072876183467 -1.0591779429803052 -1.1337570985569647 -0.83275524289806269 -0.71506020122038016 0.62411449680802811 2.7393820653716801 -1.5977576098548845 -0.20247691889582975 -0.14804669920870106 0.38907909053485179 -0.75230081645241675 -0.86822203746306048 0.66695358839479857 -0.35467383248715256 -1.3900519802340745 1.8060948735485218 3.1617118376182671 -5.0566015856357449E-2ppgdp

Residuals

Normal Probability Plot

0.25125628140703515 0.75376884422110546 1.2562814070351758 1.7587939698492461 2.2613065326633164 2.7638190954773867 3.266331658291457 3.7688442211055273 4.2713567839195976 4.7738693467336679 5.2763819095477382 5.7788944723618085 6.2814070351758788 6.7839195979899491 7.2864321608040195 7.7889447236180898 8.2914572864321592 8.7939698492462313 9.2964824120602998 9.7989949748743719 10.30150753768844 10.804020100502512 11.306532663316581 11.809045226130653 12.311557788944722 12.814070351758794 13.316582914572862 13.819095477386934 14.321608040201003 14.824120603015075 15.326633165829143 15.829145728643216 16.331658291457284 16.834170854271353 17.336683417085425 17.839195979899497 18.341708542713565 18.844221105527634 19.346733668341706 19.849246231155778 20.351758793969847 20.854271356783915 21.356783919597987 21.859296482412059 22.361809045226128 22.864321608040196 23.366834170854268 23.86934673366834 24.371859296482409 24.874371859296478 25.37688442211055 25.879396984924622 26.38190954773869 26.884422110552759 27.386934673366831 27.889447236180903 28.391959798994971 28.89447236180904 29.396984924623112 29.899497487437184 30.402010050251253 30.904522613065321 31.407035175879393 31.909547738693465 32.412060301507537 32.914572864321606 33.417085427135675 33.91959798994975 34.422110552763819 34.924623115577887 35.427135678391963 35.929648241206031 36.4321608040201 36.934673366834168 37.437185929648237 37.939698492462313 38.442211055276381 38.94472361809045 39.447236180904525 39.949748743718594 40.452261306532662 40.954773869346731 41.457286432160799 41.959798994974875 42.462311557788944 42.964824120603012 43.467336683417088 43.969849246231156 44.472361809045225 44.974874371859293 45.477386934673362 45.979899497487438 46.482412060301506 46.984924623115575 47.48743718592965 47.989949748743719 48.492462311557787 48.994974874371856 49.497487437185924 50 50.502512562814069 51.005025125628137 51.507537688442213 52.010050251256281 52.51256281407035 53.015075376884418 53.517587939698487 54.020100502512562 54.522613065326631 55.0251256281407 55.527638190954775 56.030150753768844 56.532663316582912 57.035175879396981 57.537688442211049 58.040201005025125 58.542713567839193 59.045226130653262 59.547738693467338 60.050251256281406 60.552763819095475 61.055276381909543 61.557788944723612 62.060301507537687 62.562814070351756 63.065326633165824 63.5678391959799 64.070351758793961 64.572864321608037 65.075376884422113 65.577889447236174 66.08040201005025 66.582914572864311 67.085427135678387 67.587939698492463 68.090452261306524 68.5929648241206 69.095477386934675 69.597989949748737 70.100502512562812 70.603015075376888 71.105527638190949 71.608040201005025 72.110552763819086 72.613065326633162 73.115577889447238 73.618090452261299 74.120603015075375 74.623115577889436 75.125628140703512 75.628140703517587 76.130653266331649 76.633165829145725 77.1356783919598 77.638190954773862 78.140703517587937 78.643216080402013 79.145728643216074 79.64824120603015 80.150753768844211 80.653266331658287 81.155778894472363 81.658291457286424 82.1608040201005 82.663316582914561 83.165829145728637 83.668341708542712 84.170854271356774 84.673366834170849 85.175879396984925 85.678391959798986 86.180904522613062 86.683417085427138 87.185929648241199 87.688442211055275 88.190954773869336 88.693467336683412 89.195979899497488 89.698492462311549 90.201005025125625 90.703517587939686 91.206030150753762 91.708542713567837 92.211055276381899 92.713567839195974 93.21608040201005 93.718592964824111 94.221105527638187 94.723618090452263 95.226130653266324 95.7286432160804 96.231155778894461 96.733668341708537 97.236180904522612 97.738693467336674 98.241206030150749 98.743718592964811 99.246231155778887 99.748743718592962 1.1339999999999999 1.137 1.163 1.284 1.3120000000000001 1.3460000000000001 1.367 1.3720000000000001 1.389 1.397 1.415 1.4179999999999999 1.4279999999999999 1.43 1.45 1.4510000000000001 1.4570000000000001 1.458 1.476 1.4770000000000001 1.4790000000000001 1.4830000000000001 1.4950000000000001 1.5009999999999999 1.5009999999999999 1.504 1.506 1.5249999999999999 1.528 1.528 1.5289999999999999 1.536 1.54 1.546 1.5589999999999999 1.5620000000000001 1.575 1.587 1.59 1.6 1.63 1.6319999999999999 1.6679999999999999 1.671 1.6830000000000001 1.6910000000000001 1.702 1.7070000000000001 1.7350000000000001 1.75 1.7569999999999999 1.76 1.764 1.794 1.8 1.8120000000000001 1.8320000000000001 1.835 1.867 1.875 1.877 1.885 1.9 1.907 1.909 1.925 1.9390000000000001 1.948 1.9490000000000001 1.984 1.9870000000000001 1.988 1.9950000000000001 2 2 2.0219999999999998 2.0329999999999999 2.0430000000000001 2.0550000000000002 2.077 2.0910000000000002 2.097 2.0979999999999999 2.1349999999999998 2.1419999999999999 2.1459999999999999 2.1480000000000001 2.157 2.1709999999999998 2.1709999999999998 2.1720000000000002 2.1829999999999998 2.19 2.2040000000000002 2.2170000000000001 2.2269999999999999 2.2349999999999999 2.2509999999999999 2.258 2.262 2.2639999999999998 2.266 2.2789999999999999 2.2930000000000001 2.3159999999999998 2.34 2.383 2.391 2.3929999999999998 2.4089999999999998 2.41 2.41 2.4220000000000002 2.4300000000000002 2.4460000000000002 2.4809999999999999 2.4900000000000002 2.5 2.5308062840941101 2.5379999999999998 2.5430000000000001 2.5720000000000001 2.5870000000000002 2.6019999999999999 2.617 2.621 2.6360000000000001 2.6389999999999998 2.6789999999999998 2.7719999999999998 2.8580000000000001 2.8889999999999998 2.9089999999999998 2.996 3 3.05 3.0510000000000002 3.0550000000000002 3.109 3.1589999999999998 3.1619999999999999 3.1739999999999999 3.1949999999999998 3.2010000000000001 3.2290000000000001 3.3 3.3069999999999999 3.488 3.5 3.589 3.7 3.75 3.7629999999999999 3.7829999999999999 3.7989999999999999 3.84 3.8479999999999999 3.8639999999999999 3.988 4.0410000000000004 4.0510000000000002 4.2240000000000002 4.2249999999999996 4.2430000000000003 4.2699999999999996 4.2869999999999999 4.3609999999999998 4.3844662585282403 4.423 4.4420000000000002 4.4930000000000003 4.5350000000000001 4.6050000000000004 4.6230000000000002 4.6890000000000001 4.7130000000000001 4.7279999999999998 4.742 4.8769999999999998 4.9379999999999997 4.9800000000000004 5.032 5.0380000000000003 5.0780000000000003 5.1349999999999998 5.282 5.431 5.4850000000000003 5.4989999999999997 5.7370000000000001 5.75 5.9009999999999998 5.9180000000000001 5.968 5.968 6.117 6.2830000000000004 6.3 6.9249999999999998Sample Percentile

fertility

ln(Fertility)Onln(ppgdo)

ppgdp fertility ln(ppgdp) ln(ferility) SUMMARY OUTPUT
Afghanistan 499 5.968 6.2126060958 1.7864118629
Albania 3677.2 1.525 8.209906872 0.4219944101 Regression Statistics
Algeria 4473 2.142 8.4058146034 0.761739972 Multiple R 0.7252482571
Angola 4321.9 5.135 8.3714503994 1.6360798434 R Square 0.5259850345
Anguilla 13750.1 2 9.5288013758 0.6931471806 Adjusted R Square 0.5235788671
Argentina 9162.1 2.172 9.122830689 0.7756484021 Standard Error 0.3071114681
Armenia 3030.7 1.735 8.0165488949 0.5510074134 Observations 199
Aruba 22851.5 1.671 10.0367720397 0.5134222496
Australia 57118.9 1.949 10.9528903391 0.6673164205 ANOVA
Austria 45158.8 1.346 10.7179404457 0.2971372312 df SS MS F Significance F
Azerbaijan 5637.6 2.148 8.637213722 0.7645371766 Regression 1 20.6176721099 20.6176721099 218.5986927254 9.06235683202192E-34
Bahamas 22461.6 1.877 10.0195624635 0.6296747576 Residual 197 18.5805384058 0.0943174538
Bahrain 18184.1 2.43 9.8083028649 0.8878912574 Total 198 39.1982105157
Bangladesh 670.4 2.157 6.5078745492 0.7687183674
Barbados 14497.3 1.575 9.5817177042 0.4542552723 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0%
Belarus 5702 1.479 8.6485722695 0.3913661837 Intercept 2.6655073378 0.1205657647 22.1083268954 2.93530254356805E-55 2.4277421211 2.9032725545 2.4277421211 2.9032725545
Belgium 43814.8 1.835 10.6877269388 0.6070444815 ln(ppgdp) -0.2071497864 0.0140107282 -14.7850834534 9.06235683202192E-34 -0.2347800498 -0.1795195229 -0.2347800498 -0.1795195229
Belize 4495.8 2.679 8.4108989066 0.9854435906
Benin 741.1 5.078 6.608135569 1.6249174833
Bermuda 92624.7 1.76 11.4363111237 0.5653138091
Bhutan 2047.2 2.258 7.6242282848 0.8144794657 RESIDUAL OUTPUT
Bolivia 1977.9 3.229 7.5897909548 1.1721724918
Bosnia and Herzegovina 4477.7 1.134 8.4068648007 0.1257512053 Row Observation Predicted ln(ferility) Residuals
Botswana 7402.9 2.617 8.9096270943 0.9620286235 2 1 Afghanistan 1.3785673124 0.4078445505 Max 0.9559557215
Brazil 10715.6 1.8 9.2794559026 0.5877866649 3 2 Albania 0.9648268833 -0.5428324732 Min -0.7982758851
Brunei Darussalam 32647.6 1.984 10.3935266251 0.6851150089 4 3 Algeria 0.9242446386 -0.1625046665
Bulgaria 6365.1 1.546 8.7585852218 0.4356709502 5 4 Angola 0.9313631761 0.7047166673
Burkina Faso 519.7 5.75 6.253251722 1.7491998548 6 5 Anguilla 0.6916181686 0.001529012
Burundi 176.6 4.051 5.1738872882 1.3989637642 7 6 Argentina 0.7757149096 -0.0000665075
Cambodia 797.2 2.422 6.6811055883 0.8845936451 8 7 Armenia 1.0048809469 -0.4538735335
Cameroon 1206.6 4.287 7.095561766 1.4555871876 9 8 Aruba 0.5863921541 -0.0729699045
Canada 46360.9 1.691 10.7442117106 0.5253200699 10 9 Australia 0.3966184441 0.2706979764
Cape Verde 3244 2.279 8.0845624152 0.8237367503 11 10 Austria 0.4452882643 -0.1481510331
Cayman Islands 57047.9 1.6 10.9516465448 0.4700036292 12 11 Azerbaijan 0.8763103606 -0.1117731839
Central African Republic 450.8 4.423 6.1110237822 1.4868181989 13 12 Bahamas 0.5899571141 0.0397176435
Chad 727.4 5.737 6.5894765326 1.7469364256 14 13 Bahrain 0.6337194948 0.2541717625
Chile 11887.7 1.832 9.3832595311 0.6054082663 15 14 Bangladesh 1.3174025153 -0.5486841479
China 4354 1.559 8.3788502418 0.4440445901 16 15 Barbados 0.6806565625 -0.2264012902
Colombia 6222.8 2.293 8.7359752452 0.8298610039 17 16 Belarus 0.8739574399 -0.4825912562
Comoros 736.6 4.742 6.602045004 1.5564589876 18 17 Belgium 0.4515469858 0.1554974957
Congo 2665.1 4.442 7.8879968593 1.4911047255 19 18 Belize 0.9231914263 0.0622521643
Cook Islands 12212.1 2.5308062841 9.4101825425 0.9285379413 20 19 Benin 1.2966334665 0.3282840168
Costa Rica 7703.8 1.812 8.9494689926 0.5944312076 21 20 Bermuda 0.2964779318 0.2688358772
Cote dIvoire 1154.1 4.224 7.0510760984 1.4407825464 22 21 Bhutan 1.0861500775 -0.2716706118
Croatia 13819.5 1.501 9.5338359172 0.4061315527 23 22 Bolivia 1.093283763 0.0788887287
Cuba 5704.4 1.451 8.6489930859 0.3722529739 24 23 Bosnia and Herzegovina 0.9240270904 -0.7982758851
Cyprus 28364.3 1.458 10.2528865912 0.3770656336 25 24 Botswana 0.8198799887 0.1421486348
Czech Republic 18838.8 1.501 9.8436738518 0.4061315527 26 25 Brazil 0.7432700301 -0.1554833652
Democratic Republic of the Congo 200.6 5.485 5.3013128755 1.7020170937 27 26 Brunei Darussalam 0.5124905179 0.1726244909
Denmark 55830.2 1.885 10.9300702206 0.6339278209 28 27 Bulgaria 0.8511682803 -0.4154973302
Djibouti 1282.6 3.589 7.1566445467 1.2778736122 29 28 Burkina Faso 1.3701475796 0.3790522752
Dominica 7020.8 3 8.8566324506 1.0986122887 30 29 Burundi 1.5937376915 -0.1947739272
Dominican Republic 5195.4 2.49 8.5555288977 0.9122827105 31 30 Cambodia 1.2815177426 -0.3969240974
East Timor 706.1 5.918 6.5597568705 1.777998554 32 31 Cameroon 1.1956632339 0.2599239537
Ecuador 4072.6 2.393 8.3120368951 0.8725478089 33 32 Canada 0.4398461774 0.0854738925
Egypt 2653.7 2.636 7.8837101716 0.9692626166 34 33 Cape Verde 0.9907919607 -0.1670552105
El Salvador 3425.6 2.171 8.1390319178 0.7751878909 35 34 Cayman Islands 0.3968760958 0.0731275334
Equatorial Guinea 16852.4 4.98 9.7322483589 1.605429891 36 35 Central African Republic 1.3996100669 0.087208132
Eritrea 429.1 4.243 6.061689992 1.4452705662 37 36 Chad 1.3004986819 0.4464377437
Estonia 14135.4 1.702 9.5564375683 0.5318040302 38 37 Chile 0.7217671306 -0.1163588644
Ethiopia 324.6 3.848 5.7825936551 1.3475535328 39 38 China 0.9298303003 -0.4857857102
Fiji 3545.7 2.602 8.1734908807 0.9562803801 40 39 Colombia 0.8558519322 -0.0259909283
Finland 44501.7 1.875 10.7032826697 0.6286086594 41 40 Comoros 1.2978951257 0.2585638619
France 39545.9 1.987 10.5852173016 0.6866259636 42 41 Congo 1.0315104736 0.4595942518
French Polynesia 24669 2.033 10.1133026736 0.7095125346 43 42 Cook Islands 0.7161900346 0.2123479068
Gabon 12468.8 3.195 9.4309848031 1.1615870878 44 43 Costa Rica 0.811626748 -0.2171955404
Gambia 579.1 4.689 6.3614751742 1.5452193401 45 44 Cote dIvoire 1.2048784305 0.235904116
Georgia 2680.3 1.528 7.8936840075 0.4239596907 46 45 Croatia 0.6905752644 -0.2844437118
Germany 39857.1 1.457 10.5930558365 0.3763795272 47 46 Cuba 0.8738702679 -0.501617294
Ghana 1333.2 3.988 7.1953373464 1.3832898521 48 47 Cyprus 0.5416240709 -0.1645584373
Greece 26503.8 1.54 10.1850433979 0.4317824164 49 48 Czech Republic 0.6263924024 -0.2202608498
Greenland 35292.7 2.217 10.4714314227 0.7961549306 50 49 Democratic Republic of the Congo 1.5673415083 0.1346755855
Grenada 7429 2.171 8.9131465392 0.7751878909 51 50 Denmark 0.4013456268 0.2325821941
Guatemala 2882.3 3.84 7.9663438655 1.3454723666 52 51 Djibouti 1.1830099489 0.0948636632
Guinea 427.5 5.032 6.0579542884 1.6158175194 53 52 Dominica 0.8308578178 0.2677544708
Guinea-Bissau 539.4 4.877 6.2904574107 1.5845302767 54 53 Dominican Republic 0.8932313545 0.019051356
Guyana 2996 2.19 8.0050333446 0.7839015438 55 54 East Timor 1.3066551035 0.4713434504
Haiti 612.7 3.159 6.4178754197 1.1502555218 56 55 Ecuador 0.9436706708 -0.0711228619
Honduras 2026.2 2.996 7.6139173966 1.0972780657 57 56 Egypt 1.0323984601 -0.0631358434
Hong Kong 31823.7 1.137 10.3679665742 0.1283932148 58 57 El Salvador 0.9795086149 -0.204320724
Hungary 12884 1.43 9.4637415105 0.3576744443 59 58 Equatorial Guinea 0.6494741695 0.9559557215
Iceland 39278 2.098 10.5784198447 0.74098451 60 59 Eritrea 1.409829551 0.0354410152
India 1406.4 2.538 7.2487885269 0.9313763693 61 60 Estonia 0.6858933372 -0.1540893071
Indonesia 2949.3 2.055 7.989323133 0.7202758479 62 61 Ethiopia 1.4676442976 -0.1200907648
Iran 5227.1 1.587 8.56161191 0.4618454415 63 62 Fiji 0.9723704481 -0.016090068
Iraq 888.5 4.535 6.7895346476 1.5118250836 64 63 Finland 0.4483246195 0.1802840399
Ireland 46220.3 2.097 10.7411743745 0.7405077519 65 64 France 0.4727818353 0.2138441283
Israel 29311.6 2.909 10.2857386211 1.0678093795 66 65 French Polynesia 0.5705388496 0.138973685
Italy 33877.1 1.476 10.4304945489 0.3893357262 67 66 Gabon 0.7118808507 0.4497062371
Jamaica 4899 2.262 8.4967863816 0.8162493777 68 67 Gambia 1.3477291146 0.1974902255
Japan 43140.9 1.418 10.672226782 0.3492474281 69 68 Georgia 1.0303323821 -0.6063726914
Jordan 4445.3 2.889 8.3996026372 1.0609104215 70 69 Germany 0.4711580844 -0.0947785572
Kazakhstan 9166.7 2.481 9.1233326313 0.9086617047 71 70 Ghana 1.1749947437 0.2082951084
Kenya 801.8 4.623 6.6868592002 1.531043845 72 71 Greece 0.5556777739 -0.1238953575
Kiribati 1468.2 3.5 7.2917924397 1.2527629685 73 72 Greenland 0.4963525558 0.2998023749
Kuwait 45430.4 2.251 10.7239367635 0.8113745619 74 73 Grenada 0.8191509365 -0.0439630456
Kyrgyzstan 865.4 2.621 6.7631918278 0.9635559243 75 74 Guatemala 1.015280908 0.3301914586
Laos 1047.6 2.543 6.9542571126 0.9333444864 76 75 Guinea 1.4106034012 0.2052141182
Latvia 10663 1.506 9.274535084 0.4094571294 77 76 Guinea-Bissau 1.3624404291 0.2220898476
Lebanon 9283.7 1.764 9.1360154532 0.5675839576 78 77 Guyana 1.0072663907 -0.2233648469
Lesotho 980.7 3.051 6.8882666024 1.1154694057 79 78 Haiti 1.3360458158 -0.1857902939
Liberia 218.6 5.038 5.3872435757 1.6170091779 80 79 Honduras 1.0882859758 0.0089920899
Libya 11320.8 2.41 9.3343970206 0.8796267475 81 80 Hong Kong 0.517785277 -0.3893920623
Lithuania 10975.5 1.495 9.303420795 0.4021262068 82 81 Hungary 0.7050953058 -0.3474208615
Luxembourg 105095.4 1.683 11.5626237881 0.5205779152 83 82 Iceland 0.474189927 0.266794583
Macao 49990.2 1.163 10.8195822652 0.1510028735 84 83 India 1.1639223431 -0.2325459738
Madagascar 421.9 4.493 6.0447683191 1.5025206301 85 84 Indonesia 1.0105207577 -0.2902449097
Malawi 357.4 5.968 5.8788556027 1.7864118629 86 85 Iran 0.8919712598 -0.4301258183
Malaysia 8372.8 2.572 9.0327436356 0.9446838064 87 86 Iraq 1.2590566861 0.2527683975
Maldives 4684.5 1.668 8.4520144654 0.5116253039 88 87 Ireland 0.4404753609 0.300032391
Mali 598.8 6.117 6.3949276525 1.8110717803 89 88 Israel 0.5348187799 0.5329905996
Malta 19599.2 1.284 9.8832440281 0.2499802053 90 89 Italy 0.5048326204 -0.1154968942
Marshall Islands 3069.4 4.3844662585 8.0292373817 1.4780678986 91 90 Jamaica 0.9053998541 -0.0891504765
Mauritania 1131.1 4.361 7.0309458895 1.4727013889 92 91 Japan 0.45475784 -0.1055104119
Mauritius 7488.3 1.59 8.9210970815 0.4637340162 93 92 Jordan 0.925531446 0.1353789754
Mexico 9100.7 2.227 9.1161066126 0.8006553883 94 93 Kazakhstan 0.7756109324 0.1330507723
Micronesia 2678.2 3.307 7.8929002061 1.196041434 95 94 Kenya 1.2803258831 0.2507179619
Moldova 1625.8 1.45 7.3937552813 0.3715635564 96 95 Kiribati 1.1550140918 0.0977488767
Mongolia 2246.7 2.446 7.7172177519 0.8944540373 97 96 Kuwait 0.4440461284 0.3673284336
Montenegro 6509.8 1.63 8.7810640128 0.4885800148 98 97 Kyrgyzstan 1.2645135956 -0.3009576713
Morocco 2865 2.183 7.9603236291 0.7807000776 99 98 Laos 1.2249344627 -0.2915899762
Mozambique 407.5 4.713 6.0100409327 1.5503246479 100 99 Latvia 0.7442893766 -0.3348322472
Myanmar 876.2 1.939 6.7755943754 0.6621723763 101 100 Lebanon 0.7729836885 -0.205399731
Namibia 5124.7 3.055 8.5418272657 1.1167795926 102 101 Lesotho 1.2386043828 -0.123134977
Nauru 6190.1 3.3 8.7307065206 1.1939224685 103 102 Liberia 1.5495409821 0.0674681959
Nepal 534.7 2.587 6.281705842 0.9504989032 104 103 Libya 0.7318889892 0.1477377583
Neth Antilles 20321.1 1.9 9.9194150341 0.6418538862 105 104 Lithuania 0.7383057078 -0.3361795009
Netherlands 46909.7 1.794 10.7559797561 0.5844477636 106 105 Luxembourg 0.2703122904 0.2502656248
New Caledonia 35319.5 2.091 10.4721904983 0.7376424204 107 106 Macao 0.4242331831 -0.2732303096
New Zealand 32372.1 2.135 10.3850522197 0.7584666467 108 107 Madagascar 1.4133348719 0.0891857581
Nicaragua 1131.9 2.5 7.0316529156 0.9162907319 109 108 Malawi 1.4477036557 0.3387082072
Niger 357.7 6.925 5.8796946463 1.9351380521 110 109 Malaysia 0.7943764235 0.1503073829
Nigeria 1239.8 5.431 7.1227053553 1.6921232791 111 110 Maldives 0.914674347 -0.4030490431
North Korea 504 1.988 6.2225762681 0.6871291082 112 111 Mali 1.3407994408 0.4702723394
Norway 84588.7 1.948 11.3455559669 0.6668032052 113 112 Malta 0.6181954489 -0.3682152436
Oman 20791 2.146 9.9422754797 0.7636056442 114 113 Marshall Islands 1.0022525296 0.475815369
Pakistan 1003.2 3.201 6.9109501699 1.163463261 115 114 Mauritania 1.2090483989 0.2636529899
Palau 10821.8 2 9.2893178972 0.6931471806 116 115 Mauritius 0.8175039833 -0.3537699671
Palestinian Territory 1819.5 4.27 7.5063170171 1.4516138272 117 116 Mexico 0.7771078006 0.0235475877
Panama 7614 2.409 8.9377439369 0.8792117236 118 117 Micronesia 1.0304947464 0.1655466876
Papua New Guinea 1428.4 3.799 7.2643102157 1.3347378742 119 118 Moldova 1.1338925109 -0.7623289545
Paraguay 2771.1 2.858 7.9269996323 1.0501220795 120 119 Mongolia 1.0668873292 -0.172433292
Peru 5410.7 2.41 8.5961337535 0.8796267475 121 120 Montenegro 0.8465118036 -0.3579317888
Philippines 2140.1 3.05 7.6686078359 1.1151415906 122 121 Morocco 1.0165279987 -0.2358279211
Poland 12263.2 1.415 9.4143581869 0.3471295311 123 122 Mozambique 1.4205286426 0.1297960053
Portugal 21437.6 1.312 9.9729016686 0.2715526905 124 123 Myanmar 1.2619444105 -0.5997720343
Puerto Rico 26461 1.757 10.1834272298 0.5636078092 125 124 Namibia 0.8960696446 0.220709948
Qatar 72397.9 2.204 11.1899325724 0.7902738913 126 125 Nauru 0.8569433473 0.3369791211
Republic of Korea 21052.2 1.389 9.9547603467 0.3285840638 127 126 Nepal 1.3642533147 -0.4137544115
Romania 7522.4 1.428 8.925640515 0.3562748639 128 127 Neth Antilles 0.6107026327 0.0311512534
Russian Federation 10351.4 1.529 9.2448770552 0.4246139269 129 128 Netherlands 0.4374084293 0.1470393343
Rwanda 532.3 5.282 6.2772072402 1.6643048139 130 129 New Caledonia 0.4961953134 0.241447107
Saint Lucia 6677.1 1.907 8.8064390405 0.6455313266 131 130 New Zealand 0.5142459892 0.2442206575
Samoa 3343.3 3.763 8.1147136221 1.3252165116 132 131 Nicaragua 1.2089019386 -0.2926112067
Sao Tome and Principe 1283.3 3.488 7.1571901643 1.249328506 133 132 Niger 1.447529848 0.4876082041
Saudi Arabia 15835.9 2.639 9.6700347935 0.9704000575 134 133 Nigeria 1.1900404452 0.5020828339
Senegal 1032.7 4.605 6.9399320107 1.5271426697 135 134 North Korea 1.3765019933 -0.6893728851
Serbia 5123.2 1.562 8.5415345228 0.4459670514 136 135 Norway 0.3152778432 0.351525362
Seychelles 11450.6 2.34 9.3457974094 0.8501509294 137 136 Oman 0.6059670963 0.1576385479
Sierra Leone 351.7 4.728 5.8627785395 1.5535022801 138 137 Pakistan 1.2339054866 -0.0704422256
Singapore 43783.1 1.367 10.6870031772 0.3126185577 139 138 Palau 0.74122712 -0.0480799395
Slovakia 15976 1.372 9.6788428751 0.3162695293 140 139 Palestinian Territory 1.1105753714 0.3410384558
Slovenia 23109.8 1.477 10.048012049 0.3900130035 141 140 Panama 0.8140555908 0.0651561329
Solomon Islands 1193.5 4.041 7.0846454458 1.3964921861 142 141 Papua New Guinea 1.1607070286 0.1740308456
Somalia 114.8 6.283 4.7431914839 1.8378475734 143 142 Paraguay 1.0234310576 0.026691022
South Africa 7254.8 2.383 8.8894185977 0.8683601981 144 143 Peru 0.8848200673 -0.0051933198
Spain 30542.8 1.504 10.3268842576 0.4081282255 145 144 Philippines 1.076956863 0.0381847277
Sri Lanka 2375.3 2.235 7.7728790243 0.8042412281 146 145 Poland 0.7153250507 -0.3681955196
St Vincent and Grenadines 6171.7 1.995 8.7277296057 0.6906440503 147 146 Portugal 0.5996228878 -0.3280701973
Sudan 1824.9 4.225 7.50928047 1.4410192608 148 147 Puerto Rico 0.5560125628 0.0075952464
Suriname 7018 2.266 8.8562335561 0.8180161626 149 148 Qatar 0.3475151961 0.4427586952
Swaziland 3311.2 3.174 8.1050659404 1.1549926221 150 149 Republic of Korea 0.6033808588 -0.274796795
Sweden 48906.2 1.925 10.7976594568 0.6549259677 151 150 Romania 0.8165628121 -0.4602879481
Switzerland 68880.2 1.536 11.1401240427 0.4291816347 152 151 Russian Federation 0.7504330309 -0.325819104
Syria 2931.5 2.772 7.9832695164 1.0195690813 153 152 Rwanda 1.3651851991 0.2991196148
Tajikistan 816 3.162 6.704414355 1.1512047388 154 153 Saint Lucia 0.841255372 -0.1957240454
Tanzania 516 5.499 6.2461067655 1.7045662575 155 154 Samoa 0.9845461447 0.340670367
TFYR Macedonia 4434.5 1.397 8.3971701488 0.3343270803 156 155 Sao Tome and Principe 1.1828969244 0.0664315817
Thailand 4612.8 1.528 8.4365903269 0.4239596907 157 156 Saudi Arabia 0.6623616963 0.3080383612
Togo 524.6 3.864 6.2626360674 1.3517029164 158 157 Senegal 1.2279019045 0.2992407652
Tonga 3543.1 3.783 8.1727573291 1.3305173457 159 158 Serbia 0.8961302863 -0.4501632348
Trinidad and Tobago 15205.1 1.632 9.6293861769 0.4898062565 160 159 Seychelles 0.7295274011 0.1206235282
Tunisia 4222.1 1.909 8.3480879136 0.6465795447 161 160 Sierra Leone 1.4510340159 0.1024682642
Turkey 10095.1 2.022 9.2198054366 0.7040871206 162 161 Singapore 0.4516969129 -0.1390783551
Turkmenistan 4587.5 2.316 8.4310904924 0.8398415597 163 162 Slovakia 0.6605371041 -0.3442675748
Tuvalu 3187.2 3.7 8.0668980674 1.3083328197 164 163 Slovenia 0.5840637886 -0.194050785
Uganda 509 5.901 6.2324480166 1.7751218281 165 164 Solomon Islands 1.1979245473 0.1985676388
Ukraine 3035 1.483 8.0179667035 0.3940670632 166 165 Somalia 1.6829562353 0.1548913381
United Arab Emirates 39624.7 1.707 10.5872079402 0.5347374438 167 166 South Africa 0.8240661745 0.0442940237
United Kingdom 36326.8 1.867 10.5003110399 0.6243328646 168 167 Spain 0.5262954701 -0.1181672446
United States 46545.9 2.077 10.7481942015 0.7309245449 169 168 Sri Lanka 1.0553571086 -0.2511158805
Uruguay 11952.4 2.043 9.388687374 0.7144193158 170 169 St Vincent and Grenadines 0.8575600146 -0.1669159643
Uzbekistan 1427.3 2.264 7.2635398266 0.8171331603 171 170 Sudan 1.1099614928 0.331057768
Vanuatu 2963.5 3.75 7.9941262812 1.32175584 172 171 Suriname 0.8309404487 -0.0129242861
Venezuela 13502.7 2.391 9.5106449444 0.8717116885 173 172 Swaziland 0.9865446599 0.1684479622
Viet Nam 1182.7 1.75 7.0755552393 0.5596157879 174 173 Sweden 0.4287744882 0.2261514795
Yemen 1437.2 4.938 7.2704520552 1.5969603909 175 174 Switzerland 0.3578330224 0.0713486123
Zambia 1237.8 6.3 7.1210908893 1.8405496334 176 175 Syria 1.0117747631 0.0077943183
Zimbabwe 573.1 3.109 6.3510602216 1.1343011311 177 176 Tajikistan 1.2766893365 -0.1254845978
178 177 Tanzania 1.3716276558 0.3329386017
179 178 TFYR Macedonia 0.9260353355 -0.5917082552
180 179 Thailand 0.917869454 -0.4939097633
181 180 Togo 1.3682036144 -0.0165006981
182 181 Tonga 0.9725224031 0.3579949425
183 182 Trinidad and Tobago 0.6707820485 -0.180975792
184 183 Tunisia 0.93620271 -0.2896231653
185 184 Turkey 0.7556266114 -0.0515394908
186 185 Turkmenistan 0.9190087436 -0.0791671839
187 186 Tuvalu 0.9944511266 0.313881693
188 187 Uganda 1.3744570627 0.4006647654
189 188 Ukraine 1.0045872482 -0.610520185
190 189 United Arab Emirates 0.4723694749 0.0623679689
191 190 United Kingdom 0.4903701492 0.1339627153
192 191 United States 0.4390212053 0.2919033396
193 192 Uruguay 0.7206427541 -0.0062234383
194 193 Uzbekistan 1.1608666145 -0.3437334542
195 194 Vanuatu 1.0095257866 0.3122300534
196 195 Venezuela 0.6953792695 0.176332419
197 196 Viet Nam 1.1998075817 -0.6401917937
198 197 Yemen 1.1594347479 0.4375256431
199 198 Zambia 1.1903748815 0.6501747519
200 199 Zimbabwe 1.3498865698 -0.2155854387

MLR_Output

XLMiner : Multiple Linear Regression Date: 21-Sep-2016 03:55:09
Output Navigator Elapsed Times in Milliseconds
Inputs Predictors Regress. Model ANOVA Train. Score – Summary Data read time MLR Time Report Time Total
Residuals-Fitted Values Training Lift Chart Train. Score – Detailed Rep. 6 31 38 75
Inputs
Data
Workbook UN11.xlsx
Worksheet Sheet1
Data Range $A$1:$B$200
# Records 199
Variables
# Input Variables 1
Input variables ln(ppgdp)
Output variable ln(ferility)
Parameters/Options
Force constant term to zero No
Show fitted values on training data Yes
Show ANOVA table Yes
Show standardized residuals Yes
Show un-standardized residuals No
Show variance covariance matrix No
Perform Variable Selection No
Show studentized residuals No
Show deleted residuals No
Show Cook’s distance No
Show DF fits No
Show covariance ratios No
Show hat matrix diagonals No
Output Options Chosen
Summary report of scoring on training data
Detailed report of scoring on training data
Lift charts on training data
Model Predictors
Tolerance for Entering the Model 0
Included Excluded
Predictor Criteria Predictor Criteria
Intercept 2.5472526876
ln(ppgdp) 121.3919348529
Regression Model
Input Variables Coefficient Std. Error t-Statistic P-Value CI Lower CI Upper RSS Reduction Residual DF 197
Intercept 2.6655073378 0.1205657647 22.1083268954 2.93530254356826E-55 2.4277421211 2.9032725545 165.6020594861 0.5259850345
ln(ppgdp) -0.2071497864 0.0140107282 -14.7850834534 9.06235683202295E-34 -0.2347800498 -0.1795195229 20.6176721099 Adjusted R² 0.5235788671
Std. Error Estimate 0.3071114681
RSS 18.5805384058
ANOVA
Source DF SS MS F-Statistic P-Value
Regression 1 20.6177 20.6177 218.5987 0
Error 197 18.5805 0.0943
Total 198 39.1982 20.712
Training Data Scoring – Summary Report
Total sum of squared errors RMS Error Average Error
18.5805384058 0.3055642972 4.43531308832663E-16

lifeExpFOnGroup

group other africa lifeExpF
other 1 0 49.49 SUMMARY OUTPUT
other 1 0 80.4
africa 0 1 75 Regression Statistics
africa 0 1 53.17 Multiple R 0.7868134043
other 1 0 81.1 R Square 0.6190753331
other 1 0 79.89 Adjusted R Square 0.6151883467
other 1 0 77.33 Standard Error 6.2801061827
other 1 0 77.75 Observations 199
oecd 0 0 84.27
oecd 0 0 83.55 ANOVA
other 1 0 73.66 df SS MS F Significance F
other 1 0 78.85 Regression 2 12563.0314933582 6281.5157466791 159.2687161617 8.36048455455694E-42
other 1 0 76.06 Residual 196 7730.187798459 39.4397336656
other 1 0 70.23 Total 198 20293.2192918173
other 1 0 80.26
other 1 0 76.37 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0%
oecd 0 0 82.81 Intercept 82.4464516129 1.1279403677 73.0946900864 3.54078776531392E-144 80.2219939182 84.6709093076 80.2219939182 84.6709093076
other 1 0 77.81 other -7.1197084195 1.2709066366 -5.6020703761 0.000000071 -9.6261157864 -4.6133010527 -9.6261157864 -4.6133010527
africa 0 1 58.66 africa -22.674187462 1.4199983772 -15.9677558973 2.58294591624273E-37 -25.4746247964 -19.8737501276 -25.4746247964 -19.8737501276
other 1 0 82.3
other 1 0 69.84
other 1 0 69.4
other 1 0 78.4
africa 0 1 51.34
other 1 0 77.41
other 1 0 80.64
other 1 0 77.12
africa 0 1 57.02
africa 0 1 52.58
other 1 0 65.1
africa 0 1 53.56
oecd 0 0 83.49
africa 0 1 77.7
other 1 0 83.8
africa 0 1 51.3
africa 0 1 51.61
oecd 0 0 82.35
other 1 0 75.61
other 1 0 77.69
africa 0 1 63.18
africa 0 1 59.33
other 1 0 76.2454672362
other 1 0 81.99
africa 0 1 57.71
other 1 0 80.37
other 1 0 81.33
other 1 0 82.14
oecd 0 0 81
africa 0 1 50.56
oecd 0 0 81.37
africa 0 1 60.04
other 1 0 78.2
other 1 0 76.57
other 1 0 64.2
other 1 0 78.91
africa 0 1 75.52
other 1 0 77.09
africa 0 1 52.91
africa 0 1 64.41
oecd 0 0 79.95
africa 0 1 61.59
other 1 0 72.27
oecd 0 0 83.28
oecd 0 0 84.9
other 1 0 78.07
africa 0 1 64.32
africa 0 1 60.3
other 1 0 77.31
oecd 0 0 82.99
africa 0 1 65.8
oecd 0 0 82.58
other 1 0 71.6
other 1 0 77.72
other 1 0 75.1
africa 0 1 56.39
africa 0 1 50.4
other 1 0 73.45
other 1 0 63.87
other 1 0 75.92
other 1 0 86.35
oecd 0 0 78.47
other 1 0 83.77
other 1 0 67.62
other 1 0 71.8
other 1 0 75.28
other 1 0 72.6
oecd 0 0 83.17
oecd 0 0 84.19
oecd 0 0 84.62
other 1 0 75.98
oecd 0 0 87.12
other 1 0 75.17
other 1 0 72.84
africa 0 1 59.16
other 1 0 63.1
other 1 0 75.89
other 1 0 72.36
other 1 0 69.42
other 1 0 78.51
other 1 0 75.07
africa 0 1 48.11
africa 0 1 58.59
africa 0 1 77.86
other 1 0 78.28
oecd 0 0 82.67
other 1 0 83.8
africa 0 1 68.61
africa 0 1 55.17
other 1 0 76.86
other 1 0 78.7
africa 0 1 53.14
other 1 0 82.29
other 1 0 70.6
africa 0 1 60.95
africa 0 1 76.89
oecd 0 0 79.64
other 1 0 70.17
other 1 0 73.48
other 1 0 72.83
other 1 0 77.37
africa 0 1 74.86
africa 0 1 51.81
other 1 0 67.87
africa 0 1 63.04
other 1 0 57.1
other 1 0 70.05
other 1 0 79.86
oecd 0 0 82.79
other 1 0 80.49
oecd 0 0 82.77
other 1 0 77.45
africa 0 1 55.77
africa 0 1 53.38
other 1 0 72.12
oecd 0 0 83.47
other 1 0 76.44
other 1 0 66.88
other 1 0 72.1
other 1 0 74.81
other 1 0 79.07
other 1 0 65.52
other 1 0 74.91
other 1 0 76.9
other 1 0 72.57
oecd 0 0 80.56
oecd 0 0 82.76
other 1 0 83.2
other 1 0 78.24
other 1 0 83.95
other 1 0 77.95
other 1 0 75.01
africa 0 1 57.13
other 1 0 77.54
other 1 0 76.02
africa 0 1 66.48
other 1 0 75.57
africa 0 1 60.92
other 1 0 77.05
africa 0 1 78
africa 0 1 48.87
other 1 0 83.71
oecd 0 0 79.53
oecd 0 0 82.84
other 1 0 70
africa 0 1 53.38
africa 0 1 54.09
other 1 0 84.76
other 1 0 78.4
other 1 0 74.73
africa 0 1 63.82
other 1 0 74.18
africa 0 1 48.54
oecd 0 0 83.65
oecd 0 0 84.71
other 1 0 77.72
other 1 0 71.23
africa 0 1 60.31
other 1 0 77.14
other 1 0 77.76
africa 0 1 59.4
other 1 0 75.38
other 1 0 73.82
africa 0 1 77.05
oecd 0 0 76.61
other 1 0 69.4
other 1 0 65.1
africa 0 1 55.44
other 1 0 74.58
other 1 0 78.02
oecd 0 0 82.42
oecd 0 0 81.31
other 1 0 80.66
other 1 0 71.9
other 1 0 73.58
other 1 0 77.73
other 1 0 77.44
other 1 0 67.66
africa 0 1 50.04
africa 0 1 52.72

lifeExpOnGroup&ln(ppgdp)

group other africa ln( ppgdp ) lifeExpF
other 1 0 6.2126060958 49.49 SUMMARY OUTPUT
other 1 0 8.209906872 80.4
africa 0 1 8.4058146034 75 Regression Statistics
africa 0 1 8.3714503994 53.17 Multiple R 0.8655396724
other 1 0 9.5288013758 81.1 R Square 0.7491589244
other 1 0 9.122830689 79.89 Adjusted R Square 0.745299831
other 1 0 8.0165488949 77.33 Standard Error 5.1092540244
other 1 0 10.0367720397 77.75 Observations 199
oecd 0 0 10.9528903391 84.27
oecd 0 0 10.7179404457 83.55 ANOVA
other 1 0 8.637213722 73.66 df SS MS F Significance F
other 1 0 10.0195624635 78.85 Regression 3 15202.846338057 5067.615446019 194.1282143666 2.67925530778766E-58
other 1 0 9.8083028649 76.06 Residual 195 5090.3729537603 26.104476686
other 1 0 6.5078745492 70.23 Total 198 20293.2192918173
other 1 0 9.5817177042 80.26
other 1 0 8.6485722695 76.37 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0%
oecd 0 0 10.6877269388 82.81 Intercept 49.5292409403 3.3995538651 14.5693355379 5.14239177668032E-33 42.824627035 56.2338548457 42.824627035 56.2338548457
other 1 0 8.4108989066 77.81 other -1.5346826968 1.1736824055 -1.3075791966 0.192555616 -3.8494238919 0.7800584983 -3.8494238919 0.7800584983
africa 0 1 6.608135569 58.66 africa -12.1703652569 1.5574485782 -7.8142966819 0 -15.2419716525 -9.0987588613 -15.2419716525 -9.0987588613
other 1 0 11.4363111237 82.3 ln(ppgdp) 3.1773199909 0.315959718 10.0560919945 1.97277857411405E-19 2.554182955 3.8004570267 2.554182955 3.8004570267
other 1 0 7.6242282848 69.84
other 1 0 7.5897909548 69.4
other 1 0 8.4068648007 78.4
africa 0 1 8.9096270943 51.34
other 1 0 9.2794559026 77.41
other 1 0 10.3935266251 80.64
other 1 0 8.7585852218 77.12
africa 0 1 6.253251722 57.02
africa 0 1 5.1738872882 52.58
other 1 0 6.6811055883 65.1
africa 0 1 7.095561766 53.56
oecd 0 0 10.7442117106 83.49
africa 0 1 8.0845624152 77.7
other 1 0 10.9516465448 83.8
africa 0 1 6.1110237822 51.3
africa 0 1 6.5894765326 51.61
oecd 0 0 9.3832595311 82.35
other 1 0 8.3788502418 75.61
other 1 0 8.7359752452 77.69
africa 0 1 6.602045004 63.18
africa 0 1 7.8879968593 59.33
other 1 0 9.4101825425 76.2454672362
other 1 0 8.9494689926 81.99
africa 0 1 7.0510760984 57.71
other 1 0 9.5338359172 80.37
other 1 0 8.6489930859 81.33
other 1 0 10.2528865912 82.14
oecd 0 0 9.8436738518 81
africa 0 1 5.3013128755 50.56
oecd 0 0 10.9300702206 81.37
africa 0 1 7.1566445467 60.04
other 1 0 8.8566324506 78.2
other 1 0 8.5555288977 76.57
other 1 0 6.5597568705 64.2
other 1 0 8.3120368951 78.91
africa 0 1 7.8837101716 75.52
other 1 0 8.1390319178 77.09
africa 0 1 9.7322483589 52.91
africa 0 1 6.061689992 64.41
oecd 0 0 9.5564375683 79.95
africa 0 1 5.7825936551 61.59
other 1 0 8.1734908807 72.27
oecd 0 0 10.7032826697 83.28
oecd 0 0 10.5852173016 84.9
other 1 0 10.1133026736 78.07
africa 0 1 9.4309848031 64.32
africa 0 1 6.3614751742 60.3
other 1 0 7.8936840075 77.31
oecd 0 0 10.5930558365 82.99
africa 0 1 7.1953373464 65.8
oecd 0 0 10.1850433979 82.58
other 1 0 10.4714314227 71.6
other 1 0 8.9131465392 77.72
other 1 0 7.9663438655 75.1
africa 0 1 6.0579542884 56.39
africa 0 1 6.2904574107 50.4
other 1 0 8.0050333446 73.45
other 1 0 6.4178754197 63.87
other 1 0 7.6139173966 75.92
other 1 0 10.3679665742 86.35
oecd 0 0 9.4637415105 78.47
other 1 0 10.5784198447 83.77
other 1 0 7.2487885269 67.62
other 1 0 7.989323133 71.8
other 1 0 8.56161191 75.28
other 1 0 6.7895346476 72.6
oecd 0 0 10.7411743745 83.17
oecd 0 0 10.2857386211 84.19
oecd 0 0 10.4304945489 84.62
other 1 0 8.4967863816 75.98
oecd 0 0 10.672226782 87.12
other 1 0 8.3996026372 75.17
other 1 0 9.1233326313 72.84
africa 0 1 6.6868592002 59.16
other 1 0 7.2917924397 63.1
other 1 0 10.7239367635 75.89
other 1 0 6.7631918278 72.36
other 1 0 6.9542571126 69.42
other 1 0 9.274535084 78.51
other 1 0 9.1360154532 75.07
africa 0 1 6.8882666024 48.11
africa 0 1 5.3872435757 58.59
africa 0 1 9.3343970206 77.86
other 1 0 9.303420795 78.28
oecd 0 0 11.5626237881 82.67
other 1 0 10.8195822652 83.8
africa 0 1 6.0447683191 68.61
africa 0 1 5.8788556027 55.17
other 1 0 9.0327436356 76.86
other 1 0 8.4520144654 78.7
africa 0 1 6.3949276525 53.14
other 1 0 9.8832440281 82.29
other 1 0 8.0292373817 70.6
africa 0 1 7.0309458895 60.95
africa 0 1 8.9210970815 76.89
oecd 0 0 9.1161066126 79.64
other 1 0 7.8929002061 70.17
other 1 0 7.3937552813 73.48
other 1 0 7.7172177519 72.83
other 1 0 8.7810640128 77.37
africa 0 1 7.9603236291 74.86
africa 0 1 6.0100409327 51.81
other 1 0 6.7755943754 67.87
africa 0 1 8.5418272657 63.04
other 1 0 8.7307065206 57.1
other 1 0 6.281705842 70.05
other 1 0 9.9194150341 79.86
oecd 0 0 10.7559797561 82.79
other 1 0 10.4721904983 80.49
oecd 0 0 10.3850522197 82.77
other 1 0 7.0316529156 77.45
africa 0 1 5.8796946463 55.77
africa 0 1 7.1227053553 53.38
other 1 0 6.2225762681 72.12
oecd 0 0 11.3455559669 83.47
other 1 0 9.9422754797 76.44
other 1 0 6.9109501699 66.88
other 1 0 9.2893178972 72.1
other 1 0 7.5063170171 74.81
other 1 0 8.9377439369 79.07
other 1 0 7.2643102157 65.52
other 1 0 7.9269996323 74.91
other 1 0 8.5961337535 76.9
other 1 0 7.6686078359 72.57
oecd 0 0 9.4143581869 80.56
oecd 0 0 9.9729016686 82.76
other 1 0 10.1834272298 83.2
other 1 0 11.1899325724 78.24
other 1 0 9.9547603467 83.95
other 1 0 8.925640515 77.95
other 1 0 9.2448770552 75.01
africa 0 1 6.2772072402 57.13
other 1 0 8.8064390405 77.54
other 1 0 8.1147136221 76.02
africa 0 1 7.1571901643 66.48
other 1 0 9.6700347935 75.57
africa 0 1 6.9399320107 60.92
other 1 0 8.5415345228 77.05
africa 0 1 9.3457974094 78
africa 0 1 5.8627785395 48.87
other 1 0 10.6870031772 83.71
oecd 0 0 9.6788428751 79.53
oecd 0 0 10.048012049 82.84
other 1 0 7.0846454458 70
africa 0 1 4.7431914839 53.38
africa 0 1 8.8894185977 54.09
other 1 0 10.3268842576 84.76
other 1 0 7.7728790243 78.4
other 1 0 8.7277296057 74.73
africa 0 1 7.50928047 63.82
other 1 0 8.8562335561 74.18
africa 0 1 8.1050659404 48.54
oecd 0 0 10.7976594568 83.65
oecd 0 0 11.1401240427 84.71
other 1 0 7.9832695164 77.72
other 1 0 6.704414355 71.23
africa 0 1 6.2461067655 60.31
other 1 0 8.3971701488 77.14
other 1 0 8.4365903269 77.76
africa 0 1 6.2626360674 59.4
other 1 0 8.1727573291 75.38
other 1 0 9.6293861769 73.82
africa 0 1 8.3480879136 77.05
oecd 0 0 9.2198054366 76.61
other 1 0 8.4310904924 69.4
other 1 0 8.0668980674 65.1
africa 0 1 6.2324480166 55.44
other 1 0 8.0179667035 74.58
other 1 0 10.5872079402 78.02
oecd 0 0 10.5003110399 82.42
oecd 0 0 10.7481942015 81.31
other 1 0 9.388687374 80.66
other 1 0 7.2635398266 71.9
other 1 0 7.9941262812 73.58
other 1 0 9.5106449444 77.73
other 1 0 7.0755552393 77.44
other 1 0 7.2704520552 67.66
africa 0 1 7.1210908893 50.04
africa 0 1 6.3510602216 52.72

Regression Statistics

Multiple R0.72108

R Square0.519956

Adjusted R Square0.51752

Standard Error0.93049

Observations199

ANOVA

dfSSMSFSignificance F

Regression1184.7462184.7462213.37933.16E-33

Residual197170.56480.865811

Total198355.3109

CoefficientsStandard Errort StatP-valueLower 95%Upper 95%

Intercept8.0096690.36529121.926799.34E-557.2892858.730053

ln(ppgdp)-0.620090.04245-14.60753.16E-33-0.7038-0.53637

Regression Statistics

Multiple R0.464675

R Square0.215923

Adjusted R Square0.211943

Standard Error0.394984

Observations199

ANOVA

dfSSMSFSignificance F

Regression18.4637948.46379454.250824.72E-12

Residual19730.734420.156012

Total19839.19821

CoefficientsStandard Errort StatP-valueLower 95%Upper 95%

Intercept1.0583450.03431530.842412.43E-770.9906731.126016

ppgdp-1.1E-051.52E-06-7.365524.72E-12-1.4E-05-8.2E-06

Regression Statistics

Multiple R0.725248

R Square0.525985

Adjusted R Square0.523579

Standard Error0.307111

Observations199

ANOVA

dfSSMSFSignificance F

Regression120.6176720.61767218.59879.06E-34

Residual19718.580540.094317

Total19839.19821

CoefficientsStandard Errort StatP-valueLower 95%

Intercept2.6655070.12056622.108332.94E-552.427742

ln(ppgdp)-0.207150.014011-14.78519.06E-34-0.23478