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About the case: The case deals with the dependency Child Mortality (CM)with respect to other factors like Female Literacy Rate (FLFP), Per CapitaGNP (PNGP) and Total Fertility Rate (TFR). The data has been taken for 64countries.

Objective: The motive of analyzing the data is to find out the dependency ofthe Child Mortality with respect to other given variables. That is, either theother factors are affecting the CM or not, and if they are, then to which extent.Whether it is fully dependent on the given factors or there may be some otherfactors which may be affecting the CM.

Process: In SPSS, the CM is categorized as dependent variable and FLR andPNGP are declared as independent variables.

Equation: CM=263.864-2.39FLR+ u

1. Taking only FLR as Independent Variable:

Regression

Variables Entered/Removedb

Model

Variables

Entered

Variables

RemovedMethod

1 FLRa . Enter

a. All requested variables entered.

b. Dependent Variable: CM

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the

Estimate

1 .818a .670 .664 44.024

Model Summary

ModelChange Statistics

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R Square

Change F Change df1 df2Sig. F Change

1 .670 125.645 1 62 .000

a. Predictors: (Constant), FLR

ANOVAb

Model Sum of Squares df Mean Square FSig.

1 Regression 243515.049 1 243515.049 125.645 .000a

Residual 120162.951 62 1938.112

Total 363678.000 63

a. Predictors: (Constant), FLR

b. Dependent Variable: CM

Coefficientsa

ModelUnstandardized Coefficients

BStd. Error

1 (Constant) 263.864 12.225

FLR -2.390 .213

Coefficientsa

Model

Standardized

Coefficients t Sig.95.0% Confidence Interval for B

Beta Lower BoundUpper Bound

1 (Constant) 21.584 .000 239.426 288.301

FLR -.818 -11.209 .000 -2.817 -1.964

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a. Dependent Variable: CM

Analysis: Since t value of FLR is -11.209, it means that its significancelevel is 99%. Also R square is .670, which means that value of dependentvariable(CM) is ifluenced 67% by the factor FLR.

2. Taking FLR and PGNP both as Independent Variables

Regression

Variables Entered/Removedb

Model

Variables

Entered

Variables

RemovedMethod

1 PNGP, FLRa . Enter

a. All requested variables entered.

b. Dependent Variable: CM

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the

Estimate

1 .841a .708 .698 41.748

Model Summary

Model

Change Statistics

R Square

Change F Change df1 df2Sig. F Change

1 .708 73.833 2 61 .000

a. Predictors: (Constant), PNGP, FLR

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ANOVAb

Model Sum of Squares df Mean Square FSig.

1 Regression 257362.373 2 128681.187 73.833 .000a

Residual 106315.627 61 1742.879

Total 363678.000 63

a. Predictors: (Constant), PNGP, FLR

b. Dependent Variable: CM

Coefficientsa

ModelUnstandardized Coefficients

BStd. Error

1 (Constant) 263.642 11.593

FLR -2.232 .210

PNGP -.006 .002

Coefficientsa

Model

Standardized

Coefficients t Sig.

95.0% Confidence Interval for B

Beta Lower BoundUpper Bound

1 (Constant) 22.741 .000 240.460 286.824

FLR -.764 -10.629 .000 -2.651 -1.812

PNGP -.203 -2.819 .006 -.010 -.002

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a. Dependent Variable: CM

Equation:CM=263.64 2.232FLR -0.006PGNP+ u

Analysis: Since t value of FLR is -10.629 and of PNGP is -2.819, itmeans that its significance level is 99% for FLR and 95% for PNGP. Also Rsquare is .708, which is more than the adjusted R square (.698).It meansthat value of dependent variable(CM) is influenced 70.8% by the factorsFLR and PNGP. This shows that the another variable PNGP is alsopositively dependent on the CM.