(13 points) You want to model the rela:onship between a country\'s life expectan
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(13 points) You want to model the rela:onship between a country's life expectancy at birth and the expanatory (independent) variables of the proportion of the country that s ted and its mil tary expendture as a percentage of the gross domestice product (GDP). The data ava abe are from Latin Amercan countres and a few Carbbean island nations (for a total of 17 observations Output obtained when running the regressi on using all variables in SPSS s gven below. Model Summary. R RSquareAdjusted R Square Std. Error of the Estimate 0.339 2.66325 ANOVA Model Sum of Squares d Mean Square F Sg Regression 72.429 2 36214 5.110.022 Residual99.30114 7.093 Coefficients Std. Error t Sg. Constant) 74.368 1.858 40.02 0.000 Forested -11526 4.417 -2.61 0.021 Mi it Now consider determining if the proportion of the country that is forested is needed in the model when , O military expenditure is already in the model by testing H0 : ß1-0 versus H. : The test statistic for this test is The p-value for this test is Select the appropriate conclusion for this test at a significance level of a0.05 A. We have significant evidence that proportion of the country that is forested is useful in predicting life expectancy, ewen with military expenditure aready in the model. B. We do not have significant evidence that proportion of the country tha: is forested is useful in pred icting life expectancy when miitary expenditure is already in the model. Now consider determining if miliatry expenditure s needed in the model when the proportion of the country that is forested is already in the model by testing Ho 2 versus Ha : B2 0 The test statistic for this test is The p-value for this test is Select the appropriate conclusion for this test at a significance level of 0.05 A We have significant evidence that military expenditure is useful in predicting life expectancy, even with percentage forested already in the model. ?. we do not have significant evdence that military expenditure is useful in pedcting life expectancy when percentage forested is already in the model. Report the coefficient of determination for this model as a decimal:Explanation / Answer
Here are the answers to the question:
For B1,
The test statistic for this test -11.526
The p-value for this test is : .021
A. Forested , with a p-value of less than .05 ( at .021) is statistically significant.
For B2,
The test statistic for this test is : 1.3939
The p-value for this test is : .051
B is correct. Since .051 is more than alpha of .05, we do not have significant evidence that military expenditure is useful is predicting life expectancy when percentage forested is already in the model.
The coefficient of determination for this model as a decimal: 0.422
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