Question

For Questions 4-11, use the swiss dataset, which is built into R.

Fit a multiple linear regression model with Fertility as the response and the remaining variables as predictors. You should use ?swiss to learn about the background of this dataset.

9. 1 Run Reset Report the value of the F statistic for the significance of regression test. Enter answer here point 10. 1 Run

11 1 Run Reset Consider a model that only uses the predictors Education, Catholic, and Infant.Mortality. Use an F test to com

9. 1 Run Reset Report the value of the F statistic for the significance of regression test. Enter answer here point 10. 1 Run Reset 0.01. What decision do Carry out the significance of regression test using a you make?
11 1 Run Reset Consider a model that only uses the predictors Education, Catholic, and Infant.Mortality. Use an F test to compare this with the model that uses all predictors. Report the p-value of this test. Enter answer here
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Answer #1

The following R code can be used to obtain the required results.

*******************************************************************************************************************

##question 9 : F statistic value

> summary(lm(Fertility~.,data=swiss))$fstatistic[1]
   value 
19.76106

##question 10 : Carry out the significance of the regression test at 0.01 level of significance

> summary(1m(Fertility~. ,data-swiss)) call 1m (formula Fertility ., data = swiss) Residuals Min Median 1Q -5, 2617 30 Max 4.

# as we can see the p - value of the F - Statistic is 5.594*10-10 which is less than 0.01> Thus our decision is that the regression model is significant,

## Question 11 : F-statistic value and p-value for the new model

> summary(1m(Fertility-Education+Catholic+Infant.Mortality , data-swiss)) call: 1mformula Fertility Education Catholic Infant

# as you may notice the f-statistic value is 28.14 and the p-value of the test for regression significance is 3.15*10-10

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Answer #2

res<-cor(swiss)

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