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.

7. 1 Run Reset Create a 95% confidence interval for the average Fertility for a Swiss province in 1888 with: 40% of males involved in agriculture as occupation 28% of draftees receiving highest mark on army examination 10% of draftees obtaining education beyond primary school 42% of the population identifying as Catholic 27% of live births that live less than a year Report the lower bound of this interval. Enter answer here 8. predict Fertility, interval level = 0.95) "prediction", 1 = 2 Run Reset 0.95) : Error in predict(Fertility, interval = "prediction", level object 'Fertility' not found = Create a 95% prediction interval for the Fertility of a Swiss province in 1888 with: 40% of males involved in agriculture as occupation 28% of draftees receiving highest mark on army examination 10% of draftees obtaining education beyond primary school 42% of the population identifying as Catholic 27% of live births that live less than a year Report the lower bound of this interval. Enter answer here

Answer 1

7.

Ran the linear regression model as

model = lm(Fertility ~ . , data = swiss)

Create the dataframe of new observation with the given data.

new.data = data.frame(Agriculture=40, Examination=28, Education=10, Catholic=42, Infant.Mortality=27)

Run the predict.lm function to calculate 95% confidence interval.

predict.lm(model, new.data, interval = "confidence")
fit lwr upr
1 77.55014 69.4446 85.65567

Lower bound of the interval = 69.4446

8.

Run the predict.lm function to calculate 95% prediction interval.

predict.lm(model, new.data, interval = "prediction")
fit lwr upr
1 77.55014 60.96392 94.13635

Lower bound of the interval = 60.96392