In Exexcises 14.98-14.108, use the technology of your choice to do the following tasks.
a. Decide whether your can reasonably apply the conditional mean and predicted value t-interval procedures to the data. If so, then also do parts (b) - (h).
b. Determine and interpret a point estimate for the conditional mean of the response variable corresponding to the specified value of the predictor variable.
c. Find and interpret a $95\%$ confidence interval for the conditional mean of the response variable corresponding to the specified value of the predictor variable.
d. Determine and interpret the predicted value of the response variable corresponding to the specified value of the predictor variable.
e. Find and interpret a $95\%$prediction interval for the value of the response variable corresponding to the specified value of the predictor variable.
f. Compare and discuss the differences between the confidence interval that you obtained in part (c) and the prediction interval that you obfained in part (e).
14.102 Home Size and Value. The data from Exercise 14.38 for home size (in square feet) and assessed value (in thousands of dollars) for the same homes as in Exercise $14.101$ are on the WeissStats site. Specified value of the predictor variable: $3000$ sq. ft.

To decide whether your can reasonably apply the conditional mean and predicted value $t$-interval procedures to the data.

The data from Exercise $14.38$for home size (in square feet) and assessed value (in thousands of dollars) as follows:

Using Exercise$14.38$, determine if it is reasonable to use the conditional mean and predated value $t$-interval procedures to data.
The residual plot clearly shows that the residuals lie within the horizontal band.
It is obvious from the normal probability plot of residuals that the residuals do not follow the linear pattern.
As a result, for the variables value and home size, assumption $3$ for regression inferences is broken.
Part (a) clearly shows that the regression inference assumptions have been broken.
As a result, there is no way to calculate from part (b) to part (f).

To determine and interpret a point estimate for the conditional mean of the response variable corresponding to the specified value of the predictor variable.

For the variables value and home size, assumption $3$ for regression inferences is broken.
Part (a) clearly shows that the regression inference assumptions have been broken.
As a result, there is no way to calculate from part (b) to part (f).

To find and interpret a $95\%$ confidence interval for the conditional mean of the response variable corresponding to the specified value of the predictor variable.

For the variables value and home size, assumption $3$ for regression inferences is broken.
Part (a) clearly shows that the regression inference assumptions have been broken.
As a result, there is no way to calculate from part (b) to part (f).

To determine and interpret the predicted value of the response variable corresponding to the specified value of the predictor variable.

For the variables value and home size, assumption $3$ for regression inferences is broken.
Part (a) clearly shows that the regression inference assumptions have been broken.
As a result, there is no way to calculate from part (b) to part (f).

To find and interpret a $95\%$ prediction interval for the value of the response variable corresponding to the specified value of the predictor variable.

For the variables value and home size, assumption $3$ for regression inferences is broken.
Part (a) clearly shows that the regression inference assumptions have been broken.
As a result, there is no way to calculate from part (b) to part (f).

To compare and discuss the differences between the confidence interval that obtained in part (c) and the prediction interval that obtained in part (e).

For the variables value and home size, assumption $3$ for regression inferences is broken.
Part (a) clearly shows that the regression inference assumptions have been broken.
As a result, there is no way to calculate from part (b) to part (f).