You will need the data file "sales" for completing this exercise. The file has the following columns that are relevant to this exercise:

see here for data file:

https://docs.google.com/spreadsheets/d/1vF_LEmhpQEREuejJ7qc_CyzkOzWWjJBtL_lAxgmLu9I/edit?usp=sharing

SalesPerSF: Sales per square foot of stores operated by a retail chain,

Income: the median household income in the surrounding community (dollars), Population000: and the size of the community (in thousands).

Market: This is a qualitative variable. There are 3 types of geographic locations: urban, suburban, and rural. Two dummy variables have been set up, UrbanDummy and SuburbanDummy. Rural is selected as the base level.

Disregard the other columns in the file.

(a) Run a regression using SalesPerSF as the dependent variable, and Income, Population000, and the two dummy variables as predictors. Which of the coefficients are significantly different from zero?

(b) Predict the sales per square foot for a store located in a suburban community with median household income $71,000, and population size equal to 500,000 people. Determine a 95% prediction interval and a 95% confidence interval. Explain the difference between the two intervals.

(c) Interpret all four coefficients in the estimated regression equation