Deciding where to locate a new retail store is an important decision. The manager of a chain of pizza shops plans to use a regression model to help select a location for a new shop. They decide to use annual gross revenue as a measure of success, which is the dependent variable. The manager believes that determinants of success include the following:

The number of people living within 1km of the store (PEOPLE).

Mean income of households within 1km of the store (INCOME)

Number of competitors within 1km of the store (COMPTORS)

The average price of a large pizza (PRICE)

Whether the store has street frontage or not (FRONTAGE)

The manager randomly selects 50 pizza shops and records the values of each of the variables of interest. He proposes the following regression model:

REVENUE = ?o + ?PEOPLE + ?2INCOME + ?3COMPTORS + ?4PRICE + ?5FRONTAGE + ?

a. Estimate this regression model.

b. Test the overall utility of the model.

c. Which independent variables are linearly related to the revenue? Explain.

d. Interpret all the estimated coefficients.

e.What is the coefficient of determination and the coefficient of determination adjusted for degrees of freedom? What do these statistics tell you about the regression equation?

Deciding where to locate a new retail store is an important decision. The manager of a chain of pizza shops plans to use a regression model to help select a location for a new shop. They decide to use annual gross revenue as a measure of success, which is the dependent variable. The manager believe that determinants of success include the following: 0 Number of people living within 1km of the store (PEOPLE) I Mean income of households within 1km of the store (INCOME) - Number of competitors within 1km of the store (COMPTORS) 0 Average price of a large pizza (PRICE) 0 Whether the store has street frontage or not (FRONTAGE) The manager randomly selects 50 pizza shops and records the values of each of the variables of interest. He proposes the following regression model: REVENUE = n + BIPEOPLE + erchan + gcom'ross + 34mm: + sFNTAGE + a a. Estimate this regression model. b. Test the overall utility of the model. c. Which independent variables are linearly related to the revenue? Explain. d. Interpret all the estimated coefficients. e. What g the coefcient of determination and the coefcient of determination adjusted for degrees of freedom? What do these statistics tell you about the regression equation