# Pamd Sue

1861 words 8 pages
Pam & Sue Regression Analysis

Multiple Regression Project:

Forecasting Sales for Proposed New

Sites of Pam and Susan’s Stores

I. Introduction

Pam and Susan’s is a discount department store that currently has 250 stores, most of which are located throughout the southern United States. As the company has grown, it has become increasingly more important to identify profitable locations. Using census and existing store data, a multiple regression equation will be used to forecast potential sales, and therefore which proposed new site location will be more profitable.

II. Data

The data set has 37 independent variables. This includes 7 categorical variables for competitive type and 30 numerical categories. There
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For example:

1. An adjusted R2 value of 0.733 indicates that the variation in the x-variables explains 73% of the variation in sales

2. A standard error of 2,819 tells you that two-thirds of the predicted sales will be in this range and that 95% (margin of error) of the predicted sales will be accurate within 5,638

3. When all other independent variables are the same, on average a \$130,000 increase in predicted sales is associated with a 1% increase in Spanish speaking population

The other independent variables and coefficients can be interpreted the same way as example 3 above. It should be mentioned that when interpreting the coefficients, differences in the dependent variable are true only when all other x-variables are the same. As with above, the \$130,000 increase in predicted sales with each unit change in the Spanish speaking population is only true when all other x-variables remain the same. If two variables change at once the multiple regression equation will not accurately forecast changes in

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