Regression

Case Study: Locating New Pam and Susan‘s Stores

Professor Demetra Paparounas

Lisa Chan

MGSC 6200- Information Analysis

July 3, 2014

Introduction

The purpose of this study to is to determine a new store location for Pam and Susan Stores. This discount department store chain has 250 stores that are primarily in the South. Expansion is important to their strategic success. A multiple regression model will be used to determine which location has the highest sales potential and projections. It will also be used to help see how strong of a relationship sales has to the other independent variables.

Data

For this model, the wealth of census data that was used to compute this model contained 250 observations, 33 variables and 7 additional dummy variables were created from the main comtype variable, taking values of zero or one depending on level of competitiveness for a particular store. This data set contained economic and demographical data, population type, sales numbers, store size and the competitive types. The amount of sales and selling square feet variables are given in thousands of dollars.

Results and Discussions

In analyzing the data on the 250 Pam and Susan’s stores, we first created a scatter plot of the competitive types in the horizontal axis against sales (in thousands) on the vertical axis. The competitive types were identified as follows:

* Type 1- Densely populated area with relatively little direct competition.

* Type 2 –High income areas with little competition

* Type 3-Locations near major shopping centers

* Type 4-Stores in downtown areas of suburbs

* Type 5-Stores with competition from discounters, but not from department stores

* Type 6-Stores in shopping centers

* Type 7-Store located along the side of the roads

In looking at the above scatter plot, you can see that the comtypes 1, 2 have higher sales in the stores, but the middle categories consisting of comtypes 3-6 are in similar ranges or values of sales. Category...