Locating New Pam and Susan’s Stores

1194 WordsNov 15, 20155 Pages
Multiple Regression Project Locating New Pam and Susan’s Stores Introduction Pam and Susan’s department stores are in the process of opening a new business unit. There are two locations that are being considered for the new store and decision is based upon estimates of sales for both of them. My job is to use data gathered from each store as well census data in store’s trading zones to predict sales at both of the sites that are being consider for their newest store. Data We have data out of 250 stores. The data include demographics, economics, sales of the stores, compositions of those sales as well as sales behavior per households. There are 31 variables being consider for each store and those variables range from sales,…show more content…
Seven models were created in order to obtain the model in which all-remaining variables are statistically significant and the final equation to predict sales is as follow: Sales (in $ 1000s)= 16,020.78118 + 149.15175 * %spanishsp – 44.16538 * %dryers – 112.48017 * %freezer – 79.84655 * %sch0-8 + 9,393.82229 * comtype1 + 3,802.26442 * comtype2 – 3,123.24462 * comtype7 Regression Statistics | R | 0.86485 | | | R-square | 0.74797 | | | Adjusted R-square | 0.74068 | | | S | 2,776.51435 | | | N | 250 | | | | | | | | Coefficient | Standard Error | t Stat | p-level | Intercept | 16,020.78118 | 1,157.29255 | 13.84333 | 0. | %spanishsp | 149.15175 | 55.74166 | 2.67577 | 0.00796 | %dryers | -44.16538 | 16.10174 | -2.74289 | 0.00655 | %freezer | -112.48017 | 39.36158 | -2.85761 | 0.00464 | %sch0-8 | -79.84655 | 30.30416 | -2.63484 | 0.00896 | comtype1 | 9,393.82229 | 862.77706 | 10.88789 | 0. | comtype2 | 3,802.26442 | 518.76015 | 7.32952 | 3.4437E-12 | comtype7 | -3,123.24462 | 562.54923 | -5.55195 | 7.41169E-8 | Question 1 After reviewing the regression equation and statistics, there is a high % of Spanish Speaking population, low % of people with dryers and freezers and sales are high in locations with a lower competitive type and with high population. Higher
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