Marketing Data Science: Modeling Techniques in Predictive Analytics with R and Python (FT Press Analytics) by Thomas W. Miller

Marketing Data Science: Modeling Techniques in Predictive Analytics with R and Python (FT Press Analytics) by Thomas W. Miller

Author:Thomas W. Miller [Miller, Thomas W.]
Language: eng
Format: azw3
Publisher: Pearson Education
Published: 2015-05-02T04:00:00+00:00


The linear regression of sales on competition, population, and income is summarized in table 13.1. Variance inflation factors computed for this problem show that multicollinearity is not an issue. Diagnostic plots in figure 13.3 indicate no special issues regarding the fitted model.

Table 13.1. Fitted Regression Model for Restaurant Sales

Figure 13.3. Diagnostics from Fitted Regression Model

Applying the fitted model to prospective restaurant sites involves finding the associated explanatory variable values for each site and computing the predicted sales. Table 13.2 shows the results for three prospective store sites. The middle site has the highest predicted sales, so this would be the recommended site for the next new restaurant.



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