There is an urban data mining legend that Walmart was planning to have nappies next to beer. It was theorized that the reason for this was that fathers were stopping off at Wal-Mart to buy nappies for their babies, and since they could no longer go down to the pub as often, would buy beer as well. Let us say sales of beer (in hundreds of casks) and sales of nappies (in hundreds of packets) were collected on weekends and following is the output from a simple linear regression analysis (fictitious).

a. Interpret the coefficient of Diaper Sales. b. What is the expected sales of beer if they sell 100,000 nappies?

Regression Statistics Multiple R R Square Adjusted R Sq. 0.92 0.85 0.85 Standard Error Observations 0.86 23.00 ANOVA df F 122.19 Significance F 0.00 Regression Residual Total MS 89.79 0.73 1.00 21.00 22.00 SS 89.79 15.43 105.23 Intercept Diaper Sales Coefficients 5.22 0.11 Standard Error 0.30 0.01 t Stat 17.64 11.05 P-value 0.003 0.002 Lower 95% 4.61 0.09 Upper 95% 5.84 0.14