EXAMPLE 10.3 Retail Sales and Floor Space

It is customary in retail operations to assess the performance of stores partly in terms of their annual sales relative to their floor area (square feet). We might expect sales to increase linearly as stores get larger, with, of course, individual variation among stores of the same size. The regression model for a population of stores says that

The slope is, as usual, a rate of change: it is the expected increase in annual sales associated with each additional square foot of floor space. The intercept is needed to describe the line but has no statistical importance because no stores have area close to zero. Floor space does not completely determine sales. The term in the model accounts for differences among individual stores with the same floor space. A store’s location, for example, could be important but is not included in the FIT part of the model. In Chapter 11, we consider moving variables like this out of the RESIDUAL part of the model by allowing more than one explanatory variable in the FIT part.