Multiple regression on grocery store and brand preference datasets

Grocery Store

A dataset from the textbook Applied Linear Statistical Models by Kutner, Nachtsheim, Neter, & Li

This dataset is based on the following: A large, national grocery retailer tracks productivity and costs of its facilities closely. Data below were obtained from a single distribution center for a one-year period. Each data point for each variable represents one week of activity. The variables included are the number of cases shipped (X1) the indirect costs of the total labor hours as a percentage (X2), a qualitative predictor called holiday that is coded 1 if the week has a holiday and 0 otherwise (X3), and the total labor hours (Y).

Brand Preference

A dataset from the textbook Applied Linear Statistical Models by Kutner, Nachtsheim, Neter, & Li

This dataset is based on the following: In a small-scale experimental study of the relation between degree of brand liking (Y) and moisture content (X1) and sweetness (X2) of the product, the following results were obtained from the experiment based on a completely randomized design (data are coded).

Note:

In addition to using the lm function, the closed form solution of the least squares method is used.