Reference no: EM131092712
Refer to Grocery retailer Problem 6.9.
a. Fit regression model (6.5) to the data for three predictor variables. State the estimated regression function. How are bl ,b2 , and b3 interpreted here?
b. Obtain the residuals and prepare a, box plot of the residuals. What information does this plot provide?
c. Plot the residuals against 
, X I, X2 , X3, and X I X2 on separate graphs. Also prepare a normal probability plot. Interpret the plots and summarize your findings.
d. Prepare a time plot of the residuals. Is there any indication.o1:hat the error terms are correlated? Discuss.
e. Divide the 52 cases into two groups, placing the 26 cases with the smallest fitted values 
; into group I and the other 26 cases into group 2. Conduct the Brown-Forsythe test for constancy of the error variance, using α = .01. State the decision rule and conclusion.
Problem 6.9
Grocery retailer. 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 (XI)' 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).
a. Prepare separate stem-and-leaf plots for the number of cases shipped Xit and the indirect cost of the total hours Xi2. Are there any outlying cases present? Are there any gaps in the data?
b. The cases are given in consecutive weeks. Prepare a time plot for each predictor variable. - What do the plots show?
c. Obtain the scatter plot matrix and the correlation matrix. What information do these diagnostic aids provide here?
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