These data describe the sales over time at a franchise outlet of a major U.S. oil company. This particular station sells gas, and it also has a convenience store and a car wash. Each row summarizes sales for one day at this location. The column labeled Sales gives the dollar sales of the convenience store, and the column Volume gives the number of gallons of gas sold. Formulate the regression model with dollar sales as the response and number of gallons sold as the predictor.
(a) These data are a time series, with five or six measurements per week. (The initial data collection did not monitor sales on Saturday.) Does the sequence plot of residuals from the fitted equation indicate the presence of dependence?
(b) Calculate the Durbin-Watson statistic D. (Ignore the fact that the data over the weekend are not adjacent.) Does the value of D indicate the presence of dependence? Does it agree with your impression in part (a)?
(c) The residual for row 14 is rather large and positive. How does this outlier affect the ft of the regression of sales on gallons?
(d) Should the outlier be removed from the ft?