The owner of a chain of ice cream stores has the business objective of improving the forecast of daily sales so that staffing shortages can be minimized during the summer season. The owner has decided to begin by developing a simple linear regression model to predict daily sales based on atmospheric temperature. A sample of 21 consecutive days is selected, and the results are stored in .
a. Assuming a linear relationship, use the least-squares method to compute the regression coefficients b0 and b1.
b. Predict the sales for a day in which the temperature is 83°F.
c. Plot the residuals versus the time period.
d. Compute the Durbin-Watson statistic. At the 0.05 level of significance, is there evidence of positive autocorrelation among the residuals?
e. Based on the results of (c) and (d), is there reason to question the validity of the model?