A short-term study was conducted to investigate the effect of mean monthly daily temperature x1 and cost
Question:
E(y) = β0 + β1x1 + β2x21 + β3x2 + β4x1x2 + β5x21x2
to the data shown in the table. The Excel printout for this multiple regression problem is also provided.
Excel output for Exercise 13.28
a. Do the data provide sufficient evidence to indicate that the model contributes information for the prediction of mean daily kilowatt-hour consumption per household? Test at the 5% level of significance.
b. Graph the curve depicting Å· as a function of temperature x1 when the cost per kilowatt hour is x2 = 8¢. Construct a similar graph for the case when x2 = 10¢ per kilowatt-hour. Are the consumption curves different?
c. If cost per kilowatt-hour is unimportant in predicting use, then you do not need the terms involving x2 in the model. Therefore, the null hypothesis H0: x2 does not contribute information for the prediction of y is equivalent to the null hypothesis H0: β3 = β4 = β5 = 0 (if β3 = β4 = β5 = 0, the terms involving x2 disappear from the model). The MINITAB printout, obtained by fitting the reduced model
E(y) = β0 = β1x1 = β2x21
to the data, is shown here. Use the methods of Section 13.5 to determine whether price per kilowatt hour x2 contributes significant information for the prediction of y.
Excel output for Exercise 13.28
d. Compare the values of R2(adj) for the two models fit in this exercise. Which of the two models would you recommend?
Step by Step Answer:
Introduction To Probability And Statistics
ISBN: 9781133103752
14th Edition
Authors: William Mendenhall, Robert Beaver, Barbara Beaver