Question

13.50 The owner of a moving company typically has his most experienced manager predict the total number of labor hours that will be required to complete an upcoming move. This approach has proved useful in the past, but the owner has the business ob jective of developing a more accurate method of predicting labor hours. In a preliminary effort to provide a more accurate method, the owner has decided to use the number of cubic feet moved and the number of pieces of large furniture as the independent vari ables and has collected data for 36 moves in which the origin and destination were within the borough of Manhattan in New York City and the travel time was an insignificant portion of the hours worked. The data are organized and stored in

a. State the multiple regression equation.

b. Interpret the meaning of the slopes in this equation.

c. Predict the mean labor hours for moving 500 cubic feet with two large pieces of furniture.

d. Perform a residual analysis on your results and determine whether the regression assumptions are valid.

e. Determine whether there is a significant relationship between labor hours and the two independent variables (the number of cubic feet moved and the number of pieces of large furniture) at the 0.05 level of significance.

f. Determine the p-value in (e) and interpret its meaning.

g. Interpret the meaning of the coefficient of multiple determina tion in this problem.

h. Determine the adjusted r2.

i. At the 0.05 level of significance, determine whether each inde pendent variable makes a significant contribution to the regres sion model. Indicate the most appropriate regression model for this set of data.

j. Determine the p-values in (i) and interpret their meaning.

k. Construct a 95% confidence interval estimate of the population slope between labor hours and the number of cubic feet moved. How does the interpretation of the slope here differ from that in Problem 12.44 on page 443?

l. What conclusions can you reach concerning labor hours?

Hours	Feet	Large	Elevator
24.00	545	3	Yes
13.50	400	2	Yes
26.25	562	2	No
25.00	540	2	No
9.00	220	1	Yes
20.00	344	3	Yes
22.00	569	2	Yes
11.25	340	1	Yes
50.00	900	6	Yes
12.00	285	1	Yes
38.75	865	4	Yes
40.00	831	4	Yes
19.50	344	3	Yes
18.00	360	2	Yes
28.00	750	3	Yes
27.00	650	2	Yes
21.00	415	2	No
15.00	275	2	Yes
25.00	557	2	Yes
45.00	1028	5	Yes
29.00	793	4	Yes
21.00	523	3	Yes
22.00	564	3	Yes
16.50	312	2	Yes
37.00	757	3	No
32.00	600	3	No
34.00	796	3	Yes
25.00	577	3	Yes
31.00	500	4	Yes
24.00	695	3	Yes
40.00	1054	4	Yes
27.00	486	3	Yes
18.00	442	2	Yes
62.50	1249	5	No
53.75	995	6	Yes
79.50	1397	7	No

***Please show steps on how to do this in EXCEL (newest version) only. Thank you!***

Answer 1

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Normal probability plot:

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Interpretation:

The assumptions of residuals are seemed to be satisfied, because the residual plots enables that the residuals concentrated around the zero line and the normal probability plot shows that the residuals exists around the centered line.