Exercises
Complete the following exercises:
•”Multiple Regression”: Exercises 17.39, and 17.42
•”Time-Series Analysis and Forecasting”: Exercises 20.19 and 20.35
Decision Analysis”: Exercises 22.2 and 22.11
**Submit your answers in a Microsoft Excel workbook, with each problem on a separate worksheet. Label each tab in the workbook with the exercise number. Highlight the answers in yellow and provide an interpretation in a text box.**
17.39
Perform the Durbin–Watson test at the 5% significance level to determine whether positive first-order autocorrelation exists when d = 1.10, n = 25, and k = 3.
17.42
Test the following hypotheses with a = .05.
20.19
Plot the following time series to determine which of the trend models appears to fit better.
Period
1
2
3
4
5
6
7
8
9
10
Time Series
55
57
53
49
47
39
41
33
28
20
20.35
The following trend line and seasonal indexes were computed from 4 weeks of daily observations. Forecast the 7 values for next week.
Day
Seasonal Index
Sunday
1.5
Monday
 .4
Tuesday
 .5
Wednesday
 .6
Thursday
 .7
Friday
1.4
Saturday
1.9
22.2
Draw the decision tree for Exercise 22.1.
(Exercise: 22.1) Set up the opportunity loss table from the following payoff table.
 
a 1
a 2

s 1
55
26
s 2
43
38
s 3
29
43
s 4
15
51
22.11
The owner of a clothing store must decide how many men’s shirts to order for the new season. For a particular type of shirt, she must order in quantities of 100 shirts. If she orders 100 shirts, her cost is $10 per shirt; if she orders 200 shirts, her cost is $9 per shirt; and if she orders 300 or more shirts, her cost is $8.50 per shirt. Her selling price for the shirt is $12, but any shirts that remain unsold at the end of the season are sold at her famous “half-price, end-of-season sale.” For the sake of simplicity, she is willing to assume that the demand for this type of shirt will be 100, 150, 200, or 250 shirts. Of course, she cannot sell more…