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MBA 640 Data Analysis for Managers
Summer 2018 / Paul Natke
Extra credit – multiple regression estimation
10 points
Due: 11:59 p.m. EDT on Sunday, June 17
Data: Use the Excel file entitled “extra credit stock mkt data ” which is posted on Blackboard under Class
Assignments.
Complete the following tasks:
1. (1 points) Create a set of dummy variables for each of the three industries.
2. (2 points) Estimate a multiple regression equation with the price-earnings ratio (P/E) as the
dependent variable and the following as independent variables: intercept, gross profit margin,
sales growth, dummy variable for industry 1, and dummy variable for industry 2.
3. (6 points) Interpret the regression results:
a. adjusted R-square
b. F-statistic
c. t-statistics for each of the coefficients
4. (1 point) Calculate a P/E ratio point estimate for a firm with the following characteristics:
a. gross profit margin = 16%
b. sales growth = 13%
c. operates in the oil industry
Extra credit – time series estimation
10 points
Due: 11:59 p.m. EDT on Sunday, June 24
Data: Use the Excel file entitled “extra credit auto sales data” which is posted on Blackboard under Class
Assignments.
Complete the following tasks:
1. (7 points) Provide forecasts for every month of 2016 using the following methods
a. 12-month moving average (2 points)
b. simple time trend (2 points)
c. time trend with dummy variables for months (3 points)
2. (2 points) Calculate the Mean Square Error (i.e. the average of the sum of squared forecast
errors) for each forecasting method for the period January through June 2017.
3. (1 points) Rank the forecasting methods in order of lowest to highest MSE.
Motor Vehicle Unit Retail Sales
Table 1- Domestic Autos
domestic
autos sold (in
thousands)
month
year
January
February
March
April
May
June
July
August
September
October
November
December
January
February
March
April
May
June
July
August
September
October
November
December
January
February
March
April
May
June
July
August
September
October
November
December
January
February
March
April
May
June
2010
2010
2010
2010
2010
2010
2010
2010
2010
2010
2010
2010
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2012
2012
2012
2012
2012
2012
2012
2012
2012
2012
2012
2012
2013
2013
2013
2013
2013
2013
240.0
272.7
375.2
343.5
389.7
335.3
336.8
319.1
305.6
279.7
256.3
337.6
258.6
338.6
445.3
405.4
362.2
349.0
329.5
340.5
327.5
321.0
304.9
363.5
323.4
430.2
528.1
431.8
491.1
459.9
393.3
452.8
412.0
369.8
382.7
444.8
383.9
446.4
544.5
466.7
519.4
499.7
time
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
january
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
february
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
march
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
april
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
may
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
July
August
September
October
November
December
January
February
March
April
May
June
July
August
September
October
November
December
January
February
March
April
May
June
July
August
September
October
November
December
January
February
March
April
May
June
July
August
September
October
November
December
2013
2013
2013
2013
2013
2013
2014
2014
2014
2014
2014
2014
2014
2014
2014
2014
2014
2014
2015
2015
2015
2015
2015
2015
2015
2015
2015
2015
2015
2015
2016
2016
2016
2016
2016
2016
2016
2016
2016
2016
2016
2016
446.9
516.8
383.1
398.0
406.6
421.2
344.2
409.9
534.3
470.2
564.6
499.8
480.0
556.9
414.5
430.9
428.8
475.8
386.0
419.5
525.0
477.3
563.2
491.4
481.7
496.8
446.6
447.7
387.8
472.1
362.9
430.1
504.2
448.5
469.8
454.0
436.6
434.1
420.8
380.7
379.1
448.6
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
june
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
july
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
august
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
september
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
october
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
november
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
december
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
MBA 640 Data Analysis for Managers
Summer 2018 / Paul Natke
Extra credit – multiple regression estimation
10 points
Due: 11:59 p.m. EDT on Sunday, June 17
Data: Use the Excel file entitled “extra credit stock mkt data ” which is posted on Blackboard under Class
Assignments.
Complete the following tasks:
1. (1 points) Create a set of dummy variables for each of the three industries.
2. (2 points) Estimate a multiple regression equation with the price-earnings ratio (P/E) as the
dependent variable and the following as independent variables: intercept, gross profit margin,
sales growth, dummy variable for industry 1, and dummy variable for industry 2.
3. (6 points) Interpret the regression results:
a. adjusted R-square
b. F-statistic
c. t-statistics for each of the coefficients
4. (1 point) Calculate a P/E ratio point estimate for a firm with the following characteristics:
a. gross profit margin = 16%
b. sales growth = 13%
c. operates in the oil industry
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