ECO 301 Regression Analysis of Gasoline and Jet Fuel Demands Worksheet

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ECO-301: Milestone Three Directions
Submit the results of your regression analysis for the demand function you are estimating for your term
project. Include:
? The data used to estimate the demand model
? The results of the analysis, an analysis of the results
? Description of remaining issue that needs to be addressed before the final paper is submitted.
Using your inventory of data collected, you will estimate and perform various analyses which will lead
you to an evaluation. At the conclusion of your analysis you will address how this example can inform
other real-world decision making in other organizations as well as your own decision-making and
management skills.
Statistical Analysis and Tests
1.
Evaluate Adj R2.
2.
Each variable (independent variables have to be tested by using t-test, so as to see whether
each of the variables (exogenous or independent) that you have include in the function has an
effect on the dependent variable (left hand side).
3.
For t-test, the following steps should be followed:
(i) H0: ?0 = 0
(Null hypothesis)
HA: ?0 ? 0
(Alternate hypothesis)
If t calculated > t table value (n-k) degrees of freedom
where:
4.
n = # of observations
k = # of parameters, i.e. # of right hand side variables plus the constant
then H0 is rejected, i.e. the variable you are testing has an effect on the dependent variable.
Do F-test, by following these steps:
(i) H0: ?0 = ?1 = ?2 = 0
(Null hypothesis)
HA: At least one ? is not equal to zero
(Alternate hypothesis)
(ii) If F calculated > F table value
Then H0 is rejected, i.e. all the right-hand-side variables are important.
Alabama
Alaska
Arizona
Arkansas
California
Colorado
Connecticut
Delaware
Dist. of Col.
Florida
Georgia
Hawaii
Idaho
Illinois
Indiana
Iowa
Kansas
Kentucky
Louisiana
Maine
Maryland
Massachusetts
Michigan
Minnesota
Mississippi
Missouri
Montana
Nebraska
Nevada
New Hampshire
New Jersey
New Mexico
New York
North Carolina
North Dakota
Ohio
Oklahoma
Oregon
Pennsylvania
Rhode Island
South Carolina
South Dakota
Trillions
of BTUs
Quantity
325.2
34.8
323.6
176.2
1,835.70
260.8
184.7
54.7
12.7
998.3
599.9
50.3
82
600.3
369.6
195.1
146.1
272.9
280.4
83.2
329.3
344.3
558.9
310.7
201.7
392.4
60.2
103.8
134
88.5
517.6
110.9
712.4
544.5
45.6
618
232.4
187
633.9
48.1
325.6
51.7
Price per
Million
BTU
Price
21.09
27.17
21.85
21.34
24.05
21.35
22.99
21.95
23.08
21.17
20.41
27.17
23.01
21.92
21.18
21.54
21.39
21.9
21.2
22.85
22.05
22.17
21.4
22.32
21.16
20.9
22.91
22.13
22.75
22.19
21.26
22.01
22.32
21.99
22.87
22.01
20.95
23.33
22.54
22.79
20.69
22.29
Billions of
Dollars
Millions
GDP
Population
154.1
4,785
45
714
228.5
6,413
91.8
2,922
1,731.80
37,338
235.2
5,048
211.3
3,575
56.2
605
90.7
605
673.4
18,839
362
9,712
59.3
1,363
50.7
1,571
581.3
12,842
245.4
6,491
127.7
3,050
114
2,859
144.6
4,347
195.2
4,545
46
1,327
264.9
5,786
342.1
6,555
344.9
9,877
243.4
5,311
87.1
2,970
217.3
5,996
31.8
991
79.7
1,830
111.6
2,704
54.6
1,317
438.7
8,800
72.8
19,395
1,034.30
9,560
380.6
675
31.3
675
426.1
11,538
133.5
3,760
166.7
3,838
505.9
1,053
44
1,053
145.1
4,637
36.3
817
Tennessee
Texas
Utah
Vermont
Virginia
Washington
West Virginia
Wisconsin
Wyoming
387.9
1,511.20
125.3
40.5
499.9
328.6
105.4
313.9
40.1
21.26
228.7
21.08 1,106.20
22.9
102.8
22.96
23.1
21.35
380.6
24.05
306.6
23.05
56
22.63
221.3
21.45
34.4
6,357
25,253
2,775
626
8,024
6,743
1,854
5,692
565
Source: U.S. Department of Energy, Energy Information Agency
http://www.eia.gov/beta/state/seds/seds-data-complete.cfm#Consumption
Alabama
Alaska
Arizona
Arkansas
California
Colorado
Connecticut
Delaware
Dist. of Col.
Florida
Georgia
Hawaii
Idaho
Illinois
Indiana
Iowa
Kansas
Kentucky
Louisiana
Maine
Maryland
Massachusetts
Michigan
Minnesota
Mississippi
Missouri
Montana
Nebraska
Nevada
New Hampshire
New Jersey
New Mexico
New York
North Carolina
North Dakota
Ohio
Oklahoma
Oregon
Pennsylvania
Rhode Island
South Carolina
Trillions
of BTUs
Quantity
11.9
128.9
20.9
5.6
544.3
63.8
8.5
0.5
0
199.4
105
51
3.3
144.8
43.1
2.8
17.2
58.6
120.7
8.7
16.7
36.4
20.8
51.5
32.9
17.7
5.3
4.7
26.1
3.3
227.2
7.3
83.7
9.2
4.6
75.8
38.7
24.5
70.6
3.6
5.5
Price per
Million
BTU
Price
16.44
16.81
16.63
16.13
16.17
16.2
16.41
16.24
0
16.44
16.24
16.39
16.87
16.16
16.09
16.79
16.27
16.34
16.15
16.41
16.28
16.41
16.23
16.39
16.13
16.27
16.87
16.78
16.56
16.41
16.16
16.61
16.43
16.18
16.27
16.3
16.44
16.52
16.1
16.41
16.62
Billions of
Dollars Millions
GDP Population
154.1
4,785
45
714
228.5
6,413
91.8
2,922
1,731.80
37,338
235.2
5,048
211.3
3,575
56.2
605
90.7
605
673.4
18,839
362
9,712
59.3
1,363
50.7
1,571
581.3
12,842
245.4
6,491
127.7
3,050
114
2,859
144.6
4,347
195.2
4,545
46
1,327
264.9
5,786
342.1
6,555
344.9
9,877
243.4
5,311
87.1
2,970
217.3
5,996
31.8
991
79.7
1,830
111.6
2,704
54.6
1,317
438.7
8,800
72.8
19,395
1,034.30
9,560
380.6
675
31.3
675
426.1
11,538
133.5
3,760
166.7
3,838
505.9
1,053
44
1,053
145.1
4,637
Regression Statist
South Dakota
Tennessee
Texas
Utah
Vermont
Virginia
Washington
West Virginia
Wisconsin
Wyoming
4.1
70
350.9
33.3
1.3
72
109.2
1.2
13.1
2.8
16.27
36.3
16.27
228.7
16.13 1,106.20
17.59
102.8
16.41
23.1
16.18
380.6
16.27
306.6
16.39
56
16.27
221.3
16.87
34.4
817
6,357
25,253
2,775
626
8,024
6,743
1,854
5,692
565
SUMMARY OUTPUT
Regression Statistics
Multiple R
0.889784
R Square
0.791716
Adjusted R Square 0.778421
Standard Error
45.39571
Observations
51
ANOVA
df
Regression
Residual
Total
3
47
50
SS
368163.6715
96856.19835
465019.8698
Intercept
Price
GDP
Population
Coefficients
-18.4498
0.138429
0.170079
0.005281
Standard Error
45.28617197
2.788582009
0.03916474
0.001791238
MS
F
Significance F
122721.2238 59.55115
4.83988E-16
2060.770178
t Stat
-0.407405649
0.049641374
4.34264555
2.948036043
P-value
0.68556
0.960619
7.45E-05
0.004967
Lower 95% Upper 95%
-109.5538676 72.65418
-5.471474268 5.748332
0.091289291 0.248868
0.001677128 0.008884
Lower 95.0%
Upper 95.0%
-109.554 72.65418
-5.47147 5.748332
0.091289 0.248868
0.001677 0.008884

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Explanation & Answer:
4 Questions

Tags:
economics

regression analysis

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