Step 1 Download the Regression Analysis Practice document (Excel file).

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Step 1

Download the Regression Analysis Practice document (Excel file).

 

Step 2

Make sure you have the Data Analysis ToolPak add-in for your Excel. You can do that by going to the Data tab and searching for Data Analysis. If it does not appear, you will need to download it. The steps to download add-ins varies with each version of Excel. Here are the steps for the 2007 version:

 

  • Click on the Excel icon in the upper-left corner of your spreadsheet.
  • Click on Excel Options.
  • Along the left-side menu, click on Add-Ins.
  • Select Analysis ToolPak and follow the instructions.

 

Step 3

At the bottom, click on the “Demand for Jet Fuel” tab. The sample demand equation is estimated using this data set, and the results are shown.

 

Step 4

Use the procedure described to estimate the demand for gasoline using the same steps identified in the example below. Sample answers are based on the “Demand for Jet Fuel” data.

 

 

  1. Evaluate adjusted R2.

The adjusted R2 is 0.778421. It indicates that approximately 78% of the variation in the demand for jet fuel across states is explained by the three independent variables—price, state GDP, and state population.

 

 

  1. Evaluate each of the independent variables using a t-test.

Table 1 provides the results of the t-tests for each of the independent variables.

 

 

Coefficients

Standard Error

T-Stat

P-Value

Intercept

-18.4498

45.28617

-0.40741

0.68556

Price

0.138429

2.788582

0.049641

0.960619

GDP

0.170079

0.039165

4.342646

7.45E-05

Population

0.005281

0.001791

2.948036

0.004967

Table 1: T-Test Analysis

 

To assist use the Student t-Value Calculator:  http://www.danielsoper.com/statcalc3/calc.aspx?id=10

The degrees of freedom are 47, and the probability is 0.05. The critical value is approximately 2. If the absolute value of the t-statistic is greater than 2, the null hypothesis can be rejected. The P-value results can be used to determine whether to reject each of the following hypotheses.

 

Using the null hypothesis that each of the estimated coefficients is not significantly different from zero, and a 5% probably level (or a 5% probability of obtaining the test statistic as large or larger as the one obtained if the true value is in fact zero), the coefficients for GDP and Population are significant (reject the null hypothesis that the true values are 0), while coefficients for the intercept and price are not significant (do not reject the null hypothesis that the true values of the coefficients are zero).

 

Price:

(a)          H0: βp = 0; HA; βp ¹ 0                       Do not reject at the 5% level (P-value > 0.05)

 

GDP:

(b)          H0: βgdp = 0; HA; βgdp ¹ 0             Reject at the 5% level (P-value < 0.05)

 

POP:

(c)           H0: βpop = 0; HA; βpop ¹ 0            Reject at the 5% level (P-value < 0.05)

 

  1. Perform an f-test.

 

H0: βp = βgdp = βpop = 0;

HA: at least one β is not equal to zero

 

                Use the analysis of variance (ANOVA) information given in the table below.

 

ANOVA

 

 

 

 

 

 

df

SS

MS

F

Significance F

Regression

3

368163.7

122721.2

59.55115

4.83988E-16

Residual

47

96856.2

2060.77

 

 

Total

50

465019.9

 

 

 

Table 2: F-Test Analysis

 

F = 59.5515

 

Critical value

Critical F-Value Calculator:

http://www.danielsoper.com/statcalc3/calc.aspx?id=4

 

F(3,47) = 2.80235519

 

Since the 59.5515 > 4.00, reject the null hypothesis. At least one of the β’s is not equal to zero. You can also use the “Significance of F” information, which indicates that the critical value would need to be essentially zero to not reject the null hypothesis.

 

Step 5

Submit your regression results and answers to the questions given using the Assignment link.

 

 Trillions of BTUsPrice per Million BTUBillions of DollarsMillions
 QuantityPriceGDPPopulation
Alabama325.221.09154.14,785
Alaska34.827.1745714
Arizona323.621.85228.56,413
Arkansas176.221.3491.82,922
California1,835.7024.051,731.8037,338
Colorado260.821.35235.25,048
Connecticut184.722.99211.33,575
Delaware54.721.9556.2605
Dist. of Col.12.723.0890.7605
Florida998.321.17673.418,839
Georgia599.920.413629,712
Hawaii50.327.1759.31,363
Idaho8223.0150.71,571
Illinois600.321.92581.312,842
Indiana369.621.18245.46,491
Iowa195.121.54127.73,050
Kansas146.121.391142,859
Kentucky272.921.9144.64,347
Louisiana280.421.2195.24,545
Maine83.222.85461,327
Maryland329.322.05264.95,786
Massachusetts344.322.17342.16,555
Michigan558.921.4344.99,877
Minnesota310.722.32243.45,311
Mississippi201.721.1687.12,970
Missouri392.420.9217.35,996
Montana60.222.9131.8991
Nebraska103.822.1379.71,830
Nevada13422.75111.62,704
New Hampshire88.522.1954.61,317
New Jersey517.621.26438.78,800
New Mexico110.922.0172.819,395
New York712.422.321,034.309,560
North Carolina544.521.99380.6675
North Dakota45.622.8731.3675
Ohio61822.01426.111,538
Oklahoma232.420.95133.53,760
Oregon18723.33166.73,838
Pennsylvania633.922.54505.91,053
Rhode Island48.122.79441,053
South Carolina325.620.69145.14,637
South Dakota51.722.2936.3817
Tennessee387.921.26228.76,357
Texas1,511.2021.081,106.2025,253
Utah125.322.9102.82,775
Vermont40.522.9623.1626
Virginia499.921.35380.68,024
Washington328.624.05306.66,743
West Virginia105.423.05561,854
Wisconsin313.922.63221.35,692
Wyoming40.121.4534.4565
     
Source: U.S. Department of Energy, Energy Information Agency
http://www.eia.gov/beta/state/seds/seds-data-complete.cfm#Consumption

 

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