"For XXIAO only"
Inferential Statistics and Findings
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Inferential Statistics and Findings
University of Phoenix
Gibran Rezavi
June 22, 2015
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SHORT TITLE OF PAPER |
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Running head: INFERENTIAL STATISTICS AND FINDINGS |
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Inferential Statistics and Findings
In the Week 2 Business Research Project Part 1 assignment, our Team has identified the Samuel Adams Brewery as the company of interest for research. The Samuel Adams Brewery began in a kitchen with an old family recipe and using the name of an American patriot. The long award winning history of the brewery is now a household name being sold not only in restaurants but in grocery stores and other retail locations. Our Team A has created a research question and described a scenario on how this will affect the Samuel Adams Brewery.
Research Question
Our research question is: Is there a correlation between the number of drunken driving accidents and the alcohol tax rate?
Null hypothesis: The number of drunken driving accidents and the alcohol tax rate are not correlated.
Alternative hypothesis: The number of drunken driving accidents and the alcohol tax rate are correlated.
We conduct a regression analysis in Excel (See Table 1 in Appendix). The results were significant, r(7)=.887, p< .05. The null hypothesis was rejected, and we conclude that there is a correlation between the number of drunken driving accidents and the alcohol tax rate.
Reference
Anderson, D.R., Sweeney, D.J., Williams, T.A., Camm, J.D., & Cochran, J.J. (2015). Essentials of statistics for business and economics. (7th ed.). Stamford, CT: Cengage Learning.
Tax Foundation. (2013, April). State Excise Rates on Spirits, 2007-2013. Retrieved June 07, 2015, from Tax Foundation: taxfoundation.org/article/state-excise-tax-rates-2007-2013
Virginia Highway Safety Office. (2014). 2014 Virginia Traffic Crash Facts. Retrieved from
https://www.dmv.virginia.gov/safety/crash_data/crash_facts/crash_facts_14.pdf
Appendix
1) Data on number of crashes and alcohol tax rates
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Year |
Number of crashes |
Alcohol Tax rate ($/gallon) |
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2004 |
11504 |
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2005 |
11495 |
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2006 |
11736 |
14.02 |
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2007 |
11215 |
14.54 |
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2008 |
10294 |
14.54 |
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2009 |
9366 |
20.13 |
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2010 |
8217 |
20.13 |
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2011 |
8411 |
20.13 |
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2012 |
8776 |
20.91 |
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2013 |
8047 |
20.56 |
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2014 |
7666 |
19.19 |
2) Regression analysis
Table 1
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SUMMARY OUTPUT |
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Regression Statistics |
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Multiple R |
0.88674 |
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R Square |
0.786307 |
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Adjusted R Square |
0.75578 |
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Standard Error |
721.9054 |
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Observations |
9 |
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ANOVA |
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df |
SS |
MS |
F |
Significance F |
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Regression |
1 |
13423345 |
13423345 |
25.75729 |
0.001439 |
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Residual |
7 |
3648032 |
521147.4 |
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Total |
8 |
17071377 |
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Coefficients |
Standard Error |
t Stat |
P-value |
Lower 95% |
Upper 95% |
Lower 95.0% |
Upper 95.0% |
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Intercept |
17329.2 |
1599.648 |
10.83314 |
1.26E-05 |
13546.64 |
21111.77 |
13546.64 |
21111.77 |
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X Variable 1 |
-440.054 |
86.70731 |
-5.07516 |
0.001439 |
-645.084 |
-235.024 |
-645.084 |
-235.024 |
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