case 14

 

Complete Session 14 Case Study: Case Study 16.3.

Submit a Word document formatted in APA style complete with cover and reference pages.  The reference page must have at least one entry:  the textbook. 

The submission must be a form Research Report with the following parts:

Background information about the case:  The section must provide information about the people, places, operations, business, etc. and the research question or practical business challenges for which the current research will be used to provide a solution .  This section need not be long; up to two well written paragraphs are usually sufficient. 

Descriptive Statistics and Data illustration:  In this section, the submission must summarize how the data was obtained (see chapter 1 of the text). Graphs and charts illustrating the main features of the data are also required – please see chapter 2 of the textbook.   Finally, a table of descriptive statistics accompanied by  description and explanations of the main features of the data are also required.

Statistical Method:  This part of the submission must explain the main statistical method(s) used in the case.   What is the theory behind it? What are the working hypotheses (null and alternative, etc.), what main measures, statistics, or parameters etc.,  are to be estimated or calculated using the method; how does it measures or calculates these measures, statistics, or parameters?  Finally, this section must describe how the results of the statistical method are interpreted. That is, what is it about the results that would indicate that the working hypotheses or research questions are confirmed or rejected or perhaps need to be modified and tested again? 

Results:  The actual results of the statistical method applied to the data are now presented in this section.  The section requires the student to describe the results and their theoretical interpretation based on the description of the method described in the previous section.

Conclusion and Recommendation:  This section restates the statistical results and applies it to the business situation in the case.  It also makes practical recommendations about what steps the business in the case can take going forward based on the results of the statistical analysis.  The application and recommendation can take one or more of these general forms.

The statistical results of the data analysis provided an answer(s) to the issues that the business is facing.  As a result specific policies or practical steps can be implemented in the business. 
 The statistical results of the data analysis provided only partial answers.  More research and tests need to be done to come up with a more useful answers for the business situation.
The statistical results did not provide any useful information for the challenges that a business(s) is facing.  Recommendations for conducting new research with new approaches, data, variables, etc. may be required. 

Note

:  there is always room for ‘further research’ since it is impossible for a single research case to answer every possible question. 

Note

1. The textbook provides narratives, questions, or actual steps/questions for each case study.  While these are useful for conducting actual research, the submission must take the form of a research report and follow the above pattern.
2. The dataset is available here.
3. Consistent with the emphasis of this course on interpretation, an edited version of the answer key for the case study has been provided here.  An extensive worked example in Excel is available here.  Students are required to use the information to enhance their understanding of the statistical methods and whenever possible they must independently reproduce the results.

Case

1

6.3: Wagner Machine Works

The central issue in this case is whether or not a forecasting model could be developed using the data provided. The students should first plot the data to determine what type of pattern, if any, exists. By plotting this data they should be able to see an upward trend as well as a seasonal component. The following information is developed on this data and the regression model was run on the deseasonalized data:

Quarter																																																					1	2	3	4
	Seasonal Index	1.0209	1.05 62	0.89 69	1.0193

4560330427

 

 

 

1.91522E-44

Regression Statistics
Multiple R	0.98306 61 44
R Square	0.96 64 19044
Adjusted R Square	0.96 58 40062
Standard Error	1 65 2.905207
Observations	60
ANOVA
		Df	SS	MS	F	Significance F
Regression	1		4560330427	1 66 9.169406		1.91522E-44
Residual	58	158461546.1	2732095.623
Total	59	4 71 8791973
Coefficients	Standard Error	t Stat	P-value	Lower 95%
Intercept	70 47.816202	432.1693866	16.30799501	2.484E-23	6182.735833
Period	503.4104542	12.32173948	40.85546971	478.7458313

Seasonal Index

Quarter 1

1.0209

Quarter 2

1.0562

Quarter 3

0.8969

Quarter 4

1.0193

Quarter 1

1.0209

Quarter 2

1.0562

Quarter 3

0.8969

Quarter 4

1.0193

Year	Quarter	Period	Unadjusted Forecast	Adjusted Forecast
2001			Quarter 1	61	37756			1.0209	38545
		Quarter 2	62	38259			1.0562	40408
		Quarter 3	63	38763			0.8969	34765
		Quarter 4	64	39266			1.0193	40023
2002	65	39769	40600
66	40273	42535
67	40776	36571
68	41280	42075
2003	69	41783	42656
70	42287	44662
71	42790	38377
72	43293	44127

The students should prepare a report that includes graphs and tables showing the results of their