Reference no: EM13904934
Read the scenario and analyze the given data by answering the following questions. All calculations must be conducted using statistical software MS Excel. You must provide, as a part of your response to the calculation questions, the session output of the statistical software, screen shots of the MS Excel formula/results. Answer the questions directly on this MS Word document. Grading of this assignment will follow the grading rubric provided in the course syllabus.
Scenario: In the early 1990s, research at the Ohio State University studied consumer ratings of six fast-food restaurants: Borden Burger, Hardee's, Burger King, McDonald's, Wendy's, and White Castle. Each of the 406 randomly selected individuals gave each restaurant a rating of 1, 2, 3, 4, 5, or 6 on the basis of taste, and then ranked the restaurants from 1 through 6 on the basis of overall preference. In each case, 1 is the best rating and 6 is the worst rating. The data collected, used the same scale and included taste (MeanTaste), convenience (MeanConv), familiarity (MeanFam), price (MeanPrice) and preference (MeanPref). The requirement is to determine if there is a relationship between convenience and price, and if predictions of convenience can be made based on price. The mean ratings given by the 406 individuals are given in the following table:
Table 1. Output of Fast-Food Restaurant Ratings
Restaurant
|
MeanTaste
|
MeanConv
|
MeanFam
|
MeanPrice
|
MeanPref
|
BordenBurger
|
3.5659
|
2.7005
|
2.5282
|
2.9372
|
4.2552
|
Hardee's
|
3.3290
|
3.3483
|
2.7345
|
2.7513
|
4.0911
|
Burger King
|
2.4231
|
2.7377
|
2.3368
|
3.0761
|
3.0052
|
McDonald's
|
2.0895
|
1.9380
|
1.4619
|
2.4884
|
2.2429
|
Wendy's
|
1.9661
|
2.8920
|
2.3376
|
4.0814
|
2.5351
|
White Castle
|
3.8061
|
3.7242
|
2.6515
|
1.7080
|
4.7812
|
1. Describe the data and variables.
2. Conduct appropriate descriptive statistical analysis, using selected software, for the given data (include appropriate graphs, if possible). Ensure you include screen shots of the MS Excel analysis.
3. Describe the appropriate method of analysis and the reason for its appropriateness.
4. Conduct appropriate statistical analysis, using selected software. Ensure you include the session output from screen shots of the MS Excel analysis, .
5. Provide your supported decision, based on any hypothesis tests, and your recommendations, where appropriate.
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