BUSN 230 Statistical Analysis Using Excel

BUSN 230 Statistical Analysis Using Excel

The purpose of this assignment is to examine statistics via a practical application with emphasis on a real-world application. The project consists of four parts; the first three parts will be submitted in specified modules. The fourth, and Course part, will be submitted in the last module.  The Course part will consist of a complete analysis of what you concluded, based on your statistical calculations.  Refer to Part IV – Course Project Instructions below.

Each part is worth 75 points for a total of 300 points possible.

The Course Project is based off data taken from pages 723-724 of the textbook.  Information pertaining to the data is below:

When trying to decide what car to buy, real value is not necessarily determined by how much you spend on the initial purchase.  Instead, cars that are reliable and don’t cost much to own often represent the best values.  But, no matter how reliable or inexpensive a car may cost to own, it must also perform well.

To measure value, Consumer Reports developed a statistic referred to as a value score.  The value score is based upon five-year owner costs, overall road-test scores, and predicted reliability ratings.  Five-year owner costs are based on the expenses incurred in the first five years of ownership, including depreciation, fuel, maintenance and repairs, and so on.  Using a national average of 12,000 miles per year, an average cost per mile driven is used as the measure of five-year owner costs.  Road-test scores are the results of more than 50 tests and evaluations and are based upon a 100-point scale, with higher scores indicating better performance, comfort, convenience, and fuel economy.  The highest road-test score obtained in the tests conducted by Consumer Reports was a 99 for a Lexus LS 460L.  Predicted-reliability ratings (1 = poor, 2 = Fair, 3 = Good, 4 = Very Good, and 5 = Excellent) are based on data from Consumer Reports’ Annual Auto Survey.

A car with a value score of 1.0 is considered to be “average-value.”  A car with a value score of 2.0 is considered to be twice as good a value as a car with a value score of 1.0; a car with a value score of .5 is considered half as good as average; and so on.  The data for 20 family sedans, including the price ($) of each car tested, follow.

BUSN 230 Statistical Analysis Using Excel

DATA File:  Family Sedans

Part I – Use Excel

1. Identify the quantitative and qualitative variables being used with this data.  (Qualitative Variable)(Links to an external site.)

• The “Car”category is the Qualitative variable and all of the other categories are Quantitative variables.

2. Set up a pivot table (refer to Chapter 2 Appendix for how-to) showing the type of car, the price, and the predicted reliability.
3. Construct a side-by-side chart to compare the value score and the predicted reliability.
4. Construct two (2) scatter diagrams with trend lines for (1) Value Score and Price, (2) Price and Cost/Mile.
5. Given this data, what statistical question(s) would you ask? How would it help you?

• What are the advantages and disadvantages of the manual design process of these cars, and how would you assess the advantages and disadvantages of using CAD systems in the design process?

6. What do you surmise from the charts and graphs? Specifically, what is the relationship indicated in each graph?

• The relationship is indicated by differentiating the different model types, specifically by the value score of the car related to the cost of the vehicle, cost per mile versus the score, and the total reliability of the car.

7. Are we working with a sample or a population? How do you know?

• A sample since it is only tested on a specific group of that brand of the car.

8. Submit your calculations and charts/graphs via Excel. Written responses can be made in Excel or in a Word document.

Course Report – Elements to Include: 1. Abstract: A one paragraph summary of what the project was about, what you learned, and what you ended up finding. It should summarize the entire report. 2. Introduction: A discussion of what questions you are interested in. 3. Data Set: Describe how the data was used and the results of your calculations. Be sure to embed the graphs and charts into your Word document or audio/visual presentation. 4. Analysis: Discuss what the data told you. Was anything surprising? What other questions do you have about the results and the data? From the results, which car do you believe would be the best fit for your needs. 5. Limitations of study and conclusion: Describe any limitations of this study and how those limitations may have hindered this study. What would you like to see in future studies of this type? Should other variables be considered and if so, which ones? 6. Reference page in APA format. The Course submission will be in the following format: 1. Typewritten: Written reports should be at least four (4) pages in length, double-spaced, and contain good grammar and punctuation. Include headings for each section and references and address all the elements below. Use Arial or Times New Roman, Size 12 font with 1” margins all around and, when applicable, include graphs and/or tables (imbedded from Excel or other statistical software). Include a title page and references (if used) in APA formatting. As with all professionally presented documents, use proper APA citations when referring to work or ideas from others. Refer to the Course Project Rubric located in each part’s assignment submission and under Course Resources for further guidelines.

BUSN 230 Statistical Analysis Using Excel

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