Please do Part C of Course Project: AJ DAVIS DEPARTMENT STORES
Please check out the DOCX and EXCEL document in the attachment and only do part C of the course Project,
Introduction |
AJ DAVIS is a department store chain, which has many credit customers and wants to find out more information about these customers. A sample of 50 credit customers is selected with data collected on the following five variables.
- Location (rural, urban, suburban)
- Income (in $1,000's—be careful with this)
- Size (household size, meaning number of people living in the household)
- Years (the number of years that the customer has lived in the current location)
- Credit balance (the customers current credit card balance on the store's credit card, in $).
The data is available in Doc Sharing Course Project Data Set as an Excel file. You are to copy and paste the data set into a minitab worksheet.
Project Part C: Regression and Correlation Analysis |
Using MINITAB, perform the regression and correlation analysis for the data on income(Y), the dependent variable, and credit balance (X), the independent variable, by answering the following.
1. Generate a scatterplot for income ($1,000) versus credit balance($), including the graph of the best fit line. Interpret.
2. Determine the equation of the best fit line, which describes the relationship between income and credit balance.
3. Determine the coefficient of correlation. Interpret.
4. Determine the coefficient of determination. Interpret.
5. Test the utility of this regression model (use a two tail test with α =.05). Interpret your results, including the p-value.
6. Based on your findings in 1–5, what is your opinion about using credit balance to predict income? Explain.
7. Compute the 95% confidence interval for beta-1 (the population slope). Interpret this interval.
8. Using an interval, estimate the average income for customers that have credit balance of $4,000. Interpret this interval.
9. Using an interval, predict the income for a customer that has a credit balance of $4,000. Interpret this interval.
10. What can we say about the income for a customer that has a credit balance of $10,000? Explain your answer.
In an attempt to improve the model, we attempt to do a multiple regression model predicting income based on credit balance, years, and size.
11. Using MINITAB, run the multiple regression analysis using the variables credit balance, years, and size to predict income. State the equation for this multiple regression model.
12. Perform the global test foruUtility (F-Test). Explain your conclusion.
13. Perform the t-test on each independent variable. Explain your conclusions and clearly state how you should proceed. In particular, state which independent variables should we keep and which should be discarded.
14. Is this multiple regression model better than the linear model that we generated in parts 1–10? Explain.
All DeVry University policies are in effect, including the plagiarism policy.
15. Project Part C report is due by the end of Week 7.
16. Project Part C is worth 100 total points. See the grading rubric below.
Summarize your results from 1–14 in a report that is 3 pages or less in length and explains and interprets the results in ways that are understandable to someone who does not know statistics.
Submission: The summary report + all of the work done in 1–14 (Minitab Output + interpretations) as an appendix
Format:
- Summary Report
- Points 1–14 addressed with appropriate output, graphs, and interpretations. Be sure to number each point 1–14.
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