Please check out the DOCX and EXCEL document in the attachment and only do part C of the course Project,
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
(rural, urban, suburban)
(in $1,000's—be careful with this)
(household size, meaning number of people living in the household)
(the number of years that the customer has lived in the current location)
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
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
4. Determine the coefficient of
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
9. Using an interval, predict the
income for a customer that has a credit balance of $4,000. Interpret this
10. What can we say
about the income for a customer that has a credit balance of $10,000? Explain
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
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
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
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
1–14 addressed with appropriate output, graphs, and interpretations. Be
sure to number each point 1–14.