# Using MINITAB, Perform the Regression and Correlation Analysis

Using MINITAB perform the regression and correlation analysis for the data on CREDIT BALANCE (Y) and SIZE (X) by answering the following.

1. Generate a scatterplot for CREDIT BALANCE vs. SIZE, including the graph of the "best fit" line. Interpret.

2. Determine the equation of the "best fit" line, which describes the relationship between CREDIT BALANCE and SIZE.

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 ? =.05). Interpret your results, including the p-value.

6. Based on your findings in 1-5, what is your opinion about using SIZE to predict CREDIT BALANCE? Explain.

7. Compute the 95% confidence interval for . Interpret this interval.

8. Using an interval, estimate the average credit balance for customers that have household size of 5. Interpret this interval.

9. Using an interval, predict the credit balance for a customer that has a household size of 5. Interpret this interval.

10. What can we say about the credit balance for a customer that has a household size of 10? Explain your answer.

In an attempt to improve the model, we attempt to do a multiple regression model predicting CREDIT BALANCE based on INCOME, SIZE and YEARS.

11. Using MINITAB run the multiple regression analysis using the variables INCOME, SIZE and YEARS to predict CREDIT BALANCE. State the equation for this multiple regression model.

12. Perform the Global Test for Utility (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, 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.

Summarize your results report that is three 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 + (Minitab Output + interpretations) as an appendix.

Suggested format:

A. Summary Report

B. Addressed with appropriate output, graphs and interpretations.

https://brainmass.com/statistics/regression-analysis/using-minitab-perform-the-regression-and-correlation-analysis-508281

#### Solution Summary

The answers (except Q7 which is missing information) are attached in a Word, Excel and .MPJ format including the necessary graphs and charts.

Regression and Correlation Analysis.

Using MINITAB perform the regression and correlation analysis for the data on CREDIT BALANCE (Y) and SIZE (X) by answering the following.

1. Generate a scatterplot for CREDIT BALANCE vs. SIZE, including the graph of the best fit line. Interpret.

2. Determine the equation of the best fit line, which describes the relationship between CREDIT BALANCE and SIZE.

3. Determine the coefficient of correlation. Interpret.

4. Determine the index of determination. Interpret.

5. Test the utility of this regression model (use a two tailed test with alpha =.05). Interpret your results, including the p-value.

6. Based on your findings in 1-5, what is your opinion about using SIZE to predict CREDIT BALANCE? Explain.

7. Compute the 95% confidence interval for mean. Interpret this interval.

8. Using an interval, estimate the average credit balance for customers that have household size of 5. Interpret this interval.

9. Using an interval, predict the credit balance for a customer that has a household size of 5. Interpret this interval.

10. What can we say about the credit balance for a customer that has a household size of 10? Explain your answer.

In an attempt to improve the model, we attempt to do a multiple regression model predicting CREDIT BALANCE based on INCOME, SIZE and YEARS.

11. Using MINITAB run the multiple regression analysis using the variables INCOME, SIZE and YEARS to predict CREDIT BALANCE. State the equation for this multiple regression model.

12. Perform the Global Test for Utility (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, 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.

Summarize your results from 1-14 in a report that is three pages or less in length and explains and interprets the results in ways that are understandable to someone who does not know statistics.

Please explain in Microsoft Word format. No MINITAB.

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