Please revise and improve the report in the attachment

20150413114348project_part_b-2.docx is the report for Hospital Case Part C. Please revise and improve the report because it got quite low score and some of the questions were not answered. To revised the report, please check out the attached PDF and EXCEL below. Remember: Only Project Part C: Regression and Correlation Analysis is requested. Please follow the required format and Grading Rubric to improve the score.

MATH533_Course_Project__Data_HOSPITAL-3.xlsx

MATH533_Course_Project_Requirements_HOSPITAL-3.pdf

Project Part C: Regression and Correlation Analysis Back to Top Using Minitab perform the regression and correlation analysis for the data on diabetes posttest (Y), the

dependent variable, and diabetes pretest (X), the independent variable, by answering the following.

1. Generate a scatterplot for diabetes posttest (Y) vs. diabetes pretest (X) including the graph of the “best fit” line. Interpret.

2. Determine the equation of the “best fit” line, which describes the relationship between diabetes posttest and diabetes pretest.

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 diabetes pretest to predict diabetes

   postest? Explain.

7. Compute the 95% confidence interval for beta-1 (the population slope). Interpret this interval. In an

   attempt to improve the model, we attempt to do a multiple regression model predicting diabetes posttest

   based on diabetes pretest and glucose.

8. Using Minitab, run the multiple regression analysis using the variables diabetes pretest and glucose to

   predict diabetes posttest. State the equation for this multiple regression model.

9. Perform the Global Test for Utility (F-Test). Explain your conclusion.

10. 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.

11. Is this multiple regression model better than the linear model that we generated in parts 1-7? Explain.

All DeVry University policies are in effect, including the plagiarism policy.

Project Part C report is due by the end of Week 7.

Project Part C is worth 100 total points. See grading rubric below.

Summarize your results from 1-11 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.