# Using Minitab perform the regression and correlation analysi

Using Minitab perform the regression and correlation analysis for the data on diabetes posttest (Y), thedependent 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 ‘bestfit’ line. Interpret.2. Determine the equation of the ‘best fit’ line, which describes the relationship between diabetes posttestand diabetes pretest.3. Determine the coefficient of correlation. Interpret.4. Determine the coefficient of determination. Interpret.Test the utility of this regression model (use a two tail test with α =.05). Interpret your results, includingthe p-value.5. Based on your findings in 1-5, what is your opinion about using diabetes pretest to predict diabetespostest? Explain.6. Compute the 95% confidence interval for beta-1 (the population slope). Interpret this interval. In anattempt to improve the model, we attempt to do a multiple regression model predicting diabetes posttestbased on diabetes pretest and glucose.7. Using Minitab, run the multiple regression analysis using the variables diabetes pretest and glucose topredict diabetes posttest. 8. 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 youshould proceed. In particular, which independent variables should we keep and which should bediscarded.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 andinterprets the results in ways that are understandable to someone who does not know statistics.

0 replies