MATH533 Course Project Week 7

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MATH533 Course Project Week 7
Using an interval, estimate the average for the dependent variable for a selected…

Description

MATH533 Course Project Week 7

MATH533 Course Project Week 7

A+ AJ Davis Department

Project Part C: Regression and Correlation Analysis

  1. Generate a scatterplot for the specified dependent variable and the specified independent variable, including the graph of the “best fit” line. Interpret.
  2. Determine the equation of the “best fit” line, which describes the relationship between the dependent variable and the selected independent variable.
  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 the α provided by your Instructor). Interpret your results, including the p-value.
  6. Based on your findings in 1-5, what is your opinion about using the designated independent variable to predict the designated dependent variable? Explain.
  7. Compute the confidence interval for beta-1 (the population slope), using the confidence level specified by your Instructor.  Interpret this interval.
  8. Using an interval, estimate the average for the dependent variable for a selected value of the independent variable (to be provided by your Instructor). Interpret this interval.
  9. Using an interval, predict the particular value of the dependent variable for a selected value of the independent variable (to be provided by your Instructor). Interpret this interval.
  10. What can we say about the value of the dependent variable for values of the independent variable that are outside the range of the sample values? Explain your answer.

In an attempt to improve the model, we will attempt to do a multiple regression model predicting the dependent variable based on all of the independent variables.

11. Using MINITAB run the multiple regression analysis using the designated dependent and independent variables.  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. If any independent variables are to be discarded, re-run the multiple regression, including only the significant independent variables, and include the final Minitab output, with interpretation.

14.  Is this multiple regression model better than the linear model that we generated in parts 1-10? Explain.

Preview:

Interpretation: Income and time in years explains 79.21% of the variations in the credit balanced. Increase in income has a effect of increase credit balance while increase in time (years) seems to..