MATH 533 Week 7 Course Project Part C: Regression and Correlation Analysis
Using Minitab, perform the regression and correlation analysis for the data on SALES (Y) and CALLS (X) by answering the following questions.
- Generate a scatterplot for SALES versus CALLS, including the graph of the best fit line. Interpret.
- Determine the equation of the best fit line, which describes the relationship between SALES and CALLS.
- Determine the coefficient of correlation. Interpret.
- Determine the coefficient of determination. Interpret math 533 week 7 course project
- Test the utility of this regression model (use a two tail test with α =.05). Interpret your results, including the p-value.
- Based on your findings in 1–5, what is your opinion about using CALLS to predict SALES? Explain.
- Compute the 95% confidence interval for beta-1 (the population slope). Interpret this interval.
- Using an interval, estimate the average weekly sales for weekly calls that are 150. Interpret this interval.
- Using an interval, predict the weekly sales when weekly calls are 150. Interpret this interval.
- What can we say about the weekly sales when weekly calls are 300? Explain your answer.
- In an attempt to improve this model, we attempt to do a multiple regression model predicting SALES based on CALLS, TIME, and YEARS.
- Using Minitab, run the multiple regression analysis using the variables CALLS, TIME, and YEARS to predict SALES. State the equation for this multiple regression model.
- Perform the global test for utility (F-Test). Explain your conclusion math 533 week 7 course project
- 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.
- Is this multiple regression model better than the linear model that we generated in parts 1–10? Explain