MATH 533 WEEK 7 COURSE PROJECT PART C, REGRESSION AND CORRELATION- PERFECT

MATH 533 WEEK 7 COURSE PROJECT PART C, REGRESSION AND CORRELATION- PERFECT 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