Regression and Correlation Analysis in Applied Managerial Statistics: A Case Study, Assignments of Mathematics

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Course Project Final

Part: Regression and

Correlation Analysis

Course Name: MATH534 Applied Managerial Statistics

Student Name: XXX

Final Project: Regression and Correlation Analysis Brief Introduction For this regression analysis we will choose X1-calls as Independent Variable and Y-Sales as Dependent Variable. The reason behind it is because the correlation coefficient between Time and Years with Sales is weaker than Calls with Sales.

1. Generate a scatterplot for the specified dependent variable (Y) and the selected independent variable (X), 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. ^y= 0 .1278 x + 2 3.
3. Determine the correlation coefficient. Interpret. There is not a strong connection between the calls and the sales
4. Determine the coefficient of determination. Interpret. Based on the value of the coefficient of the determination we can conclude that only 10.95% in the variation in dependent variable sales can be explained by the variation in the dependent variable-calls. The rest of the 90% we have other factor that affect the dependent variable.

9. Using the same chosen value for part (8), estimate the 99% prediction interval for the dependent variable. Interpret this interval. Based on the regression equation, if we make x=173 calls, we are predicting to have between 27 and 64 sales. Our 99% prediction interval for the dependent variable is (27, 64).
10. What can be said about the value of the dependent variable for values of the independent variable that are outside the range of the sample values? Explain. When we choose the value of x=105 to be outside of the range, we get a wider interval for the dependent variable. 11.Describe a business decision that could be made based on the results of this analysis. In other words, how might the business operations change based on these statistical results. ❖ When we have an independent variable outside of the range of x, the difference between the upper and lower limits stays almost the same. ❖ Based on the coefficient of determination r^2 =0.11, only 11% of the variation in y can be explained by x. There are too many outside independent variables to determine if the calls are impacting sales. The management needs to look for what else could affect the sales.