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MATH 534 Week 7 Course Project Part C: Regression and Correlation Analysis.

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Running head: COURSE PROJECT: PART C 1 Course Project: Part C Week 7 MATH 534 : Applied Managerial Statistics Keller Graduate School of Management Regression and Correlation Analysis COURSE PRO ... JECT: PART C 2 1. Generate a scatterplot for the specified dependent variable (Y) and the X1 independent variable, including the graph of the "best fit" line. Interpret. Fitted Plot Line 0 20 40 60 80 100 120 140 0 10 20 30 40 50 60 According to the Graph the linear relationship there is a positive relationship between Sales and calls. If number of calls increases the sales also increase and the same if sales increases the calls increases. COURSE PROJECT: PART C 3 2. Determine the equation of the "best fit" line, which describes the relationship between the dependent variable and the selected independent variable. y = 0.0707x + 31.2 3. Determine the coefficient of correlation. Interpret. The correlation coefficient between sales and calls is calculated as 0.268711. This is a moderate positive correlation between number of calls and number of sales. P Value = 0.000 4. Determine the coefficient of determination. Interpret. It is more commonly known as R squared value. It measures how close the data points are to the line. The coefficient of determination .0722. 7.2% of the variations can be explained by knowing the number of calls made. SUMMARY OUTPUT Regression Statistics Multiple R 0.332811341 R Square 0.110763389 Adjusted R Square 0.082974745 Standard Error 4.823306161 Observations 100 5. Test the utility of this regression model. Interpret results, including the p-value. H0: (Null Hypothesis) – There is not significant correlation H1: (Alternate Hypothesis)- There is correlation either negative or positive. COURSE PROJECT: PART C 4 P Value = 0.000 ANOVA df SS MS F Significance F Regression 3 278.1888971 92.72963236 3.985922758 0.010080614 Residual 96 2233 [Show More]

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