**Understanding Regression Analysis: Sales Contacts and Sales Dollars**A sales manager at an advertising agency is exploring the relationship between the number of contacts a salesperson makes and the sales dollars earned. A regression analysis was conducted, and the results are outlined below.### Regression Analysis Summary:**Coefficients Table:**- **Intercept:** - **Coefficient:** -12.201 - **Standard Error:** 6.560 - **t-Statistic:** -1.860 - **p-value:** 0.100- **Number of Contacts:** - **Coefficient:** 2.195 - **Standard Error:** 0.176 - **t-Statistic:** 12.505 - **p-value:** 0.000**Interpretation:**- The intercept term (-12.201) indicates the expected sales dollars when no contacts are made; however, it's not statistically significant (p = 0.100).- Each additional contact is associated with an increase of approximately 2.195 dollars in sales, which is statistically significant (p = 0.000).### Analysis of Variance (ANOVA):**ANOVA Table:**- **Regression:** - **df (Degrees of Freedom):** 1.00 - **SS (Sum of Squares):** 13,555.42 - **MS (Mean Square):** 13,555.42 - **F-Statistic:** 156.38 - **Significance F:** 0.00- **Residual:** - **df:** 8.00 - **SS:** 693.48 - **MS:** 86.68- **Total:** - **df:** 9.00 - **SS:** 14,248.90**Interpretation:**- The F-Statistic of 156.38 with a significance level of 0.00 indicates that the model is highly significant overall.### Additional Information:- **Mean of X ($ \bar{X} $):** 33.4- **Sum of Squares of X deviation ($ \sum(X - \bar{X})^2 $):** 2814.4### Prediction Interval:The 95% prediction interval for a salesperson making 30 calls can be calculated using the above model statistics, incorporating variability in

Formula : Prediction interval for an individual y for x = xp is as follows : PI = y^ ±…

Answered: A sales manager for an advertising…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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A sales manager for an advertising agency believes there is a relationship between the number of contacts that a salesperson makes and the amount of sales dollars earned. A regression analysis shows the following results. Coefficients Standard Error t-Stat p-value Intercept -12.201 6.560 -1.860 0.100 Number of contacts 2.195 0.176 12.505 0.000 ANOVA df SS MS F Significance F Regression 1.00 |13,555.42 |13,555.42 156.38 0.00 Residual 8.00 693.48 86.68 Total 9.00 14,248.90 Assume that X = 33.4 and E(X – X) 2814.4. Rounding to one decimal place, the 95% confidence interval for 30 calls is
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