The product manager for a brand of all-natural herbal shampoo has compiled 15 weeks of data on the weekly sales of the brand (in units), the level of media advertising (in thousands of dollars), the price (in dollars), and the use of displays (in number of stores with the brand on an end-aisle display). She then carried out a multiple regression analysis on these data in order to calculate a price elasticity. Her data and the results of the regression analysis can be seen below.Name each of the variables that were used in this multiple regression analysis. For each of these variables, indicate whether it was an independent variable or a dependent variable in this regression analysis.Use these data and the results of the regression analysis to calculate the price elasticity for this shampoo brand. Show your work.Based on the course material, describe two issues that should lead the product manager to not entirely trust the price elasticity calculated from this analysis. ### Table: Weekly Sales DataThis table presents data collected over a 15-week period, detailing sales figures alongside advertising expenditure, price, and display metrics.#### Columns:- **Week#**: Identifies the week number.- **Sales**: The number of units sold each week.- **Advertising**: The advertising costs for each week.- **Price**: The price per unit each week.- **Display**: Display score indicating promotional display intensity.#### Data Summary:- **Mean Values**: - Sales: 6408.5 units - Advertising: $169.6 - Price: $2.70 - Display: 60.0### Summary Output#### Regression Statistics:- **Multiple R**: 0.92- **R Square**: 0.85- **Adjusted R Square**: 0.81- **Standard Error**: 155.42- **Observations**: 15### ANOVA Table- **Degrees of Freedom (df)**: - Regression: 3 - Residual: 11 - Total: 14- **Sum of Squares (SS)**: - Regression: 1492659.25 - Residual: 265700.49 - Total: 1758359.73- **Mean Square (MS)**: - Regression: 497553.08 - Residual: 24154.59- **F Value**: 20.60- **Significance F**: 0.00### Coefficients Table| Variable | Coefficient | Standard Error | t Stat | P-value | Lower 95% | Upper 95% ||---------------|-------------|----------------|--------|---------|-----------|-----------|| Intercept | 932.8866 | 1402.29 | 6.65 | 0.00 | 6242.43 | 12415.28 || Advertising | 5.06 | 4.80 | 1.06 | 0.31 | -5.50 | 15.62 || Price | -1286.05 | 259.75 | -4.95 | 0.00 | -1857

The variables used in the analysis are:Sales (of the brand): Dependent variableAdvertising level:…

Answered: The product manager for a brand of…

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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The product manager for a brand of all-natural herbal shampoo has compiled 15 weeks of data on the weekly sales of the brand (in units), the level of media advertising (in thousands of dollars), the price (in dollars), and the use of displays (in number of stores with the brand on an end-aisle display). She then carried out a multiple regression analysis on these data in order to calculate a price elasticity. Her data and the results of the regression analysis can be seen below.

Name each of the variables that were used in this multiple regression analysis. For each of these variables, indicate whether it was an independent variable or a dependent variable in this regression analysis.
Use these data and the results of the regression analysis to calculate the price elasticity for this shampoo brand. Show your work.
Based on the course material, describe two issues that should lead the product manager to not entirely trust the price elasticity calculated from this analysis.