Follow the instructions under the title of “Using Excel’s Regression Tool for the Armand’s Pizza Parlors Example” to develop regression equation and ANOVA table as in Figure 14.13 and answer the following questions: Open the dataset of Armand’s (attached). Follow the instructions under the title of “Using Excel’s Regression Tool for the Armand’s Pizza Parlors Example” to develop regression equation and ANOVA table as in Figure 14.13 (attached). Upload the Figure 14.13. What is the estimated regression equation? Conduct the hypothesis test to test for significance of regression. Can we conclude that there is a significant relationship between student population and sales? Provide the rationale for your answer.
Follow the instructions under the title of “Using Excel’s Regression Tool for the Armand’s Pizza Parlors Example” to develop regression equation and ANOVA table as in Figure 14.13 and answer the following questions: Open the dataset of Armand’s (attached). Follow the instructions under the title of “Using Excel’s Regression Tool for the Armand’s Pizza Parlors Example” to develop regression equation and ANOVA table as in Figure 14.13 (attached). Upload the Figure 14.13. What is the estimated regression equation? Conduct the hypothesis test to test for significance of regression. Can we conclude that there is a significant relationship between student population and sales? Provide the rationale for your answer.
MATLAB: An Introduction with Applications
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Author:Amos Gilat
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Question
Follow the instructions under the title of “Using Excel’s Regression Tool for the Armand’s Pizza Parlors Example” to develop regression equation and ANOVA table as in Figure 14.13 and answer the following questions:
- Open the dataset of Armand’s (attached).
- Follow the instructions under the title of “Using Excel’s Regression Tool for the Armand’s Pizza Parlors Example” to develop regression equation and ANOVA table as in Figure 14.13 (attached).
- Upload the Figure 14.13.
- What is the estimated regression equation?
- Conduct the hypothesis test to test for significance of regression. Can we conclude that there is a significant relationship between student population and sales? Provide the rationale for your answer.
Transcribed Image Text:### Restaurant Performance Data
This table provides an overview of sales performance for ten restaurants. It highlights the relationship between the surrounding population of each restaurant and its sales figures.
| Restaurant | Population | Sales |
|------------|------------|-------|
| 1 | 2 | 58 |
| 2 | 6 | 105 |
| 3 | 8 | 88 |
| 4 | 8 | 118 |
| 5 | 12 | 117 |
| 6 | 16 | 137 |
| 7 | 20 | 157 |
| 8 | 20 | 169 |
| 9 | 22 | 149 |
| 10 | 26 | 202 |
#### Analysis:
- **Restaurant 1**: Located in an area with a population of 2, experiences low sales of 58 units.
- **Restaurant 10**: With the highest surrounding population of 26, leads in sales with 202 units.
- As the population increases, there is a general trend of increasing sales.
This data can be used as a basis for further analysis of how demographic factors impact restaurant sales performance.
Transcribed Image Text:# Excel's Regression Tool - Armand's Pizza Parlors Analysis
### Figure 14.13: Regression Tool Output
This figure displays the output from Excel's Regression Tool for Armand's Pizza Parlors. The analysis involves variables such as population and sales for different restaurants.
#### Data Table:
| Restaurant | Population | Sales |
|------------|------------|-------|
| 1 | 2 | 58 |
| 2 | 6 | 108 |
| 3 | 8 | 85 |
| 4 | 12 | 118 |
| 5 | 12 | 117 |
| 6 | 16 | 137 |
| 7 | 20 | 157 |
| 8 | 20 | 169 |
| 9 | 22 | 149 |
| 10 | 26 | 202 |
#### Summary Output:
##### Regression Statistics
- **Multiple R**: 0.9501
- **R Square**: 0.9027
- **Adjusted R Square**: 0.8906
- **Standard Error**: 13.8293
- **Observations**: 10
##### ANOVA
| | df | SS | MS | F | Significance F |
|------------|----|-------|-------|--------|----------------|
| Regression | 1 | 14200 | 14200 | 74.2484| 2.55E-05 |
| Residual | 8 | 1530 | 191.25| | |
| Total | 9 | 15730 | | | |
##### Coefficients
| | Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% | Lower 90.0% | Upper 90.0% |
|------------|--------------|----------------|--------|---------|-----------|-----------|-------------|-------------|
| Intercept | 60 | 9.2260 | 6.5033 | 0.0002 | 38.7247 | 81.2753 | 29.0431 | 90.9469 |
| Population |
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