Problem #1 - Freeze Inc. is an air conditioning company located in Lakeland, Florida. They collected data for the number of air conditioning units sold in the Central Florida area and for the outside temperature on the day that sales took place. The Sales Manager put the following table together: Outside Temperature Sales (Degrees F) (Number of air conditioning units sold) 68 3 72 78 81 12 84 15 86 16 89 22 91 18 93 19 94 26 a) Plot a scatter diagram for the data provided on the table above and the linear regression line calculated in topic (b). Consider that: Y: number of air conditioning units sold X: outside temperature (degrees F) Guidance: graph should look like the one presented in Figure 4.2 of textbook. Graph plotted by MS Excel, as a result of the Regression function will not be accepted. b) Perform the linear regression calculation and provide the linear regression equation that describes the relationship between Y (number of air conditioning units sold) and X (outside temperature in degrees Fahrenheit. Calculate: Coefficient of determination (r²) and the coefficient of correlation (r). SST, SSE and SSR for this linear regression. Estimate for the variance (o') and the standard deviation for the linear regression model you have developed Guidance: Follow the steps presented on Table 4.2 and 4.3 of textbook and show that your calculations followed that method. Do NOT present the resolution using MS Excel, because it will not count for this item. c) for a day that will reach 66 degrees F and for a day that will reach 95 F and for both temperature levels calculate Using the linear regression equation that you developed in topic (b), calculate the estimated sales the error "e" when comparing the estimated value against the actual data provided. At which of the two temperatures, is your model more accurate? Justify. d) spreadsheet You can use the linear regression function in MS Excel if vou prefer Using MS Excel, verify your calculations made in item (b) assuming a 0.05, upload the MS Excel
Problem #1 - Freeze Inc. is an air conditioning company located in Lakeland, Florida. They collected data for the number of air conditioning units sold in the Central Florida area and for the outside temperature on the day that sales took place. The Sales Manager put the following table together: Outside Temperature Sales (Degrees F) (Number of air conditioning units sold) 68 3 72 78 81 12 84 15 86 16 89 22 91 18 93 19 94 26 a) Plot a scatter diagram for the data provided on the table above and the linear regression line calculated in topic (b). Consider that: Y: number of air conditioning units sold X: outside temperature (degrees F) Guidance: graph should look like the one presented in Figure 4.2 of textbook. Graph plotted by MS Excel, as a result of the Regression function will not be accepted. b) Perform the linear regression calculation and provide the linear regression equation that describes the relationship between Y (number of air conditioning units sold) and X (outside temperature in degrees Fahrenheit. Calculate: Coefficient of determination (r²) and the coefficient of correlation (r). SST, SSE and SSR for this linear regression. Estimate for the variance (o') and the standard deviation for the linear regression model you have developed Guidance: Follow the steps presented on Table 4.2 and 4.3 of textbook and show that your calculations followed that method. Do NOT present the resolution using MS Excel, because it will not count for this item. c) for a day that will reach 66 degrees F and for a day that will reach 95 F and for both temperature levels calculate Using the linear regression equation that you developed in topic (b), calculate the estimated sales the error "e" when comparing the estimated value against the actual data provided. At which of the two temperatures, is your model more accurate? Justify. d) spreadsheet You can use the linear regression function in MS Excel if vou prefer Using MS Excel, verify your calculations made in item (b) assuming a 0.05, upload the MS Excel
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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I only need D please the last answer I was sent was wrong? Can that also be credited back to me.
Transcribed Image Text:**Problem #1** – Freeze Inc. is an air conditioning company located in Lakeland, Florida. They collected data for the number of air conditioning units sold in the Central Florida area and for the outside temperature on the day that sales took place. The Sales Manager put the following table together:
| Outside Temperature (Degrees F) | Sales (Number of air conditioning units sold) |
|---------------------------------|----------------------------------------------|
| 68 | 3 |
| 72 | 5 |
| 78 | 7 |
| 81 | 12 |
| 84 | 15 |
| 86 | 16 |
| 89 | 22 |
| 91 | 18 |
| 93 | 19 |
| 94 | 26 |
a) Plot a scatter diagram for the data provided on the table above and the linear regression line calculated in topic (b). Consider that:
- Y: number of air conditioning units sold
- X: outside temperature (degrees F)
**Guidance:** Graph should look like the one presented in Figure 4.2 of the textbook. Graph plotted by MS Excel, as a result of the Regression function, will not be accepted.
b) Perform the linear regression calculation and provide the linear regression equation that describes the relationship between Y (number of air conditioning units sold) and X (outside temperature in degrees Fahrenheit). Calculate:
- Coefficient of determination (r²) and the coefficient of correlation (r).
- SST, SSE, and SSR for this linear regression.
- Estimate for the variance (σ²) and the standard deviation for the linear regression model you have developed.
**Guidance:** Follow the steps presented on Table 4.2 and 4.3 of the textbook and show that your calculations followed that method. Do NOT present the resolution using MS Excel, because it will not count for this item.
c) Using the linear regression equation that you developed in topic (b), calculate the estimated sales for a day that will reach 68 degrees F and for a day that will reach 95 F and for both temperature levels calculate the error "e" when comparing the estimated value against the actual data provided. At which of the two temperatures, is your model more accurate? Justify.
d) Using MS Excel, verify your calculations made in item (b) assuming α
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