MMB-HW * D O Saved to Drive Edit View Insert Format Tools Add-ons Help Accessibility Last edit was seconds ago 100% Normal text Calibri BIUA E- E E- E E E 10 1. I 2 | 4 I ..5 I 6 I I Þerform the...

Extracted text: MMB-HW * D O Saved to Drive Edit View Insert Format Tools Add-ons Help Accessibility Last edit was seconds ago 100% Normal text Calibri BIUA E- E E- E E E 10 1. I 2 | 4 I ..5 I 6 I I Þerform 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 (r) and the coefficient of correlation (r). ST, 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. Using the linear regression equation that you developed in topic (b), calculate the estimated sales for a day that will reach 72 degrees F and for a day that will reach 94 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. #2 a- Freeze Inc. is planning the implementation of a new sales offices in the Tampa – FL area for its growing air conditioning business and have identified activities and their immediate predecessors for this project as follows:


Extracted text: Normal text Calibri BIUA 10 2 |II 3 I. 4 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 4 72 78 8 81 10 84 14 86 15 89 21 91 20 93 22 94 25 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. a) 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