1. (5.0 POINTS) An air conditioning company located in Central Florida 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 5 78 7 81 12 84 15 86 16 89 22 91 18 93 19 94 26 a) (1.0 POINTS) 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 b) (1.0 POINT) 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. Guidance: follow the steps presented on Table 4.2 of textbook c) (0.5 POINTS) Calculate SST, SSE and SSR for this linear regression Guidance: follow the steps presented on Table 4.3 of textbook d) (0.5 POINTS) Calculate the coefficient of determination (r?) and the coefficient of correlation (r). e) (1.0 POINT) Using the linear regression equation that you developed in topic (b), calculate the estimated sales for a day that will reach 84 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? Explain