ANOVA and Regression Projects A national distributor of “Eagle” brand snacks is attempting to develop a model to explain sales of their product. To do so, data have been gathered on monthly sales (measured in hundreds of dollars) from its many marketing areas. From these, sixty observations have been selected at random. Data 114.5 47.3 43.5 0.65 2.40 3.25 B 70.1 51.3 38.5 0.76 2.55 3.06 A 111.4 51.1 37.7 0.75 2.74 3.12 C 122.1 43.7 42.9 0.83 2.46 1.85 C 127.9 54.2 39.2 0.65 2.55 2.52 C 83.3 46.3 38.8 0.84 2.75 2.87 B 97.0 53.6 42.7 0.69 2.83 2.65 D 114.6 51.6 44.6 0.75 2.60 1.87 D 118.4 53.9 42.4 0.77 2.54 2.24 B 75.2 53.4 36.3 0.77 3.12 1.87 B 71.7 53.6 44.4 0.85 3.27 2.46 A 80.0 46.1 43.2 0.82 2.95 3.37 D 71.4 49.1 39.0 0.64 2.93 2.97 D 105.0 51.3 43.7 0.67 2.71 2.61 D 97.6 55.9 43.6 0.77 2.93 2.14 A 76.2 51.7 36.8 0.70 3.02 1.58 A 86.6 48.7 40.3 0.80 2.45 1.51 A 138.2 59.2 43.5 0.82 2.50 2.02 C 90.4 54.6 42.2 0.72 2.98 3.14 B 88.5 58.4 35.8 0.72 3.11 1.82 D 98.1 42.2 44.4 0.72 2.42 3.40 A 71.6 57.7 36.0 0.84 2.90 2.91 D 111.9 50.5 38.1 0.62 2.93 1.75 C 83.5 48.8 39.4 0.82 2.92 2.06 B 112.8 49.7 39.1 0.69 3.02 1.84 C 75.5 48.0 35.8 0.82 2.95 1.58 B 84.2 58.1 41.5 0.76 2.75 3.03 B 78.1 56.2 39.2 0.80 2.79 3.08 A 90.1 47.2 40.5 0.73 2.69 2.13 D 119.0 51.7 38.7 0.81 2.84 1.82 C 120.0 47.5 42.6 0.74 2.77 1.81 C 117.4 56.2 35.6 0.79 2.87 2.08 C 120.9 47.1 38.2 0.63 2.51 2.23 C 97.2 52.1 37.4 0.78 2.72 3.02 B 120.5 51.9 43.4 0.67 2.99 1.85 C 104.6 52.0 39.7 0.71 2.38 1.50 D 96.4 55.0 35.8 0.80 2.68 1.81 B 95.1 54.1 44.3 0.77 3.06 1.72 D 72.0 45.0 39.0 0.82 2.97 2.34 B 99.8 52.2 42.5 0.78 2.59 1.90 A 111.5 47.9 44.6 0.78 2.51 3.12 C 51.1 44.2 35.6 0.72 2.88 3.40 A 80.4 49.7 35.0 0.72 2.69 2.03 D 109.6 54.2 38.4 0.82 2.73 1.50 D 106.1 58.9 42.4 0.76 3.28 3.16 C 79.5 51.8 38.2 0.79 2.75 2.70 A 94.1 57.7 43.1 0.67 2.92 2.84 D 97.7 53.8 39.8 0.75 2.79 2.52 A 61.6 53.8 40.0 0.79 3.27 1.55 A 64.1 44.0 39.8 0.73 3.02 1.93 A 92.1 46.0 35.4 0.78 2.99 2.48 C 67.4 54.0 36.2 0.80 3.09 1.55 A 82.5 55.1 44.1 0.72 2.68 2.49 A 70.9 49.2 38.0 0.77 3.06 3.22 B 64.6 49.1 44.4 0.77 2.66 2.95 A 104.7 57.6 37.4 0.78 2.81 3.41 B 103.9 53.4 43.6 0.81 3.05 2.19 B 79.3 48.2 44.8 0.76 2.48 2.83 A 126.8 50.2 44.5 0.72 2.14 3.18 B 83.6 41.9 39.8 0.76 2.55 2.57 A The data reported on the data sheet are as follows: Column #1 = Monthly sales in thousands of dollars per marketing area. 2 = Promotional budget for the sales area, in thousands of dollars. 3 = Median family income in the sales area, in thousands of dollars. 4 = Product recognition index, proportion of respondents to a marketing survey in the market district that recognized the Eagle brand name (reported as a decimal value). 5 = Average retail price of product in dollars. 6 = Average retail price of leading competitor brand in dollars. 7 = A coded variable representing the advertising method employed in the sales area. There are four levels of this categorical variable labeled A, B, C, and D as follows: A = Sports Magazine only B = Radio Sport Show Ads C = TV Sports Show Ad D = TV General Advertising Simple Regression Project Of particular interest to the company is the effect of advertising expenditures on sales, the effect their price has on sales, and the effect of the different package designs the company has been using on sales (note: the dependent variable is not unit sales but dollar sales reported in hundreds of dollars). You will need to adjust your Excel spreadsheet file from the Anova Project to do the following: In Excel use the Data > Data Analysis > Regression procedure to fit a simple regression of Sales (dependent, or Y, variable) as a function of Advertising Expenditures (independent, or X, variable). 1.Report the estimated regression equation. 2.Conduct the F-test for model significance. Interpret your results. 3.Interpret the slope coefficient and test for significance using a t test. 4.a. Use a t test to determine if the slope coefficient is significantly different (two-tail test) than the value 1.0 that is, test H0: = 1 against H1: 1. b. Of what importance is it to the company to know if this slope coefficient differs significantly from 1.0? 5.Be sure to include a copy of your Excel printout.