Developing a model to explain and predict sales

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Reference no: EM13988397

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.

The variables in the data set are in columns, one observation per line (row). The first column is variable number 1, the second is variable number 2, etc.

Variable #1 = Monthly sales in thousands of dollars per marketing area.

This is the variable in which the company is primarily interested. They would like to determine what factors have an effect on their sales. They would also like to be able to predict sales based upon these factors, once they are identified. This variable will be the dependent variable in your analyses.

The company has also identified several potential explanatory factors that may have an effect on Eagle Chip sales. These are identified below and available in your data set. Variables 2 through 6 are quantitative high-level measurements. Variable 7 is qualitative having four nominal levels identified below.

Variable #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 Download your data set, import your data set into Excel, label your variables, and save your Excel file.

59.7 49.2 40.4 0.77 2.97 2.45 A

113.3 50.9 36.2 0.68 2.59 2.29 C

98.7 53.6 43.3 0.65 2.45 2.09 A

114.4 55.1 41.5 0.81 2.19 2.51 D

69.7 47.7 36.8 0.66 2.45 2.49 A

56.2 46.4 37.9 0.73 3.22 3.20 B

81.8 50.2 35.5 0.85 2.85 3.19 B

96.2 55.0 38.9 0.77 2.72 1.90 D

75.1 48.1 35.7 0.77 2.65 3.17 B

100.9 52.1 40.5 0.76 2.89 3.42 C

104.7 50.5 41.8 0.71 2.53 2.58 D

48.3 48.2 36.1 0.82 2.78 3.43 A

100.0 47.8 42.1 0.84 2.64 1.73 B

111.6 42.2 44.0 0.79 2.45 2.12 B

89.4 54.1 43.5 0.71 3.14 3.15 D

80.7 49.3 44.1 0.75 3.20 2.22 D

98.5 49.0 35.5 0.79 2.32 2.10 B

85.4 42.6 37.0 0.78 2.78 2.20 B

69.7 39.9 40.3 0.79 3.03 3.10 B

87.5 54.1 44.2 0.73 2.65 3.22 A

99.5 53.2 40.3 0.73 2.67 3.41 B

98.8 56.1 40.1 0.72 2.57 2.60 B

108.8 41.0 38.1 0.71 2.62 1.55 C

86.5 43.2 35.5 0.70 2.92 2.47 C

128.7 57.6 42.8 0.77 2.58 1.52 C

111.6 53.3 44.3 0.77 2.63 1.90 B

114.6 52.1 37.8 0.73 2.63 2.65 C

81.8 56.5 40.8 0.77 3.51 1.90 B

116.0 53.2 39.5 0.74 2.65 2.67 C

84.4 59.3 39.5 0.86 2.92 3.37 A

98.3 56.9 37.9 0.79 2.67 2.31 B

111.6 52.7 39.8 0.73 2.37 1.98 B

61.2 44.0 37.4 0.70 2.57 1.99 A

53.5 49.1 38.8 0.89 3.05 3.32 D

122.3 52.8 40.0 0.82 2.79 2.89 C

107.8 54.3 39.7 0.73 3.12 3.48 C

72.2 49.5 36.6 0.74 2.55 2.94 B

83.6 42.2 38.7 0.75 2.80 1.99 C

65.7 56.3 35.3 0.66 3.18 2.67 B

93.3 55.3 37.4 0.74 2.70 3.50 D

89.6 54.3 39.2 0.80 2.51 3.37 A

92.5 48.8 38.3 0.82 2.63 1.75 D

43.1 42.1 38.2 0.74 3.16 2.72 A

112.8 47.3 38.3 0.73 2.35 2.36 C

102.4 50.1 41.7 0.77 2.50 3.42 D

89.9 58.7 39.8 0.71 3.00 2.97 A

89.3 52.6 37.8 0.67 2.97 2.78 D

114.8 56.3 39.8 0.75 3.04 3.21 C

64.3 51.6 38.7 0.72 2.71 1.75 A

67.1 49.3 39.8 0.68 3.02 3.24 B

74.7 52.3 39.3 0.71 3.28 1.83 B

106.3 51.4 42.1 0.74 2.44 2.08 D

101.2 56.0 39.8 0.77 2.48 2.44 D

85.1 44.9 38.5 0.73 2.80 3.25 B

95.3 53.0 42.0 0.76 2.90 2.10 D

69.6 52.4 36.3 0.73 2.90 3.22 A

102.4 60.2 44.5 0.67 3.23 2.16 C

106.5 48.0 41.6 0.82 2.80 2.24 C

62.3 44.6 38.4 0.75 2.65 2.98 A

93.0 51.9 39.0 0.75 2.61 2.45 A

The company is primarily interested in developing a model to explain and predict sales. Company sales (variable number 1) will be your dependent variable in these analyses.

Part A. Provide summary descriptive statistics for company sales.

Part B. The company is interested in determining which, if any, of the advertising methods used might lead to the highest average sales level and has asked you to do the analysis to provide this information. It will be possible to make this determination since each observation in the sample was generated using only one of the four advertising methods.

Perform an analysis of variance on Excel as demonstrated in class using Sales (variable number 1) as the dependent variable and Advertising Method (variable 7) as the explanatory variable.

1. Specify the null and alternative hypotheses for the F-test for this model.

2. Report the critical value of the test statistic -or- interpret the p-level for this test.

3. State your conclusion regarding the test result.

4. Interpret your finding; in particular, make certain that you respond to the company’s inquiry.

Reference no: EM13988397

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