The Fresh Detergent Case Enterprise Industries produces Fresh, a brand of liquid detergent. In order to more effectively manage its inventory, the company would like to better predict demand for Fresh. To develop a prediction model, the company has gathered data concerning demand for Fresh over the last 33 sales periods. Each sales period is defined as one month. The variables are as follows: · Period = Time period in month · Demand = Y = demand for a large size bottle of Fresh (in 100,000) · Price = the price of Fresh as offered by Ent. Industries · AIP = the Average Industry Price · ADV = Enterprise Industries Advertising Expenditure (in $100,000) to Promote Fresh in the sales period. · DIFF = AIP - Price = the "price difference" in the sales period Only the trend of PRICE is negative. Other four variables have positive trends. However, the R2 values suggest that for ADV and DEMAND only the linear model is explained by the data points moderately (66% and 51% respectively). For all the other three variables, the R2 values are too poor to accept the models as adequates because very few percent of data points actually represents the linear model. As expected, the Demand is negatively correlated with Price. But the regression line equation cannot be relied upon due to poor R2 value. For other three variables, there is a positive correlation. Out of these, for the ADV variable, the regression line can be adequate for the R2 value is moderately higher. Interpretation Strong positive correlation is found between 1. PERIOD and ADV 2. PERIOD and DEMAND 3. AIP and DIFF 4. DIFF and ADV 5. DIFF and DEMAND 6. ADV and DEMAND Strong negative correlation exists between 1. PRICE and DIFF 2. PRICE and ADV 3. PRICE and DEMAND PERIOD DEMAND Forecast MA(3) Forecast MA(6) Absotute Error - MA(3) Absotute Error - MA(6) 1 9.4 2 10.3 3 11.5 4 11.1 10.4 0.7 5 11 11.0 0.0 6 10.5 11.2 0.7 7 10.2 10.9 10.6 0.7 0.4 8 8.9 10.6 10.8 1.7 1.9 9 8.3 9.9 10.5 1.6 2.2 10 8.12 9.1 10.0 1.0 1.9 11 8.8 8.4 9.5 0.4 0.7 12 9.8 8.4 9.1 1.4 0.7 13 10.1 8.9 9.0 1.2 1.1 14 11.3 9.6 9.0 1.7 2.3 15 12.5 10.4 9.4 2.1 3.1 16 12.4 11.3 10.1 1.1 2.3 17 12.1 12.1 10.8 0.0 1.3 18 11.8 12.3 11.4 0.5 0.4 19 11.5 12.1 11.7 0.6 0.2 20 11 11.8 11.9 0.8 0.9 21 10.2 11.4 11.9 1.2 1.7 22 10.3 10.9 11.5 0.6 1.2 23 10.9 10.5 11.2 0.4 0.2 24 11.2 10.5 11.0 0.7 0.2 25 12.5 10.8 10.9 1.7 1.7 26 13.4 11.5 11.0 1.9 2.4 27 14.7 12.4 11.4 2.3 3.3 28 14.1 13.5 12.2 0.6 1.9 29 14 14.1 12.8 0.1 1.2 30 13.5 14.3 13.3 0.8 0.2 31 13.5 13.9 13.7 0.4 0.2 32 13.1 13.7 13.9 0.6 0.8 33 12.5 13.4 13.8 0.9 1.3 34 13.0 13.5 MAD = 0.9 1.3 Since MAD of MA(3) is less than that of MA(6), we should be preferring MA(3) over MA(6). However, Moving average may not be a good choice for predicting the demand because there is a clear p ...