Enterprise Industries produces Fresh, a brand of liquid laundry detergent. In order to manage its inventory more effecti

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Enterprise Industries Produces Fresh A Brand Of Liquid Laundry Detergent In Order To Manage Its Inventory More Effecti 1 (209.13 KiB) Viewed 13 times

Enterprise Industries produces Fresh, a brand of liquid laundry detergent. In order to manage its inventory more effectively and make revenue projections, 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 30 sales periods (each sales period is defined to be a four-week period). The demand data are presented in picture Excel Data File. For each sales period, let x₁ = x2 = x3 = X4 = the demand for the large size bottle of Fresh (in hundreds of thousands of bottles) in the sales period (Demand) the price (in dollars) of Fresh as offered by Enterprise Industries in the sales period the average industry price (in dollars) of competitors' similar detergents in the sales period Enterprise Industries' advertising expenditure (in hundreds of thousands of dollars) to promote Fresh in the sales period (AdvExp) the difference between the average industry price (in dollars) of competitors' similar detergents and the price (in dollars) of Fresh as offered by Enterprise Industries in the sales period (PriceDif). (Note that x4 = x2-x1). The JMP Output of a Regression Tree for the Fresh Detergent Demand Data RSquare RMSE 0.854 0.2561097 Split Prune All Rows Count Mean Std Dev 0.6812409 AdvExp<6.3 Count 15 LogWorth Difference 7.864 1.3218458 0.43714 Std Dev 0.3568073 Mean AdvExp<5.8 Count Mean Std Dev 0.3301947 Std Dev 30 LogWorth Difference 8.4526667 25.24418 1.17733 N Number of Splits 3 AdvExp>= 5.8 8 Count 7 7.66 Mean 8.0971429 0.2257369 30 AICC 15.9073 AdvExp>=6.3 Count 15 LogWorth Difference Mean 9.0413333 0.6822567 0.32556 Std Dev 0.3024157 PriceDif<0.5 Price Dif>=0.5 Count 9 Count 6 Mean 8.9111111 Mean 9.2366667 Std Dev 0.262985 Std Dev 0.2628815
The JMP Leaf Report for the Fresh Detergent Regression Tree Leaf Report Leaf Label AdvExp<6.3&AdvExp<5.8 AdvExp<6.3&AdvExp>5.8 AdvExp>6.3&PriceDif<0.5 AdvExp>6.3& PriceDif>0.5 31 32 PriceDif 0.3 0.1 AdvExp 7.8 6.1 Mean The JMP Predictions of Demand in Periods 31 and 32 Using the Fresh Detergent Regression Tree Leaf Demand Fresh in future sales period 31 Fresh in future sales period 32 7.66 8.09714286 8.91111111 9.23666667 Demand Predictor Count 8 7 Predicted Demand 9 6 The above image and tables show the JMP outputs of a regression tree analysis of the Fresh demand data, where the response variable is Demand and the predictor variables are AdvExp and PriceDif. The default minimum split size of 5 was used. Find the JMP regression tree prediction of demand for Fresh in Future sales periods 31 and 32. (Round your answers to 4 decimal places.) hundred thousand bottles hundred thousand bottles Number Formula 3 2 Leaf Label Formula AdvExp>6.3&PriceDif<0.5 AdvExp<6.3&AdvExp>5.8