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

Posted: Tue Jul 05, 2022 9:56 am
by answerhappygod
Enterprise Industries Produces Fresh A Brand Of Liquid Laundry Detergent In Order To Manage Its Inventory More Effecti 1
Enterprise Industries Produces Fresh A Brand Of Liquid Laundry Detergent In Order To Manage Its Inventory More Effecti 1 (137.58 KiB) Viewed 11 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 y = x1 = x2 = x3 = X4 = the demand for the large size bottle of Fresh (in hundreds of thousands of bottles) in the sales period (Demand) Split 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 Prune AdvExp<7.2 Count Mean Std Dev 0.3568073 RSquare RMSE 0.854 0.2561097 N Number of Splits 30 3 All Rows Count 30 LogWorth Difference Mean 8.8326667 25.24418 1.17733 Std Dev 0.6812409 AICC 15.9073 AdvExp>=7.2 Count 15 LogWorth Difference 15 LogWorth Difference 8.244 1.3218458 0.43714 Mean 9.4213333 0.6822567 0.32556 Std Dev 0.3024157

AdvExp<6.7 AdvExp>=6.7 Price Dif<0.5 Count 8 Count Count 9 Count 6 Mean 8.04 Mean 8.4771429 Mean 9.2911111 Mean 9.6166667 Std Dev 0.3301947 Std Dev 0.2257369 Std Dev 0.262985 Std Dev 0.2628815 AdvExp<7.2 & AdvExp<6.7 AdvExp<7.2&AdvExp>6.7 AdvExp>7.2&PriceDif<0.5 AdvExp>7.2&PriceDif>0.5 The JMP Leaf Report for the Fresh Detergent Regression Tree Leaf Report Leaf Label 31 32 PriceDif 0.3 0.1 7 AdvExp 7.25 6.85 PriceDif>=0.5 Fresh in future sales period 31 Fresh in future sales period 32 Demand Mean 8.04 The JMP Predictions of Demand in Periods 31 and 32 Using the Fresh Detergent Regression Tree Leaf Number Formula 3 2 8.47714286 9.29111111 9.61666667 Demand Predictor Count 8 7 9 Predicted Demand 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 Leaf Label Formula AdvExp>7.2&PriceDif<0.5 AdvExp<7.2&AdvExp> 6.7