Answer Happy

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 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) the price (in dollars) of Fresh as offered by Enterprise Industries in the sales period Split 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 Prune AdvExp<6.95 Count Mean Std Dev 0.3568073 0.854 0.2561097 N Number of Splits 15 LogWorth Difference 8.234 1.3218458 0.43714 30 All Rows Count 30 LogWorth Difference Mean 8.8226667 25.24418 1.17733 Std Dev 0.6812409 AICC 3 15.9073 AdvExp>=6.95 Count 15 LogWorth Difference Mean 9.4113333 0.6822567 0.32556 Std Dev 0.3024157
AdvExp<6.95 Count Mean Std Dev 0.3568073 15 LogWorth Difference Count 15 LogWorth Difference 8.234 1.3218458 0.43714 Mean 9.4113333 0.6822567 0.32556 Std Dev 0.3024157 AdvExp<6.45 Count Mean AdvExp>=6.45 8 Count Price Dif<0.5 Count Mean 9.2811111 Mean 9.6066667 Price Dif>=0.5 9 Count 8.03 Mean 8.4671429 Std Dev 0.3301947 Std Dev 0.2257369 Std Dev 0.262985 Std Dev 0.2628815 AdvExp<6.95&AdvExp<6.45 AdvExp<6.95&AdvExp>6.45 AdvExp>6.95&PriceDif<0.5 AdvExp>6.95&PriceDif>0.5 31 32 The JMP Leaf Report for the Fresh Detergent Regression Tree Leaf Report Leaf Label AdvExp>=6.95 PriceDif 0.3 0.1 7 AdvExp 7.45 6.5 Fresh in future sales period 31 Fresh in future sales period 32 The JMP Predictions of Demand in Periods 31 and 32 Using the Fresh Detergent Regression Tree Leaf Number Formula 3 2 Mean 8.03 8.46714286 9.28111111 9.60666667 Demand 6 Demand Predictor Count 8 7 9 6 Predicted Demand 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.) Leaf Label Formula AdvExp>6.95&PriceDif<0.5 AdvExp<6.95&AdvExp>6.45 hundred thousand bottles hundred thousand bottles