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 Zpicture Excel Data Flle. For each sales period, let y= the demand for the large size bottle of Fresh (in hundreds of thousands of bottles) in the sales period (Demand) x1 = the price (in dollars) of Fresh as offered by Enterprise Industries in the sales period x2= the average industry price (in dollars) of cospetitors' similar detergents in the sales period x3= Enterprise Industries' advertising expenditure (in hundreds of thousands of dollars) to promote Fresh in the sales period (AdvExp) x4= the difference betieen the averase 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 The JMP Output of a Regression Tree for the Fresh Detergent Demand Data 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.) The above Image and tables show the JMP outputs of a regression tree analysis of the Fresh demand data, where the response yarlable 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.). 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 Zpicture Excel Data Flle. For each sales period, let y= the demand for the large size bottle of Fresh (in hundreds of thousands of bottles) in the sales period (Demand) x1 = the price (in dollars) of Fresh as offered by Enterprise Industries in the sales period x2= the average industry price (in dollars) of cospetitors' similar detergents in the sales period x3= Enterprise Industries' advertising expenditure (in hundreds of thousands of dollars) to promote Fresh in the sales period (AdvExp) x4= the difference betieen the averase 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 The JMP Output of a Regression Tree for the Fresh Detergent Demand Data 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.) The above Image and tables show the JMP outputs of a regression tree analysis of the Fresh demand data, where the response yarlable 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.)
