2. Using the cost equation from Requirement 1, calculate the total expected material handling cost for November if 350 moves are expected and 17,000 pounds of material will be moved (round final answer to the nearest dollar).

Expected material handling cost: $________

3. For the coming year, McCourt expects 3,940 moves involving a total of 204,000 pounds. Calculate the following:

Total expected fixed costs (round to the nearest dollar): $_____ Total material handling cost (add each component in the equation and then round to the nearest dollar): $_______

Multiple Regression In the McCourt Companry example, variables. For example, the weight of the items moved might be useful-particularly if forklifts and other heavy machinery are needed for moving parts and products from one location to another. In the case of two explanatory variables, the linear equation is expanded to include the additional variable percent of the variability in materials handling cost was explained by changes in the number of moves. As a result, McCourt may want to search for additional explanatory Xi Number of moves Number of pounds moved With three variables Y, X X2 a minim m or three points is needed to compute the parameters F Vz, and V-Seeing the points becomes difficult because they must be plotted in three dimensions. Using the s atter lot method or the high-low method is not practical. However, the extension or the method of least squares is straightforward It is relatively simple to develop a set of equations that provides values for F V1, and V2 that yields the best fitting equation whenever least squares is used to fit an equation ivolving two or more independent variables, the method is called multiple regression. The computations required for multiple regressions are far more complex than in simple (one independent variable) regression and any practical application of multiple regression requires use of regression software. The reliability measures are basically the same for multiple regressions as they were for a regression involving a single variable. Applying the Concepts The stalf of controller of McCourt Company added the variable "pounds moved to the ten-morth data set: Month Materials Handling Cost Number of Moves $5,600 090 780 8,000 1,990 Pounds Moved 12,000 15,000 7,800 29,000 125 175 600 200 300 250 400 100 600 23,000 17,000 25,000 6,000 22,400 2,000 1. Using the data on material handling, use regression software such as Microsoft Excel to complete the missing data in the table below (round regression parameters to the nearest cent and other answers to three decimal McCourt Company SUMMARY OUTPUT Multiple R R Square Adjusted R Square Standard Error 0.999 119.600 ANOVA Regression 2 37,768,070.16 18,884,035 1,320.168 9.50629E-10 100,129.84 14,304.26 9 37,868,200.00 Multiple Regression In the McCourt Companry example, variables. For example, the weight of the items moved might be useful-particularly if forklifts and other heavy machinery are needed for moving parts and products from one location to another. In the case of two explanatory variables, the linear equation is expanded to include the additional variable percent of the variability in materials handling cost was explained by changes in the number of moves. As a result, McCourt may want to search for additional explanatory Xi Number of moves Number of pounds moved With three variables Y, X X2 a minim m or three points is needed to compute the parameters F Vz, and V-Seeing the points becomes difficult because they must be plotted in three dimensions. Using the s atter lot method or the high-low method is not practical. However, the extension or the method of least squares is straightforward It is relatively simple to develop a set of equations that provides values for F V1, and V2 that yields the best fitting equation whenever least squares is used to fit an equation ivolving two or more independent variables, the method is called multiple regression. The computations required for multiple regressions are far more complex than in simple (one independent variable) regression and any practical application of multiple regression requires use of regression software. The reliability measures are basically the same for multiple regressions as they were for a regression involving a single variable. Applying the Concepts The stalf of controller of McCourt Company added the variable "pounds moved to the ten-morth data set: Month Materials Handling Cost Number of Moves $5,600 090 780 8,000 1,990 Pounds Moved 12,000 15,000 7,800 29,000 125 175 600 200 300 250 400 100 600 23,000 17,000 25,000 6,000 22,400 2,000 1. Using the data on material handling, use regression software such as Microsoft Excel to complete the missing data in the table below (round regression parameters to the nearest cent and other answers to three decimal McCourt Company SUMMARY OUTPUT Multiple R R Square Adjusted R Square Standard Error 0.999 119.600 ANOVA Regression 2 37,768,070.16 18,884,035 1,320.168 9.50629E-10 100,129.84 14,304.26 9 37,868,200.00