ACCOUNTING 306 COMPUTER PROJECT # 4 MULTIPLE REGRESSION ANALYSIS PROJECT A4 USING THE DATA BASE ATTACHED: 1) USE THE REGRESSION TOOL TO DETERMINE A REGRESSION EQUATION USING THE FOLLOWING TWO INDEPENDENT VARIABLES 1) "UNITS PRODUCED" AND 2) "NUMBER OF PRODUCTION BATCHES" USING MANUFACTURING OVERHEAD AS THE DEPENDENT VARIABLE. 2) DISPLAY THE EQUATION OF THAT LINE AND ALSO THE R-SQUARED ON THAT REGRESSION LINE. 3) HOW WOULD YOU ASSESS THE QUALITY OF THE RELATIONSHIP IN QUESTION # 2 BASED ON THE VALUE OF R-SQUARED USING MULTIPLE REGRESSION ANALYSIS? 4) GOING BACK TO PROJECT #1, SIMPLE REGRESSION ANALYSIS, HOW WOULD YOU ASSESS THE FORECASTING ABILITY OF MULTIPLE REGRESSION ANALYSIS AS COMPARED TO SIMPLE REGRESSION ANALYSIS (BASED ON PROJECT# 1), BASED ON THE COMPUTION OF R-SQUARED? anestrow Queens Lamps Inc specializes in manufacturing custom designed lamps. It is a low volume manufacturer. Its cost data for four years is as follows. Sales Price Per Unit: $ 400.00 Variable Selling and General Expenses per unit Monthly Fixed Selling and General Expenses $ $ 12.00 2,000 Number of Production Batches Observation Number 1 2 3 8 4 4 5 7 10 5 5 11 6 7 8 9 10 5 3 6 4 11 12 13 14 15 16 Month Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Units Year Produced 20X1 121 20X1 103 20X1 82 20X1 123 20X1 95 20X1 100 20X1 125 20X1 68 20X1 130 20X1 80 20X1 124 20X1 128 20X2 121 20X2 71 20X2 122 20X2 35 20X2 116 20X2 44 20X2 71 20X2 57 20X2 56 20X2 73 20x2 128 20X2 114 Machine Hours 1,557 1,259 970 1,631 1,235 1,391 1,479 955 1,808 988 1,483 1,597 1,715 951 1,507 473 1,493 578 886 771 692 940 1,498 1,615 Direct Material Direct Labor Cost Cost 3,703 4,646 3,059 4,408 2,411 3,674 3,653 4,723 2,850 4,028 2,970 4,280 3,750 5,750 2,060 2,530 3,822 4,992 2,448 3,520 3,683 4,613 3,802 5,530 3,630 4,453 2,173 3,039 3,587 1,050 1,330 3,480 4,083 1,294 2,006 2,087 2,698 1,727 2,440 1,697 2,419 2,146 3,066 3,802 5,171 3,420 4,697 Manufacturing Overhead 10,991 9,724 9,830 11,006 10,413 10,403 11,307 9,716 10,310 9,622 10,237 11,120 10,311 10,103 10,777 9,822 10,527 9,331 10,697 9,767 10,241 9,695 10,746 10,790 10 5 7 7 10 4,197 4 17 18 8 11 6 19 20 21 22 23 24 10 5 6 9 ACCOUNTING 306 COMPUTER PROJECT # 4 MULTIPLE REGRESSION ANALYSIS PROJECT A4 USING THE DATA BASE ATTACHED: 1) USE THE REGRESSION TOOL TO DETERMINE A REGRESSION EQUATION USING THE FOLLOWING TWO INDEPENDENT VARIABLES 1) "UNITS PRODUCED" AND 2) "NUMBER OF PRODUCTION BATCHES" USING MANUFACTURING OVERHEAD AS THE DEPENDENT VARIABLE. 2) DISPLAY THE EQUATION OF THAT LINE AND ALSO THE R-SQUARED ON THAT REGRESSION LINE. 3) HOW WOULD YOU ASSESS THE QUALITY OF THE RELATIONSHIP IN QUESTION # 2 BASED ON THE VALUE OF R-SQUARED USING MULTIPLE REGRESSION ANALYSIS? 4) GOING BACK TO PROJECT #1, SIMPLE REGRESSION ANALYSIS, HOW WOULD YOU ASSESS THE FORECASTING ABILITY OF MULTIPLE REGRESSION ANALYSIS AS COMPARED TO SIMPLE REGRESSION ANALYSIS (BASED ON PROJECT# 1), BASED ON THE COMPUTION OF R-SQUARED? anestrow Queens Lamps Inc specializes in manufacturing custom designed lamps. It is a low volume manufacturer. Its cost data for four years is as follows. Sales Price Per Unit: $ 400.00 Variable Selling and General Expenses per unit Monthly Fixed Selling and General Expenses $ $ 12.00 2,000 Number of Production Batches Observation Number 1 2 3 8 4 4 5 7 10 5 5 11 6 7 8 9 10 5 3 6 4 11 12 13 14 15 16 Month Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Units Year Produced 20X1 121 20X1 103 20X1 82 20X1 123 20X1 95 20X1 100 20X1 125 20X1 68 20X1 130 20X1 80 20X1 124 20X1 128 20X2 121 20X2 71 20X2 122 20X2 35 20X2 116 20X2 44 20X2 71 20X2 57 20X2 56 20X2 73 20x2 128 20X2 114 Machine Hours 1,557 1,259 970 1,631 1,235 1,391 1,479 955 1,808 988 1,483 1,597 1,715 951 1,507 473 1,493 578 886 771 692 940 1,498 1,615 Direct Material Direct Labor Cost Cost 3,703 4,646 3,059 4,408 2,411 3,674 3,653 4,723 2,850 4,028 2,970 4,280 3,750 5,750 2,060 2,530 3,822 4,992 2,448 3,520 3,683 4,613 3,802 5,530 3,630 4,453 2,173 3,039 3,587 1,050 1,330 3,480 4,083 1,294 2,006 2,087 2,698 1,727 2,440 1,697 2,419 2,146 3,066 3,802 5,171 3,420 4,697 Manufacturing Overhead 10,991 9,724 9,830 11,006 10,413 10,403 11,307 9,716 10,310 9,622 10,237 11,120 10,311 10,103 10,777 9,822 10,527 9,331 10,697 9,767 10,241 9,695 10,746 10,790 10 5 7 7 10 4,197 4 17 18 8 11 6 19 20 21 22 23 24 10 5 6 9