Advanced Cost and Managerial Accounting
MAF 700 Advanced Cost and Managerial Accounting Case 4 Cost Estimation Due Date May 21st, 2014 Sultan Ltd is a Construction Company specialized in roads and bridges’ construction. The
Company has accumulated data over the years for the projects that it had completed. Mr. Jalal, the general manager, has been reviewing the company’s annual report about the bidding success
rate. He was wondering about the possibility of using available data to improve the bidding process and its outcome. One member of the board suggested looking at the relationship between
engineer’s estimate of the number of work days to complete a project and its estimated cost. Another member suggested the use of correlation between estimated project cost and the
awarded value of the contract. A third member suggested the use of regression analysis where all possible variables related to the estimation of a project costs could to be considered. The
general manager called upon Mrs. Sara, the cost accountant, and assigned her the task of collecting all relevant available data and making the suggested analyses to estimate project costs. She
collected thirty five observations as on the next pages about the following items: – Number of estimated work days to complete a project – Estimate construction costs – Awarded contract
values (contract prices) – Number of bidders – Ratio of successful bids Mrs. Sara also prepared the following simple and multiple regression equations. Y = a + ß1 X1 + e Y = a + ß1 X1 + ß2 X2 + ß3
X3 + ß4 X4 + e Y = Estimated construction costs X1 = Number of work days Contract cost X2 = Awarded contract values X3 = Number of bidders. X4 = Ratio of successful bids. Required: (using a
statistical package such as SPSS) 1. Prepare a correlation matrix among the above variables. What does the matrix tell you? 2. Prepare a table that shows the results of the simple regression and
another that shows the results of the multiple regression analysis. What do these results tell you? 3. Which analysis is more suitable for the general manager’s purpose? Explain why.
1
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35
Estimated cost (000) 85,000 70,000 110,000 90,000 130,000 160,000 160,000 280,000 130,000 320,000 310,000 305,000 180,000 170,000 160,000 110,000 150,000 180,000 175,000 180,000 200,000
110,000 150,000 180,000 170,000 190,000 220,000 110,000 345,000 305,000 190,000 200,000 105,000 185,000 195,000
Work days 250 300 210 65 100 110 120 200 105 340 345 340 140 150 290 110 120 130 140 160 200 110 115 120 170 260 200 110 310 315 210 130 110 100 155
Contract value (000) 100,000 120,000 150,000 80,000 180,000 190,000 200,000 350,000 180,000 380,000 360,000 370,000 200,000 250,000 300,000 160,000 210,000 230,000 250,000 270,000 260,000
180,000 220,000 230,000 250,000 260,000 270,000 180,000 450,000 340,000 250,000 290,000 160,000 215,000 235,000
No of bidders 5 6 7 8 4 5 6 7 8 10 11 10 10 9 7 8 6 15 12 11 13 15 16 14 16 14 11 8 9 10 11 12 13 12 10
Ratio of success 40 50 60 50 70 70 80 60 40 50 30 60 50 30 40 30 30 40 50 30 20 20 25 60 50 40 70 30 20 40 30 50 30 40
2
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MAF 700 Advanced Cost and Managerial Accounting Case 4 Cost Estimation Due Date May 21st, 2014 Sultan Ltd is a Construction Company specialized in roads and bridges’ construction. The
Company has accumulated data over the years for the projects that it had completed. Mr. Jalal, the general manager, has been reviewing the company’s annual report about the bidding success
rate. He was wondering about the possibility of using available data to improve the bidding process and its outcome. One member of the board suggested looking at the relationship between
engineer’s estimate of the number of work days to complete a project and its estimated cost. Another member suggested the use of correlation between estimated project cost and the
awarded value of the contract. A third member suggested the use of regression analysis where all possible variables related to the estimation of a project costs could to be considered. The
general manager called upon Mrs. Sara, the cost accountant, and assigned her the task of collecting all relevant available data and making the suggested analyses to estimate project costs. She
collected thirty five observations as on the next pages about the following items: – Number of estimated work days to complete a project – Estimate construction costs – Awarded contract
values (contract prices) – Number of bidders – Ratio of successful bids Mrs. Sara also prepared the following simple and multiple regression equations. Y = a + ß1 X1 + e Y = a + ß1 X1 + ß2 X2 + ß3
X3 + ß4 X4 + e Y = Estimated construction costs X1 = Number of work days Contract cost X2 = Awarded contract values X3 = Number of bidders. X4 = Ratio of successful bids. Required: (using a
statistical package such as SPSS) 1. Prepare a correlation matrix among the above variables. What does the matrix tell you? 2. Prepare a table that shows the results of the simple regression and
another that shows the results of the multiple regression analysis. What do these results tell you? 3. Which analysis is more suitable for the general manager’s purpose? Explain why.
1
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35
Estimated cost (000) 85,000 70,000 110,000 90,000 130,000 160,000 160,000 280,000 130,000 320,000 310,000 305,000 180,000 170,000 160,000 110,000 150,000 180,000 175,000 180,000 200,000
110,000 150,000 180,000 170,000 190,000 220,000 110,000 345,000 305,000 190,000 200,000 105,000 185,000 195,000
Work days 250 300 210 65 100 110 120 200 105 340 345 340 140 150 290 110 120 130 140 160 200 110 115 120 170 260 200 110 310 315 210 130 110 100 155
Contract value (000) 100,000 120,000 150,000 80,000 180,000 190,000 200,000 350,000 180,000 380,000 360,000 370,000 200,000 250,000 300,000 160,000 210,000 230,000 250,000 270,000 260,000
180,000 220,000 230,000 250,000 260,000 270,000 180,000 450,000 340,000 250,000 290,000 160,000 215,000 235,000
No of bidders 5 6 7 8 4 5 6 7 8 10 11 10 10 9 7 8 6 15 12 11 13 15 16 14 16 14 11 8 9 10 11 12 13 12 10
Ratio of success 40 50 60 50 70 70 80 60 40 50 30 60 50 30 40 30 30 40 50 30 20 20 25 60 50 40 70 30 20 40 30 50 30 40
2
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