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Homework – Problem #2 2. Ethics: Manipulating Data to Establish a Budget. Healthy Bar, Inc., produces...
Homework – Problem #2
2. Ethics: Manipulating Data to Establish a Budget.
Healthy Bar, Inc., produces energy bars for sports enthusiasts. The company’s fiscal year ends on December 31. The production manager, Jim Wallace, is establishing a cost budget for the production department for each month of this coming quarter (January through March). At the end of March, Jim will be evaluated based on his ability to meet the budget for the three months ending March 31. In fact, Jim will receive a significant bonus if actual costs are below budgeted costs for the quarter. The production budget is typically established based on data from the last 18 months. These data are as follows:
|
Reporting Period (Month) |
Total Overhead Costs |
Total Machine Hours |
|
July |
$686,000 |
3,390 |
|
August |
700,000 |
3,441 |
|
September |
652,000 |
2,443 |
|
October |
715,000 |
3,730 |
|
November |
645,000 |
2,433 |
|
December |
665,700 |
2,680 |
|
January |
676,500 |
2,935 |
|
February |
701,000 |
3,641 |
|
March |
614,000 |
2,202 |
|
April |
627,000 |
2,231 |
|
May |
642,000 |
2,242 |
|
June |
692,000 |
3,498 |
|
July |
711,000 |
3,585 |
|
August |
725,000 |
2,541 |
|
September |
691,200 |
3,893 |
|
October |
757,600 |
2,893 |
|
November |
670,900 |
2,522 |
|
December |
701,100 |
2,699 |
You are the accountant who assists Jim in preparing an estimate of production costs for the next three months. You intend to use regression analysis to estimate costs, as was done in the past. Jim expects that 3,100 machine hours will be used in January, 3,650 machine hours in February, and 2,850 machine hours in March.
Jim approaches you and asks that you add $100,000 to production costs for each of the past 18 months before running the regression analysis. As he puts it, “After all, management always takes my proposed budgets and reduces them by about 10 percent. This is my way of leveling the playing field!”
Required:
A. Use Excel to perform regression analysis using the historical data provided.
- Submit a printout of the results. Explain.
- Use the regression output to develop the cost equation Y = f + vX by filling in the dollar amounts for f and v. Explain procedure and results in detail.
- Calculate estimated production costs for January, February, and March. Also provide a total for three months. Explain procedure and results in detail.
B. Use Excel to perform regression analysis after adding $100,000 to production costs for each of the past 18 months, as Jim requested.
- Submit a printout of the results. Explain procedure and results in detail and compare with #
- Use the regression output to develop the cost equation Y = f + vX by filling in the dollar amounts for f and v. Explain procedure and results in detail and compare with #1
- Calculate estimated production costs for January, February, and March. Also provide a total for the three months. Explain procedure and results in detail and Compare with #1
C. Why did Jim ask you to add $100,000 to production costs for each of the past 18 months? Explain
D. How should you handle Jim’s request? Explain
Solutions
Expert Solution
A)
| Reporting Period (Month) | Total Overhead Costs (y) | Total Machine Hours (x) | xy($) | x^2 | y^2 |
| July | $686,000 | 3,390 | 2,325,540,000.00 | 11,492,100 | $470,596,000,000 |
| August | 700,000 | 3,441 | 2,408,700,000.00 | 11,840,481 | $490,000,000,000 |
| September | 652,000 | 2,443 | 1,592,836,000.00 | 5,968,249 | $425,104,000,000 |
| October | 715,000 | 3,730 | 2,666,950,000.00 | 13,912,900 | $511,225,000,000 |
| November | 645,000 | 2,433 | 1,569,285,000.00 | 5,919,489 | $416,025,000,000 |
| December | 665,700 | 2,680 | 1,784,076,000.00 | 7,182,400 | $443,156,490,000 |
| January | 676,500 | 2,935 | 1,985,527,500.00 | 8,614,225 | $457,652,250,000 |
| February | 701,000 | 3,641 | 2,552,341,000.00 | 13,256,881 | $491,401,000,000 |
| March | 614,000 | 2,202 | 1,352,028,000.00 | 4,848,804 | $376,996,000,000 |
| April | 627,000 | 2,231 | 1,398,837,000.00 | 4,977,361 | $393,129,000,000 |
| May | 642,000 | 2,242 | 1,439,364,000.00 | 5,026,564 | $412,164,000,000 |
| June | 692,000 | 3,498 | 2,420,616,000.00 | 12,236,004 | $478,864,000,000 |
| July | 711,000 | 3,585 | 2,548,935,000.00 | 12,852,225 | $505,521,000,000 |
| August | 725,000 | 2,541 | 1,842,225,000.00 | 6,456,681 | $525,625,000,000 |
| September | 691,200 | 3,893 | 2,690,841,600.00 | 15,155,449 | $477,757,440,000 |
| October | 757,600 | 2,893 | 2,191,736,800.00 | 8,369,449 | $573,957,760,000 |
| November | 670,900 | 2,522 | 1,692,009,800.00 | 6,360,484 | $450,106,810,000 |
| December | 701,100 | 2,699 | 1,892,268,900.00 | 7,284,601 | $491,541,210,000 |
| SUM(Ʃ) | 12,273,000 | 52,999 | 36,354,117,600 | 161,754,347 | 8,390,821,960,000 |
| y | x | xy($) | x^2 | y^2 | |
| 569,505.30 | |||||
| 38.15 | |||||
| Linear equation | y=f+vx | Unit Variable Cost (v) = | (Σy)(Σx2) − (Σxy) | 569,505.30 | |
| y | Total overhead cost | nΣx2 − (Σx)2 | |||
| f | Fixed cost' | Total Fixed Cost (f) = | Σxy − (Σx)(Σy) | ||
| v | variable cost | nΣx2 − (Σx)2 | 38.15 | ||
| x | hours | ||||
| y= | 569505.3+38.15x | ||||
| Using the above equation- | |||||
| Reporting Period (Month) | Total Overhead Costs (y) | Total Machine Hours (x) | |||
| Jan | 687770.30 | 3,100.00 | 569595.30+38.15(3100) | ||
| Feb' | 708752.80 | 3,650.00 | 569595.30+38.15(3650) | ||
| Mar' | 678232.80 | 2,850.00 | 569595.30+38.15(2850) |
B) Similarly if $100000 is added
| Reporting Period (Month) | Total Overhead Costs (y) | Total Machine Hours (x) | xy($) | x^2 | y^2 |
| July | $786,000 | 3,390 | 2,664,540,000.00 | 11,492,100 | $617,796,000,000 |
| August | 800,000 | 3,441 | 2,752,800,000.00 | 11,840,481 | $640,000,000,000 |
| September | 752,000 | 2,443 | 1,837,136,000.00 | 5,968,249 | $565,504,000,000 |
| October | 815,000 | 3,730 | 3,039,950,000.00 | 13,912,900 | $664,225,000,000 |
| November | 745,000 | 2,433 | 1,812,585,000.00 | 5,919,489 | $555,025,000,000 |
| December | 765,700 | 2,680 | 2,052,076,000.00 | 7,182,400 | $586,296,490,000 |
| January | 776,500 | 2,935 | 2,279,027,500.00 | 8,614,225 | $602,952,250,000 |
| February | 801,000 | 3,641 | 2,916,441,000.00 | 13,256,881 | $641,601,000,000 |
| March | 714,000 | 2,202 | 1,572,228,000.00 | 4,848,804 | $509,796,000,000 |
| April | 727,000 | 2,231 | 1,621,937,000.00 | 4,977,361 | $528,529,000,000 |
| May | 742,000 | 2,242 | 1,663,564,000.00 | 5,026,564 | $550,564,000,000 |
| June | 792,000 | 3,498 | 2,770,416,000.00 | 12,236,004 | $627,264,000,000 |
| July | 811,000 | 3,585 | 2,907,435,000.00 | 12,852,225 | $657,721,000,000 |
| August | 825,000 | 2,541 | 2,096,325,000.00 | 6,456,681 | $680,625,000,000 |
| September | 791,200 | 3,893 | 3,080,141,600.00 | 15,155,449 | $625,997,440,000 |
| October | 857,600 | 2,893 | 2,481,036,800.00 | 8,369,449 | $735,477,760,000 |
| November | 770,900 |
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