Full Test Bank Ch5 Cost Estimation - Cost Accounting 6e Complete Test Bank by William Lanen. DOCX document preview.
Fundamentals of Cost Accounting, 6e (Lanen)
Chapter 5 Cost Estimation
1) Cost behavior is the most important characteristic for managerial decision making.
2) In general, accounting records accumulate cost information according to its behavior (i.e., variable and fixed).
3) In general, cost behavior results are likely to differ between the engineering method and the account analysis method.
4) The engineering method of determining cost behavior is particularly useful for new activities or products.
5) One advantage of the engineering method is that it does not require data from prior periods to estimate cost behavior.
6) One advantage of the account analysis method for estimating cost behavior is that it includes actual work conditions.
7) The account analysis method is more subjective than other cost estimation methods because it relies heavily on the personal judgment and experience of accountants.
8) In general, the account analysis method focuses on the underlying relationship between cost and activities from the previous period.
9) The relevant range represents those activity levels for which valid cost relationships have been observed.
10) A scattergraph is useful for identifying outliers/irrelevant data points.
11) One disadvantage of the high-low method is the highest and lowest points may not be representative of normal operating activities.
12) One advantage that regression techniques have over other cost estimation methods is it generates information that can be used to determine how well the estimated cost equation will predict future costs.
13) Because outliers are extreme data points, they can be included in the regression analysis and not significantly affect the results.
14) In general, the use of multiple independent variables increases the proportion of the variation in the dependent variable explained by the cost equation.
15) One way to control the effects of a nonlinear relation between total costs and volume is to reduce the relevant range.
16) The linear cost estimate tends to understate the slope of the cost line in ranges close to capacity.
17) Cost estimates using regression analysis are always more accurate and dependable than cost estimates using the scattergraph methods.
18) A basic assumption of most cost estimation methods is cost behavior patterns are linear within the relevant range.
19) The quality of the cost equation depends on collecting appropriate data.
20) Different cost estimations methods may produce different cost equations, even when using the same set of data.
21) Which of the following statements is(are) true regarding cost behaviors?
(A) In general, accounting records accumulate cost information according to its behavior.
(B) Cost behaviors are the most important consideration in managerial decision making.
A) Only A is true.
B) Only B is true.
C) Both of these are true.
D) Neither of these is true.
22) Which of the following is the difference between variable costs and fixed costs? (CMA adapted)
A) Variable costs per unit fluctuate and fixed costs per unit remain constant.
B) Variable costs per unit are fixed over the relevant range and fixed costs per unit are variable.
C) Total variable costs are variable over the relevant range and fixed in the long term, while fixed costs never change.
D) Variable costs per unit change in varying increments, while fixed costs per unit change in equal units.
23) A cost driver is defined as: (CMA adapted)
A) the largest cost in a manufacturing process.
B) a fixed cost that cannot be avoided.
C) the significant factor in developing a new product.
D) a causal factor that increases the total cost of a cost objective.
24) Which cost estimation method does not use the company's cost information as its primary source of information about the relationship between total costs and activity levels?
A) Scattergraph.
B) High-low.
C) Account analysis.
D) Engineering estimates.
25) A manager is trying to estimate the manufacturing costs of a new product. The company makes several other products that utilize some of the same manufacturing procedures as the new product. Which cost estimation method would be the best method to determine the total cost of manufacturing the new product?
A) Engineering estimates.
B) Regression analysis.
C) Account analysis.
D) Scattergraph.
26) Engineering cost estimates are usually based on operating conditions that are considered:
A) optimal.
B) practical.
C) attainable.
D) historical.
27) Identifying the relation between the activity and the costs is a key step in which of the following cost estimation methods?
A) Scattergraph.
B) High-low method.
C) Account analysis.
D) Linear regression.
28) Which of the following costs would most likely be classified as variable, assuming the account analysis method is used to determine cost behaviors?
A) Indirect materials.
B) Supervisory salaries.
C) Equipment maintenance.
D) Building occupancy costs.
29) Given the following information, compute the total number of units for the period:
|
|
|
|
Direct labor hours |
| 12,000 |
|
Direct labor cost | $ | 2.70 | per hour |
Direct materials cost | $ | 75 | per unit |
Total manufacturing cost | $ | 132,600 |
|
Fixed overhead cost | $ | 36,000 |
|
Variable overhead cost |
| 50 | % of total labor cost |
A) 360.
B) 432.
C) 640.
D) 840.
30) In the cost equation TC = F + VX, "X" is best described as the:
A) costs that do not vary with changes in the activity level.
B) costs that do vary with changes in the activity level.
C) total cost estimate at a particular activity level.
D) activity level used to estimate the total cost.
31) In the cost equation TC = F + VX, "V" is best described as the:
A) total costs that do not vary with changes in the activity level.
B) intercept of the cost equation.
C) slope of the cost equation.
D) activity level used to estimate the dependent variable.
32) Ballard Company incurred a total cost of $8,600 to produce 400 units of pulp. Each unit of pulp required five (5) direct labor hours to complete. What is the total fixed cost if the variable cost was $1.50 per direct labor hour?
A) $1,700.
B) $3,000.
C) $5,600.
D) $8,000.
33) The term "relevant range," as used in cost accounting, means the range over which:
A) relevant costs are incurred.
B) costs may fluctuate.
C) cost relationships are valid.
D) cost data is available.
34) Which of the following cost estimation methods is based on two cost observations?
A) Engineering approach.
B) High-low method.
C) Account analysis.
D) Linear regression.
35) A disadvantage of the high-low method of cost analysis is that it:
A) typically results in a totally inaccurate cost formula.
B) is too time consuming to apply.
C) uses only two data points, which may not be representative of normal conditions.
D) relies totally on the judgment of the person performing the cost analysis.
36) Obtaining regression estimates for cost estimation requires establishing the existence of a logical relation between activities and the cost to be estimated. Which of the following is not used to refer to these activities?
A) independent variables.
B) predictors.
C) dependent variables.
D) X terms.
37) Obtaining regression estimates for cost estimation requires establishing the existence of a logical relation between activities and the cost to be estimated. Which of the following is not used to refer to the cost to be estimated?
A) left-hand side (LHS).
B) dependent variable.
C) Y term.
D) independent variable.
38) Which of the following is not true of regression techniques for estimating costs?
A) They permit the inclusion of more than one predictor.
B) They typically use the highest and lowest activity points to estimate the relation between cost and activity.
C) They help develop estimates that have a broader base than those based on a few select points.
D) They are designed to generate a line that best fits a set of data points.
39) The correlation coefficient is:
A) the range of values over which the probability may be estimated based upon the regression equation results.
B) the proportion of the total variance in the dependent variable explained by the independent variable.
C) the measure of variability of the actual observations from the predicting (forecasting) equation line.
D) the relative degree that changes in one variable can be used to estimate changes in another variable.
40) Brewsky's is a chain of micro-breweries. Managers are interested in the costs of the stores and believe that the costs can be explained in large part by the number of customers patronizing the stores. Monthly data regarding customer visits and costs for the preceding year for one of the stores have been entered into the regression analysis and the analysis is as follows:
|
|
|
|
Average monthly customer visits |
| 1,462 |
|
Average monthly total costs | $ | 4,629 |
|
Regression Results |
|
|
|
Intercept | $ | 1,496 |
|
b coefficient | $ | 2.08 |
|
R2 |
| 0.86814 |
|
In a regression equation expressed as y = a + bx, how is the letter b best described? (CMA adapted)
A) An estimate of the probability of return customers.
B) The fixed costs per customer visit.
C) The estimate of the cost for an additional customer visit.
D) The proximity of the data points to the regression line.
41) Brewsky's is a chain of micro-breweries. Managers are interested in the costs of the stores and believe that the costs can be explained in large part by the number of customers patronizing the stores. Monthly data regarding customer visits and costs for the preceding year for one of the stores have been entered into the regression analysis and the analysis is as follows:
|
|
| |||
Average monthly customer visits |
| 1,462 |
| ||
Average monthly total costs | $ | 4,629 |
| ||
Regression Results |
|
|
| ||
Intercept | $ | 1,496 |
| ||
b coefficient | $ | 2.08 |
| ||
R2 |
| 0.86814 |
|
In a regression equation expressed as y = a + bx, how is the letter y best described? (CMA adapted)
A) An estimate of the total customers for the month.
B) The observed store cost for a given month.
C) The estimate of the number of new customer visits for the month.
D) The proximity of the data points to the regression line.
42) Brewsky's is a chain of micro-breweries. Managers are interested in the costs of the stores and believe that the costs can be explained in large part by the number of customers patronizing the stores. Monthly data regarding customer visits and costs for the preceding year for one of the stores have been entered into the regression analysis and the analysis is as follows:
|
|
| |||
Average monthly customer visits |
| 1,462 |
| ||
Average monthly total costs | $ | 4,629 |
| ||
Regression Results |
|
|
| ||
Intercept | $ | 1,496 |
| ||
b coefficient | $ | 2.08 |
| ||
R2 |
| 0.86814 |
|
In a regression equation expressed as y = a + bx, how is the letter x best described? (CMA adapted)
A) Fixed costs per each customer-visit.
B) The observed store costs for a given month.
C) The estimate of the number of new customer visits for the month.
D) The observed customer visits for a given month.
43) Brewsky's is a chain of micro-breweries. Managers are interested in the costs of the stores and believe that the costs can be explained in large part by the number of customers patronizing the stores. Monthly data regarding customer visits and costs for the preceding year for one of the stores have been entered into the regression analysis and the analysis is as follows:
|
|
| |||
Average monthly customer visits |
| 1,462 |
| ||
Average monthly total costs | $ | 4,629 |
| ||
Regression Results |
|
|
| ||
Intercept | $ | 1,496 |
| ||
b coefficient | $ | 2.08 |
| ||
R2 |
| 0.86814 |
|
Based on the data derived from the regression analysis, what are the estimated costs for 1,600 customer visits in a month? (CMA adapted)
A) $6,125.
B) $4,629.
C) $3,328.
D) $4,824.
44) Brewsky's is a chain of micro-breweries. Managers are interested in the costs of the stores and believe that the costs can be explained in large part by the number of customers patronizing the stores. Monthly data regarding customer visits and costs for the preceding year for one of the stores have been entered into the regression analysis and the analysis is as follows:
|
|
| |||
Average monthly customer visits |
| 1,462 |
| ||
Average monthly total costs | $ | 4,629 |
| ||
Regression Results |
|
|
| ||
Intercept | $ | 1,496 |
| ||
b coefficient | $ | 2.08 |
| ||
R2 |
| 0.86814 |
|
What is the percent of the total variance that can be explained by the regression equation? (CMA adapted)
A) 86.8%
B) 31.6%
C) 97.7%
D) 71.9%
45) The Macon Company uses the high-low method to determine its cost equation. The following information was gathered for the past year:
| Machine Hours |
| Direct Labor Costs |
| |||||||
Busiest month (June) |
| 14,000 |
|
| $ | 200,000 |
|
| |||
Slowest month (December) |
| 6,000 |
|
| $ | 120,000 |
|
|
What are the direct labor costs per machine hour?
A) $20.00.
B) $16.00.
C) $14.29.
D) $10.00.
46) The Macon Company uses the high-low method to determine its cost equation. The following information was gathered for the past year:
| Machine Hours |
| Direct Labor Costs |
| |||||||
Busiest month (June) |
| 14,000 |
|
| $ | 200,000 |
|
| |||
Slowest month (December) |
| 6,000 |
|
| $ | 120,000 |
|
|
If Macon expects to use 10,000 machine hours next month, what are the estimated direct labor costs?
A) $160,000.
B) $180,000.
C) $175,000.
D) $150,000.
47) Fromme's Frocks has the following machine hours and production costs for the last six months of last year:
Month | Machine Hours |
| Production Cost | |||||||
July |
| 15,000 |
|
| $ | 12,075 |
| |||
August |
| 13,500 |
|
|
| 10,800 |
| |||
September |
| 11,500 |
|
|
| 9,580 |
| |||
October |
| 15,500 |
|
|
| 12,080 |
| |||
November |
| 14,800 |
|
|
| 11,692 |
| |||
December |
| 12,100 |
|
|
| 9,922 |
|
If Fromme expects to incur 14,000 machine hours in January, what will be the estimated total production cost using the high-low method?
A) $8,750.00.
B) $11,142.50.
C) $22,400.00.
D) $10,889.10.
48) The controller of Fortnight Co. has requested a quick estimate of the manufacturing supplies needed for the Cleveland Plant for the month of July, when production is expected to be 470,000 units to meet the ending inventory requirements and sales of 475,000 units. Fortnight Co.'s budget analyst has the following actual data for the last three months.
Month | Production in Units |
| Manufacturing Supplies | ||||||
March |
| 450,000 |
|
| $ | 723,060 |
| ||
April |
| 540,000 |
|
|
| 853,560 |
| ||
May |
| 480,000 |
|
|
| 766,560 |
|
Using the high-low method to develop a cost estimating equation, the total estimated cost of needed manufacturing supplies for July would be: (CMA adapted)
A) $681,500.
B) $688,750.
C) $749,180.
D) $752,060.
49) The Crater Manufacturing Company recorded overhead costs of $14,182 at an activity level of 4,200 machine hours and $8,748 at 2,300 machine hours. The records also indicated that overhead of $9,730 was incurred at 2,600 machine hours. What is the variable cost per machine hour using the high-low method to estimate the cost equation?
A) $2.78.
B) $2.86.
C) $3.10.
D) $3.38.
50) The Missou Manufacturing Company recorded overhead costs of $14,182 at an activity level of 4,200 machine hours and $8,748 at 2,300 machine hours. What is the total estimated cost for 2,600 machine hours using the high-low method to estimate the cost equation?
A) $9,730.
B) $9,606.
C) $9,106.
D) $8,788.
51) The cost accountants at the Barkley Company regressed total overhead costs and direct labor hours for the past 30-months and reported the following results:
|
|
| ||
Slope | $ | 41.27 |
| |
Intercept | $ | 596.36 |
| |
Correlation Coefficient |
| 0.934 |
|
What is the estimated overhead cost if 225 direct labor hours are expected to be used in the upcoming period? (rounded to the nearest whole dollar)
A) $10,534.
B) $9,882.
C) $9,230.
D) $8,617.
52) The McGraw Company is accumulating data to be used in preparing its annual profit plan for the coming year. The cost behavior pattern of the maintenance costs must be determined. The accounting staff has suggested that linear regression be employed to derive an equation in the form of y = a + bx for maintenance costs. Data regarding the maintenance hours and costs for last year and the results of the regression analysis are as follows: (CMA adapted)
What would be the cost equation if regression analysis is used?
A) Maintenance Costs = $7.2884 + ($684.65 × Hours of Activity).
B) Maintenance Costs = $684.65 + ($49.515 × Hours of Activity).
C) Maintenance Costs = $684.65 + ($7.2884 × Hours of Activity).
D) Maintenance Costs = $34.469 + ($0.99724 × Hours of Activity).
53) The McGraw Company is accumulating data to be used in preparing its annual profit plan for the coming year. The cost behavior pattern of the maintenance costs must be determined. The accounting staff has suggested that linear regression be employed to derive an equation in the form of y = a + bx for maintenance costs. Data regarding the maintenance hours and costs for last year and the results of the regression analysis are as follows: (CMA adapted)
Based upon the data derived from the regression analysis, 420 maintenance hours in a month would mean the maintenance costs would be budgeted at: (rounded to the nearest whole dollar)
A) $3,797.
B) $3,780.
C) $3,746.
D) $3,600.
54) The McGraw Company is accumulating data to be used in preparing its annual profit plan for the coming year. The cost behavior pattern of the maintenance costs must be determined. The accounting staff has suggested that linear regression be employed to derive an equation in the form of y = a + bx for maintenance costs. Data regarding the maintenance hours and costs for last year and the results of the regression analysis are as follows: (CMA adapted)
What is the variable cost per hour using the high-low method to estimate the cost equation?
A) $9.00.
B) $7.50.
C) $0.1333.
D) $0.1111.
55) The McGraw Company is accumulating data to be used in preparing its annual profit plan for the coming year. The cost behavior pattern of the maintenance costs must be determined. The accounting staff has suggested that linear regression be employed to derive an equation in the form of y = a + bx for maintenance costs. Data regarding the maintenance hours and costs for last year and the results of the regression analysis are as follows: (CMA adapted)
What is the fixed cost per month using the high-low method to estimate the cost equation?
A) $570.
B) $600.
C) $1,140.
D) $2,250.
56) The McGraw Company is accumulating data to be used in preparing its annual profit plan for the coming year. The cost behavior pattern of the maintenance costs must be determined. The accounting staff has suggested that linear regression be employed to derive an equation in the form of y = a + bx for maintenance costs. Data regarding the maintenance hours and costs for last year and the results of the regression analysis are as follows: (CMA adapted)
Using the high-low method to estimate cost behavior, 420 maintenance hours in a month would mean the maintenance costs would be budgeted at:
A) $3,150.
B) $3,600.
C) $3,720.
D) $3,780.
57) The McGraw Company is accumulating data to be used in preparing its annual profit plan for the coming year. The cost behavior pattern of the maintenance costs must be determined. The accounting staff has suggested that linear regression be employed to derive an equation in the form of y = a + bx for maintenance costs. Data regarding the maintenance hours and costs for last year and the results of the regression analysis are as follows: (CMA adapted)
What would be the cost equation if the high-low method is used?
A) Maintenance Costs = $9.00 × Hours of Activity.
B) Maintenance Costs = 3,600 + (400 × Hours of Activity).
C) Maintenance Costs = $570 + ($7.50 × Hours of Activity).
D) Maintenance Costs = $34.469 + ($0.99724 × Hours of Activity).
58) The College of Business at Northeast College is accumulating data as a first step in the preparation of next year's budget development. One cost that is being looked at closely is administrative costs as a function of student credit hours. Data on administrative costs and credit hours for the past thirteen months are shown below:
Month | Administrative Costs |
| Credit Hours | ||||||
July |
| $ | 129,301 |
| 250 |
| |||
August |
|
| 82,613 |
| 115 |
| |||
September |
|
| 225,580 |
| 1,392 |
| |||
October |
|
| 216,394 |
| 1,000 |
| |||
November |
|
| 258,263 |
| 1,309 |
| |||
December |
|
| 184,449 |
| 1,112 |
| |||
January |
|
| 219,137 |
| 1,339 |
| |||
February |
|
| 245,000 |
| 1,373 |
| |||
March |
|
| 209,462 |
| 1,064 |
| |||
April |
|
| 191,925 |
| 1,123 |
| |||
May |
|
| 249,978 |
| 1,360 |
| |||
June |
|
| 170,418 |
| 420 |
| |||
July |
|
| 128,167 |
| 315 |
| |||
Total |
| $ | 2,510,687 |
| 12,172 |
| |||
Average |
| $ | 193,130 |
| 936 |
|
The controller's office has analyzed the data and has given you the results from the regression analysis:
SUMMARY OUTPUT | |
Regression Statistics | |
Multiple R | 0.9317157 |
R Square | 0.868094147 |
Adjusted R Square | 0.856102705 |
Standard Error | 20,134.92395 |
Observations | 13 |
ANOVA |
|
|
|
|
|
| df | SS | MS | F | Significance F |
Regression | 1 | 29,349,143,514 | 29,349,143,514 | 72.3928117 | 3.61909E-06 |
Residual | 11 | 4,459,566,787 | 405,415,162.4 |
|
|
Total | 12 | 33,808,710,301 |
|
|
|
| Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% | Lower 95.0% | Upper 95.0% |
Intercept | 96,647.02398 | 12,641.66539 | 7.64511803 | 1.00291E-05 | 68,822.90608 | 124,471.1419 | 68,822.90608 | 124,471.1419 |
X Variable 1 | 103.0607697 | 12.11283103 | 8.508396541 | 3.61909E-06 | 76.40060833 | 129.720931 | 76.40060833 | 129.720931 |
If the controller uses the high-low method to estimate costs, the variable cost per credit hour is:
A) $82.33.
B) $103.56.
C) $111.96.
D) $201.22.
59) The College of Business at Northeast College is accumulating data as a first step in the preparation of next year's budget development. One cost that is being looked at closely is administrative costs as a function of student credit hours. Data on administrative costs and credit hours for the past thirteen months are shown below:
Month | Administrative Costs |
| Credit Hours | ||||||
July |
| $ | 129,301 |
| 250 |
| |||
August |
|
| 82,613 |
| 115 |
| |||
September |
|
| 225,580 |
| 1,392 |
| |||
October |
|
| 216,394 |
| 1,000 |
| |||
November |
|
| 258,263 |
| 1,309 |
| |||
December |
|
| 184,449 |
| 1,112 |
| |||
January |
|
| 219,137 |
| 1,339 |
| |||
February |
|
| 245,000 |
| 1,373 |
| |||
March |
|
| 209,462 |
| 1,064 |
| |||
April |
|
| 191,925 |
| 1,123 |
| |||
May |
|
| 249,978 |
| 1,360 |
| |||
June |
|
| 170,418 |
| 420 |
| |||
July |
|
| 128,167 |
| 315 |
| |||
Total |
| $ | 2,510,687 |
| 12,172 |
| |||
Average |
| $ | 193,130 |
| 936 |
|
The controller's office has analyzed the data and has given you the results from the regression analysis:
SUMMARY OUTPUT | |
Regression Statistics | |
Multiple R | 0.9317157 |
R Square | 0.868094147 |
Adjusted R Square | 0.856102705 |
Standard Error | 20,134.92395 |
Observations | 13 |
ANOVA |
|
|
|
|
|
| df | SS | MS | F | Significance F |
Regression | 1 | 29,349,143,514 | 29,349,143,514 | 72.3928117 | 3.61909E-06 |
Residual | 11 | 4,459,566,787 | 405,415,162.4 |
|
|
Total | 12 | 33,808,710,301 |
|
|
|
| Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% | Lower 95.0% | Upper 95.0% |
Intercept | 96,647.02398 | 12,641.66539 | 7.64511803 | 1.00291E-05 | 68,822.90608 | 124,471.1419 | 68,822.90608 | 124,471.1419 |
X Variable 1 | 103.0607697 | 12.11283103 | 8.508396541 | 3.61909E-06 | 76.40060833 | 129.720931 | 76.40060833 | 129.720931 |
If the controller uses the high-low method to estimate costs, the fixed cost portion of the cost equation for administrative costs is:
A) $198,808.00.
B) $69,731.68.
C) $96,409.42.
D) $19,943.58.
60) The College of Business at Northeast College is accumulating data as a first step in the preparation of next year's budget development. One cost that is being looked at closely is administrative costs as a function of student credit hours. Data on administrative costs and credit hours for the past thirteen months are shown below:
Month | Administrative Costs |
| Credit Hours | ||||||
July |
| $ | 129,301 |
| 250 |
| |||
August |
|
| 82,613 |
| 115 |
| |||
September |
|
| 225,580 |
| 1,392 |
| |||
October |
|
| 216,394 |
| 1,000 |
| |||
November |
|
| 258,263 |
| 1,309 |
| |||
December |
|
| 184,449 |
| 1,112 |
| |||
January |
|
| 219,137 |
| 1,339 |
| |||
February |
|
| 245,000 |
| 1,373 |
| |||
March |
|
| 209,462 |
| 1,064 |
| |||
April |
|
| 191,925 |
| 1,123 |
| |||
May |
|
| 249,978 |
| 1,360 |
| |||
June |
|
| 170,418 |
| 420 |
| |||
July |
|
| 128,167 |
| 315 |
| |||
Total |
| $ | 2,510,687 |
| 12,172 |
| |||
Average |
| $ | 193,130 |
| 936 |
|
The controller's office has analyzed the data and has given you the results from the regression analysis:
SUMMARY OUTPUT | |
Regression Statistics | |
Multiple R | 0.9317157 |
R Square | 0.868094147 |
Adjusted R Square | 0.856102705 |
Standard Error | 20,134.92395 |
Observations | 13 |
ANOVA |
|
|
|
|
|
| df | SS | MS | F | Significance F |
Regression | 1 | 29,349,143,514 | 29,349,143,514 | 72.3928117 | 3.61909E-06 |
Residual | 11 | 4,459,566,787 | 405,415,162.4 |
|
|
Total | 12 | 33,808,710,301 |
|
|
|
| Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% | Lower 95.0% | Upper 95.0% |
Intercept | 96,647.02398 | 12,641.66539 | 7.64511803 | 1.00291E-05 | 68,822.90608 | 124,471.1419 | 68,822.90608 | 124,471.1419 |
X Variable 1 | 103.0607697 | 12.11283103 | 8.508396541 | 3.61909E-06 | 76.40060833 | 129.720931 | 76.40060833 | 129.720931 |
If the controller uses the high-low method to estimate costs, the cost equation for administrative costs is
A) Administrative Costs = $96,409.42 + $103.56 × Credit-hours.
B) Administrative Costs = $69,731.68 + $111.96 × Credit-hours.
C) Administrative Costs = $201.21 × Credit-hours.
D) Administrative Costs = $198,808.
61) The College of Business at Northeast College is accumulating data as a first step in the preparation of next year's budget development. One cost that is being looked at closely is administrative costs as a function of student credit hours. Data on administrative costs and credit hours for the past thirteen months are shown below:
Month | Administrative Costs |
| Credit Hours | ||||||
July |
| $ | 129,301 |
| 250 |
| |||
August |
|
| 82,613 |
| 115 |
| |||
September |
|
| 225,580 |
| 1,392 |
| |||
October |
|
| 216,394 |
| 1,000 |
| |||
November |
|
| 258,263 |
| 1,309 |
| |||
December |
|
| 184,449 |
| 1,112 |
| |||
January |
|
| 219,137 |
| 1,339 |
| |||
February |
|
| 245,000 |
| 1,373 |
| |||
March |
|
| 209,462 |
| 1,064 |
| |||
April |
|
| 191,925 |
| 1,123 |
| |||
May |
|
| 249,978 |
| 1,360 |
| |||
June |
|
| 170,418 |
| 420 |
| |||
July |
|
| 128,167 |
| 315 |
| |||
Total |
| $ | 2,510,687 |
| 12,172 |
| |||
Average |
| $ | 193,130 |
| 936 |
|
The controller's office has analyzed the data and has given you the results from the regression analysis:
SUMMARY OUTPUT | |
Regression Statistics | |
Multiple R | 0.9317157 |
R Square | 0.868094147 |
Adjusted R Square | 0.856102705 |
Standard Error | 20,134.92395 |
Observations | 13 |
ANOVA |
|
|
|
|
|
| df | SS | MS | F | Significance F |
Regression | 1 | 29,349,143,514 | 29,349,143,514 | 72.3928117 | 3.61909E-06 |
Residual | 11 | 4,459,566,787 | 405,415,162.4 |
|
|
Total | 12 | 33,808,710,301 |
|
|
|
| Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% | Lower 95.0% | Upper 95.0% |
Intercept | 96,647.02398 | 12,641.66539 | 7.64511803 | 1.00291E-05 | 68,822.90608 | 124,471.1419 | 68,822.90608 | 124,471.1419 |
X Variable 1 | 103.0607697 | 12.11283103 | 8.508396541 | 3.61909E-06 | 76.40060833 | 129.720931 | 76.40060833 | 129.720931 |
Based on the results of the high-low analysis, the estimate of administrative costs in a month with 1,000 credit hours would be: (rounded to the nearest whole dollar)
A) $181,692.
B) $199,969.
C) $201,210.
D) $198,808.
62) The College of Business at Northeast College is accumulating data as a first step in the preparation of next year's budget development. One cost that is being looked at closely is administrative costs as a function of student credit hours. Data on administrative costs and credit hours for the past thirteen months are shown below:
Month | Administrative Costs |
| Credit Hours | ||||||
July |
| $ | 129,301 |
| 250 |
| |||
August |
|
| 82,613 |
| 115 |
| |||
September |
|
| 225,580 |
| 1,392 |
| |||
October |
|
| 216,394 |
| 1,000 |
| |||
November |
|
| 258,263 |
| 1,309 |
| |||
December |
|
| 184,449 |
| 1,112 |
| |||
January |
|
| 219,137 |
| 1,339 |
| |||
February |
|
| 245,000 |
| 1,373 |
| |||
March |
|
| 209,462 |
| 1,064 |
| |||
April |
|
| 191,925 |
| 1,123 |
| |||
May |
|
| 249,978 |
| 1,360 |
| |||
June |
|
| 170,418 |
| 420 |
| |||
July |
|
| 128,167 |
| 315 |
| |||
Total |
| $ | 2,510,687 |
| 12,172 |
| |||
Average |
| $ | 193,130 |
| 936 |
|
The controller's office has analyzed the data and has given you the results from the regression analysis:
SUMMARY OUTPUT | |
Regression Statistics | |
Multiple R | 0.9317157 |
R Square | 0.868094147 |
Adjusted R Square | 0.856102705 |
Standard Error | 20,134.92395 |
Observations | 13 |
ANOVA |
|
|
|
|
|
| df | SS | MS | F | Significance F |
Regression | 1 | 29,349,143,514 | 29,349,143,514 | 72.3928117 | 3.61909E-06 |
Residual | 11 | 4,459,566,787 | 405,415,162.4 |
|
|
Total | 12 | 33,808,710,301 |
|
|
|
| Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% | Lower 95.0% | Upper 95.0% |
Intercept | 96,647.02398 | 12,641.66539 | 7.64511803 | 1.00291E-05 | 68,822.90608 | 124,471.1419 | 68,822.90608 | 124,471.1419 |
X Variable 1 | 103.0607697 | 12.11283103 | 8.508396541 | 3.61909E-06 | 76.40060833 | 129.720931 | 76.40060833 | 129.720931 |
If the controller uses regression analysis to estimate costs, the cost equation for administrative costs is:
A) Administrative Costs = $19,943.58 + ($13.00 × Credit hours).
B) Administrative Costs = $69,474.40 + ($114.30 × Credit hours).
C) Administrative Costs = $96,647.02 + ($103.06 × Credit hours).
D) Administrative Costs = $12,521.26 + ($11.99 × Credit hours).
63) The College of Business at Northeast College is accumulating data as a first step in the preparation of next year's budget development. One cost that is being looked at closely is administrative costs as a function of student credit hours. Data on administrative costs and credit hours for the past thirteen months are shown below:
Month | Administrative Costs |
| Credit Hours | ||||||
July |
| $ | 129,301 |
| 250 |
| |||
August |
|
| 82,613 |
| 115 |
| |||
September |
|
| 225,580 |
| 1,392 |
| |||
October |
|
| 216,394 |
| 1,000 |
| |||
November |
|
| 258,263 |
| 1,309 |
| |||
December |
|
| 184,449 |
| 1,112 |
| |||
January |
|
| 219,137 |
| 1,339 |
| |||
February |
|
| 245,000 |
| 1,373 |
| |||
March |
|
| 209,462 |
| 1,064 |
| |||
April |
|
| 191,925 |
| 1,123 |
| |||
May |
|
| 249,978 |
| 1,360 |
| |||
June |
|
| 170,418 |
| 420 |
| |||
July |
|
| 128,167 |
| 315 |
| |||
Total |
| $ | 2,510,687 |
| 12,172 |
| |||
Average |
| $ | 193,130 |
| 936 |
|
The controller's office has analyzed the data and has given you the results from the regression analysis:
SUMMARY OUTPUT | |
Regression Statistics | |
Multiple R | 0.9317157 |
R Square | 0.868094147 |
Adjusted R Square | 0.856102705 |
Standard Error | 20,134.92395 |
Observations | 13 |
ANOVA |
|
|
|
|
|
| df | SS | MS | F | Significance F |
Regression | 1 | 29,349,143,514 | 29,349,143,514 | 72.3928117 | 3.61909E-06 |
Residual | 11 | 4,459,566,787 | 405,415,162.4 |
|
|
Total | 12 | 33,808,710,301 |
|
|
|
| Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% | Lower 95.0% | Upper 95.0% |
Intercept | 96,647.02398 | 12,641.66539 | 7.64511803 | 1.00291E-05 | 68,822.90608 | 124,471.1419 | 68,822.90608 | 124,471.1419 |
X Variable 1 | 103.0607697 | 12.11283103 | 8.508396541 | 3.61909E-06 | 76.40060833 | 129.720931 | 76.40060833 | 129.720931 |
If the controller uses regression analysis to estimate costs, the estimate of the variable portion of administrative costs is:
A) Variable Costs = $8.63 × Credit hours.
B) Variable Costs = $0.87 × Credit hours.
C) Variable Costs = $103.06 × Credit hours.
D) Variable Costs = $11.99 × Credit hours.
64) The College of Business at Northeast College is accumulating data as a first step in the preparation of next year's budget development. One cost that is being looked at closely is administrative costs as a function of student credit hours. Data on administrative costs and credit hours for the past thirteen months are shown below:
Month | Administrative Costs |
| Credit Hours | ||||||
July |
| $ | 129,301 |
| 250 |
| |||
August |
|
| 82,613 |
| 115 |
| |||
September |
|
| 225,580 |
| 1,392 |
| |||
October |
|
| 216,394 |
| 1,000 |
| |||
November |
|
| 258,263 |
| 1,309 |
| |||
December |
|
| 184,449 |
| 1,112 |
| |||
January |
|
| 219,137 |
| 1,339 |
| |||
February |
|
| 245,000 |
| 1,373 |
| |||
March |
|
| 209,462 |
| 1,064 |
| |||
April |
|
| 191,925 |
| 1,123 |
| |||
May |
|
| 249,978 |
| 1,360 |
| |||
June |
|
| 170,418 |
| 420 |
| |||
July |
|
| 128,167 |
| 315 |
| |||
Total |
| $ | 2,510,687 |
| 12,172 |
| |||
Average |
| $ | 193,130 |
| 936 |
|
The controller's office has analyzed the data and has given you the results from the regression analysis:
SUMMARY OUTPUT | |
Regression Statistics | |
Multiple R | 0.9317157 |
R Square | 0.868094147 |
Adjusted R Square | 0.856102705 |
Standard Error | 20,134.92395 |
Observations | 13 |
ANOVA |
|
|
|
|
|
| df | SS | MS | F | Significance F |
Regression | 1 | 29,349,143,514 | 29,349,143,514 | 72.3928117 | 3.61909E-06 |
Residual | 11 | 4,459,566,787 | 405,415,162.4 |
|
|
Total | 12 | 33,808,710,301 |
|
|
|
| Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% | Lower 95.0% | Upper 95.0% |
Intercept | 96,647.02398 | 12,641.66539 | 7.64511803 | 1.00291E-05 | 68,822.90608 | 124,471.1419 | 68,822.90608 | 124,471.1419 |
X Variable 1 | 103.0607697 | 12.11283103 | 8.508396541 | 3.61909E-06 | 76.40060833 | 129.720931 | 76.40060833 | 129.720931 |
If the controller uses regression analysis to estimate costs, the estimate of the fixed portion of administrative costs is:
A) Fixed Cost = $103.56.
B) Fixed Cost = $12,521.26.
C) Fixed Cost = $19,943.58.
D) Fixed Cost = $96,647.02.
65) The College of Business at Northeast College is accumulating data as a first step in the preparation of next year's budget development. One cost that is being looked at closely is administrative costs as a function of student credit hours. Data on administrative costs and credit hours for the past thirteen months are shown below:
Month | Administrative Costs |
| Credit Hours | ||||||
July |
| $ | 129,301 |
| 250 |
| |||
August |
|
| 82,613 |
| 115 |
| |||
September |
|
| 225,580 |
| 1,392 |
| |||
October |
|
| 216,394 |
| 1,000 |
| |||
November |
|
| 258,263 |
| 1,309 |
| |||
December |
|
| 184,449 |
| 1,112 |
| |||
January |
|
| 219,137 |
| 1,339 |
| |||
February |
|
| 245,000 |
| 1,373 |
| |||
March |
|
| 209,462 |
| 1,064 |
| |||
April |
|
| 191,925 |
| 1,123 |
| |||
May |
|
| 249,978 |
| 1,360 |
| |||
June |
|
| 170,418 |
| 420 |
| |||
July |
|
| 128,167 |
| 315 |
| |||
Total |
| $ | 2,510,687 |
| 12,172 |
| |||
Average |
| $ | 193,130 |
| 936 |
|
The controller's office has analyzed the data and has given you the results from the regression analysis:
SUMMARY OUTPUT | |
Regression Statistics | |
Multiple R | 0.9317157 |
R Square | 0.868094147 |
Adjusted R Square | 0.856102705 |
Standard Error | 20,134.92395 |
Observations | 13 |
ANOVA |
|
|
|
|
|
| df | SS | MS | F | Significance F |
Regression | 1 | 29,349,143,514 | 29,349,143,514 | 72.3928117 | 3.61909E-06 |
Residual | 11 | 4,459,566,787 | 405,415,162.4 |
|
|
Total | 12 | 33,808,710,301 |
|
|
|
| Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% | Lower 95.0% | Upper 95.0% |
Intercept | 96,647.02398 | 12,641.66539 | 7.64511803 | 1.00291E-05 | 68,822.90608 | 124,471.1419 | 68,822.90608 | 124,471.1419 |
X Variable 1 | 103.0607697 | 12.11283103 | 8.508396541 | 3.61909E-06 | 76.40060833 | 129.720931 | 76.40060833 | 129.720931 |
Based on the results of the regression analysis, the estimate of administrative costs in a month with 1,000 credit hours would be: (rounded to the nearest whole dollar)
A) $198,808.
B) $201,000.
C) $199,707.
D) $96,409.
66) The College of Business at Northeast College is accumulating data as a first step in the preparation of next year's budget development. One cost that is being looked at closely is administrative costs as a function of student credit hours. Data on administrative costs and credit hours for the past thirteen months are shown below:
Month | Administrative Costs |
| Credit Hours | ||||||
July |
| $ | 129,301 |
| 250 |
| |||
August |
|
| 82,613 |
| 115 |
| |||
September |
|
| 225,580 |
| 1,392 |
| |||
October |
|
| 216,394 |
| 1,000 |
| |||
November |
|
| 258,263 |
| 1,309 |
| |||
December |
|
| 184,449 |
| 1,112 |
| |||
January |
|
| 219,137 |
| 1,339 |
| |||
February |
|
| 245,000 |
| 1,373 |
| |||
March |
|
| 209,462 |
| 1,064 |
| |||
April |
|
| 191,925 |
| 1,123 |
| |||
May |
|
| 249,978 |
| 1,360 |
| |||
June |
|
| 170,418 |
| 420 |
| |||
July |
|
| 128,167 |
| 315 |
| |||
Total |
| $ | 2,510,687 |
| 12,172 |
| |||
Average |
| $ | 193,130 |
| 936 |
|
The controller's office has analyzed the data and has given you the results from the regression analysis:
SUMMARY OUTPUT | |
Regression Statistics | |
Multiple R | 0.9317157 |
R Square | 0.868094147 |
Adjusted R Square | 0.856102705 |
Standard Error | 20,134.92395 |
Observations | 13 |
ANOVA |
|
|
|
|
|
| df | SS | MS | F | Significance F |
Regression | 1 | 29,349,143,514 | 29,349,143,514 | 72.3928117 | 3.61909E-06 |
Residual | 11 | 4,459,566,787 | 405,415,162.4 |
|
|
Total | 12 | 33,808,710,301 |
|
|
|
| Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% | Lower 95.0% | Upper 95.0% |
Intercept | 96,647.02398 | 12,641.66539 | 7.64511803 | 1.00291E-05 | 68,822.90608 | 124,471.1419 | 68,822.90608 | 124,471.1419 |
X Variable 1 | 103.0607697 | 12.11283103 | 8.508396541 | 3.61909E-06 | 76.40060833 | 129.720931 | 76.40060833 | 129.720931 |
The correlation coefficient (rounded to the 3rd decimal) for the regression equation for administrative costs is:
A) 0.932.
B) 0.868.
C) 0.856.
D) 0.966.
67) The College of Business at Northeast College is accumulating data as a first step in the preparation of next year's budget development. One cost that is being looked at closely is administrative costs as a function of student credit hours. Data on administrative costs and credit hours for the past thirteen months are shown below:
Month | Administrative Costs |
| Credit Hours | ||||||
July |
| $ | 129,301 |
| 250 |
| |||
August |
|
| 82,613 |
| 115 |
| |||
September |
|
| 225,580 |
| 1,392 |
| |||
October |
|
| 216,394 |
| 1,000 |
| |||
November |
|
| 258,263 |
| 1,309 |
| |||
December |
|
| 184,449 |
| 1,112 |
| |||
January |
|
| 219,137 |
| 1,339 |
| |||
February |
|
| 245,000 |
| 1,373 |
| |||
March |
|
| 209,462 |
| 1,064 |
| |||
April |
|
| 191,925 |
| 1,123 |
| |||
May |
|
| 249,978 |
| 1,360 |
| |||
June |
|
| 170,418 |
| 420 |
| |||
July |
|
| 128,167 |
| 315 |
| |||
Total |
| $ | 2,510,687 |
| 12,172 |
| |||
Average |
| $ | 193,130 |
| 936 |
|
The controller's office has analyzed the data and has given you the results from the regression analysis:
SUMMARY OUTPUT | |
Regression Statistics | |
Multiple R | 0.9317157 |
R Square | 0.868094147 |
Adjusted R Square | 0.856102705 |
Standard Error | 20,134.92395 |
Observations | 13 |
ANOVA |
|
|
|
|
|
| df | SS | MS | F | Significance F |
Regression | 1 | 29,349,143,514 | 29,349,143,514 | 72.3928117 | 3.61909E-06 |
Residual | 11 | 4,459,566,787 | 405,415,162.4 |
|
|
Total | 12 | 33,808,710,301 |
|
|
|
| Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% | Lower 95.0% | Upper 95.0% |
Intercept | 96,647.02398 | 12,641.66539 | 7.64511803 | 1.00291E-05 | 68,822.90608 | 124,471.1419 | 68,822.90608 | 124,471.1419 |
X Variable 1 | 103.0607697 | 12.11283103 | 8.508396541 | 3.61909E-06 | 76.40060833 | 129.720931 | 76.40060833 | 129.720931 |
The percent of the total variance that can be explained by the regression is:
A) 93.3%.
B) 86.8%.
C) 85.9%.
D) 96.6%.
68) The College of Business at Northeast College is accumulating data as a first step in the preparation of next year's budget development. One cost that is being looked at closely is administrative costs as a function of student credit hours. Data on administrative costs and credit hours for the past thirteen months are shown below:
Month | Administrative Costs |
| Credit Hours | ||||||
July |
| $ | 129,301 |
| 250 |
| |||
August |
|
| 82,613 |
| 115 |
| |||
September |
|
| 225,580 |
| 1,392 |
| |||
October |
|
| 216,394 |
| 1,000 |
| |||
November |
|
| 258,263 |
| 1,309 |
| |||
December |
|
| 184,449 |
| 1,112 |
| |||
January |
|
| 219,137 |
| 1,339 |
| |||
February |
|
| 245,000 |
| 1,373 |
| |||
March |
|
| 209,462 |
| 1,064 |
| |||
April |
|
| 191,925 |
| 1,123 |
| |||
May |
|
| 249,978 |
| 1,360 |
| |||
June |
|
| 170,418 |
| 420 |
| |||
July |
|
| 128,167 |
| 315 |
| |||
Total |
| $ | 2,510,687 |
| 12,172 |
| |||
Average |
| $ | 193,130 |
| 936 |
|
The controller's office has analyzed the data and has given you the results from the regression analysis:
SUMMARY OUTPUT | |
Regression Statistics | |
Multiple R | 0.9317157 |
R Square | 0.868094147 |
Adjusted R Square | 0.856102705 |
Standard Error | 20,134.92395 |
Observations | 13 |
ANOVA |
|
|
|
|
|
| df | SS | MS | F | Significance F |
Regression | 1 | 29,349,143,514 | 29,349,143,514 | 72.3928117 | 3.61909E-06 |
Residual | 11 | 4,459,566,787 | 405,415,162.4 |
|
|
Total | 12 | 33,808,710,301 |
|
|
|
| Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% | Lower 95.0% | Upper 95.0% |
Intercept | 96,647.02398 | 12,641.66539 | 7.64511803 | 1.00291E-05 | 68,822.90608 | 124,471.1419 | 68,822.90608 | 124,471.1419 |
X Variable 1 | 103.0607697 | 12.11283103 | 8.508396541 | 3.61909E-06 | 76.40060833 | 129.720931 | 76.40060833 | 129.720931 |
Based on the results of the regression analysis, the estimate of the variable portion of administrative costs in a month with 200 credit hours would be:
A) $198,808.
B) $20,612.
C) $117,121.
D) $40,242.
69) In determining cost behavior in business, the cost function is often expressed as Y = a + bX. Which one of the following cost estimation methods should not be used in estimating fixed and variable costs for the equation? (CMA adapted)
A) Scattergraph method.
B) Simple regression.
C) High and low point method.
D) Management analysis of data.
70) Which of the following may be used to estimate how inventory warehouse costs are affected by both the number of shipments and the weight of the material handled? (CPA adapted)
A) Economic order quantity analysis.
B) Probability analysis.
C) Correlation analysis.
D) Multiple regression analysis.
71) Thane Company is interested in establishing the relationship between electricity costs and machine hours. Data have been collected and a regression analysis prepared using Excel. The monthly data and the regression output follow:
Month | Machine Hours | Electricity Costs | ||
January | 2,500 | $ | 18,400 |
|
February | 2,900 |
| 21,000 |
|
March | 1,900 |
| 13,500 |
|
April | 3,100 |
| 23,000 |
|
May | 3,800 |
| 28,250 |
|
June | 3,300 |
| 22,000 |
|
July | 4,100 |
| 24,750 |
|
August | 3,500 |
| 22,750 |
|
September | 2,000 |
| 15,500 |
|
October | 3,700 |
| 26,000 |
|
November | 4,700 |
| 31,000 |
|
December | 4,200 |
| 27,750 |
|
Summary Output | |
Regression Statistics | |
Multiple R | 0.965 |
R Square | 0.932 |
Adjusted R2 | 0.925 |
Standard Error | 1,425.18 |
Observations | 12.00 |
| Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% |
Intercept | 3,726.88 | 1,682.82 | 2.21 | 0.05 | (22.69) | 7,476.45 |
Machine Hours | 5.77 | 0.49 | 11.7 | 0.00 | 4.67 | 6.87 |
If the controller uses the high-low method to estimate costs, the variable cost per machine hour is:
A) $6.25.
B) $6.90.
C) $5.77.
D) $11.70.
72) Thane Company is interested in establishing the relationship between electricity costs and machine hours. Data have been collected and a regression analysis prepared using Excel. The monthly data and the regression output follow:
Month | Machine Hours | Electricity Costs | ||
January | 2,500 | $ | 18,400 |
|
February | 2,900 |
| 21,000 |
|
March | 1,900 |
| 13,500 |
|
April | 3,100 |
| 23,000 |
|
May | 3,800 |
| 28,250 |
|
June | 3,300 |
| 22,000 |
|
July | 4,100 |
| 24,750 |
|
August | 3,500 |
| 22,750 |
|
September | 2,000 |
| 15,500 |
|
October | 3,700 |
| 26,000 |
|
November | 4,700 |
| 31,000 |
|
December | 4,200 |
| 27,750 |
|
Summary Output | |
Regression Statistics | |
Multiple R | 0.965 |
R Square | 0.932 |
Adjusted R2 | 0.925 |
Standard Error | 1,425.18 |
Observations | 12.00 |
| Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% |
Intercept | 3,726.88 | 1,682.82 | 2.21 | 0.05 | (22.69) | 7,476.45 |
Machine Hours | 5.77 | 0.49 | 11.7 | 0.00 | 4.67 | 6.87 |
If the controller uses the high-low method to estimate costs, the fixed cost portion of the cost equation for electricity costs is:
A) $3,726.88.
B) $1,425.18.
C) $1,625.00.
D) $22,825.00.
73) Thane Company is interested in establishing the relationship between electricity costs and machine hours. Data have been collected and a regression analysis prepared using Excel. The monthly data and the regression output follow:
Month | Machine Hours | Electricity Costs | ||
January | 2,500 | $ | 18,400 |
|
February | 2,900 |
| 21,000 |
|
March | 1,900 |
| 13,500 |
|
April | 3,100 |
| 23,000 |
|
May | 3,800 |
| 28,250 |
|
June | 3,300 |
| 22,000 |
|
July | 4,100 |
| 24,750 |
|
August | 3,500 |
| 22,750 |
|
September | 2,000 |
| 15,500 |
|
October | 3,700 |
| 26,000 |
|
November | 4,700 |
| 31,000 |
|
December | 4,200 |
| 27,750 |
|
Summary Output | |
Regression Statistics | |
Multiple R | 0.965 |
R Square | 0.932 |
Adjusted R2 | 0.925 |
Standard Error | 1,425.18 |
Observations | 12.00 |
| Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% |
Intercept | 3,726.88 | 1,682.82 | 2.21 | 0.05 | (22.69) | 7,476.45 |
Machine Hours | 5.77 | 0.49 | 11.7 | 0.00 | 4.67 | 6.87 |
If the controller uses the high-low method to estimate costs, the cost equation for electricity costs is:
A) Electricity Costs = $3,726.88 + ($5.77 × Machine-hours).
B) Electricity Costs = $1,625.00 + ($6.25 × Machine-hours).
C) Electricity Costs = $6.90 × Machine-hours.
D) Electricity Costs = $22,825.
74) Thane Company is interested in establishing the relationship between electricity costs and machine hours. Data have been collected and a regression analysis prepared using Excel. The monthly data and the regression output follow:
Month | Machine Hours | Electricity Costs | ||
January | 2,500 | $ | 18,400 |
|
February | 2,900 |
| 21,000 |
|
March | 1,900 |
| 13,500 |
|
April | 3,100 |
| 23,000 |
|
May | 3,800 |
| 28,250 |
|
June | 3,300 |
| 22,000 |
|
July | 4,100 |
| 24,750 |
|
August | 3,500 |
| 22,750 |
|
September | 2,000 |
| 15,500 |
|
October | 3,700 |
| 26,000 |
|
November | 4,700 |
| 31,000 |
|
December | 4,200 |
| 27,750 |
|
Summary Output | |
Regression Statistics | |
Multiple R | 0.965 |
R Square | 0.932 |
Adjusted R2 | 0.925 |
Standard Error | 1,425.18 |
Observations | 12.00 |
| Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% |
Intercept | 3,726.88 | 1,682.82 | 2.21 | 0.05 | (22.69) | 7,476.45 |
Machine Hours | 5.77 | 0.49 | 11.7 | 0.00 | 4.67 | 6.87 |
Based on the results of the high-low analysis, the estimate of electricity costs in a month with 2,200 machine hours would be:
A) $15,375.
B) $22,825.
C) $15,180.
D) $16,427.
75) Thane Company is interested in establishing the relationship between electricity costs and machine hours. Data have been collected and a regression analysis prepared using Excel. The monthly data and the regression output follow:
Month | Machine Hours | Electricity Costs | ||
January | 2,500 | $ | 18,400 |
|
February | 2,900 |
| 21,000 |
|
March | 1,900 |
| 13,500 |
|
April | 3,100 |
| 23,000 |
|
May | 3,800 |
| 28,250 |
|
June | 3,300 |
| 22,000 |
|
July | 4,100 |
| 24,750 |
|
August | 3,500 |
| 22,750 |
|
September | 2,000 |
| 15,500 |
|
October | 3,700 |
| 26,000 |
|
November | 4,700 |
| 31,000 |
|
December | 4,200 |
| 27,750 |
|
Summary Output | |
Regression Statistics | |
Multiple R | 0.965 |
R Square | 0.932 |
Adjusted R2 | 0.925 |
Standard Error | 1,425.18 |
Observations | 12.00 |
| Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% |
Intercept | 3,726.88 | 1,682.82 | 2.21 | 0.05 | (22.69) | 7,476.45 |
Machine Hours | 5.77 | 0.49 | 11.7 | 0.00 | 4.67 | 6.87 |
If the controller uses regression analysis to estimate costs, the cost equation for electricity costs is:
A) Electricity Costs = $1,425.18 + ($12.00 × Machine hours).
B) Electricity Costs = $3,726.88 + ($1,682.82 × Machine hours).
C) Electricity Costs = $1,682.82 + ($0.49 × Machine hours).
D) Electricity Costs = $3,726.88 + ($5.77 × Machine hours).
76) Thane Company is interested in establishing the relationship between electricity costs and machine hours. Data have been collected and a regression analysis prepared using Excel. The monthly data and the regression output follow:
Month | Machine Hours | Electricity Costs | ||
January | 2,500 | $ | 18,400 |
|
February | 2,900 |
| 21,000 |
|
March | 1,900 |
| 13,500 |
|
April | 3,100 |
| 23,000 |
|
May | 3,800 |
| 28,250 |
|
June | 3,300 |
| 22,000 |
|
July | 4,100 |
| 24,750 |
|
August | 3,500 |
| 22,750 |
|
September | 2,000 |
| 15,500 |
|
October | 3,700 |
| 26,000 |
|
November | 4,700 |
| 31,000 |
|
December | 4,200 |
| 27,750 |
|
Summary Output | |
Regression Statistics | |
Multiple R | 0.965 |
R Square | 0.932 |
Adjusted R2 | 0.925 |
Standard Error | 1,425.18 |
Observations | 12.00 |
| Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% |
Intercept | 3,726.88 | 1,682.82 | 2.21 | 0.05 | (22.69) | 7,476.45 |
Machine Hours | 5.77 | 0.49 | 11.7 | 0.00 | 4.67 | 6.87 |
If the controller uses regression analysis to estimate costs, the estimate of the variable portion of electricity costs is:
A) Electricity Costs = $11.70 × Machine hours.
B) Electricity Costs = $0.93 × Machine hours.
C) Electricity Costs = $5.77 × Machine hours.
D) Electricity Costs = $0.49 × Machine hours.
77) Thane Company is interested in establishing the relationship between electricity costs and machine hours. Data have been collected and a regression analysis prepared using Excel. The monthly data and the regression output follow:
Month | Machine Hours | Electricity Costs | ||
January | 2,500 | $ | 18,400 |
|
February | 2,900 |
| 21,000 |
|
March | 1,900 |
| 13,500 |
|
April | 3,100 |
| 23,000 |
|
May | 3,800 |
| 28,250 |
|
June | 3,300 |
| 22,000 |
|
July | 4,100 |
| 24,750 |
|
August | 3,500 |
| 22,750 |
|
September | 2,000 |
| 15,500 |
|
October | 3,700 |
| 26,000 |
|
November | 4,700 |
| 31,000 |
|
December | 4,200 |
| 27,750 |
|
Summary Output | |
Regression Statistics | |
Multiple R | 0.965 |
R Square | 0.932 |
Adjusted R2 | 0.925 |
Standard Error | 1,425.18 |
Observations | 12.00 |
| Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% |
Intercept | 3,726.88 | 1,682.82 | 2.21 | 0.05 | (22.69) | 7,476.45 |
Machine Hours | 5.77 | 0.49 | 11.7 | 0.00 | 4.67 | 6.87 |
If the controller uses regression analysis to estimate costs, the estimate of the fixed portion of electricity costs is:
A) Fixed Cost = $5.77.
B) Fixed Cost = $1,682.82.
C) Fixed Cost = $1,425.18.
D) Fixed Cost = $3,726.88
78) Thane Company is interested in establishing the relationship between electricity costs and machine hours. Data have been collected and a regression analysis prepared using Excel. The monthly data and the regression output follow:
Month | Machine Hours | Electricity Costs | ||
January | 2,500 | $ | 18,400 |
|
February | 2,900 |
| 21,000 |
|
March | 1,900 |
| 13,500 |
|
April | 3,100 |
| 23,000 |
|
May | 3,800 |
| 28,250 |
|
June | 3,300 |
| 22,000 |
|
July | 4,100 |
| 24,750 |
|
August | 3,500 |
| 22,750 |
|
September | 2,000 |
| 15,500 |
|
October | 3,700 |
| 26,000 |
|
November | 4,700 |
| 31,000 |
|
December | 4,200 |
| 27,750 |
|
Summary Output | |
Regression Statistics | |
Multiple R | 0.965 |
R Square | 0.932 |
Adjusted R2 | 0.925 |
Standard Error | 1,425.18 |
Observations | 12.00 |
| Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% |
Intercept | 3,726.88 | 1,682.82 | 2.21 | 0.05 | (22.69) | 7,476.45 |
Machine Hours | 5.77 | 0.49 | 11.7 | 0.00 | 4.67 | 6.87 |
Based on the results of the regression analysis, the estimate of electricity costs in a month with 2,200 machine hours would be: (rounded to the nearest whole dollar)
A) $3,727.
B) $16,421.
C) $15,180.
D) $22,825.
79) Thane Company is interested in establishing the relationship between electricity costs and machine hours. Data have been collected and a regression analysis prepared using Excel. The monthly data and the regression output follow:
Month | Machine Hours | Electricity Costs | ||
January | 2,500 | $ | 18,400 |
|
February | 2,900 |
| 21,000 |
|
March | 1,900 |
| 13,500 |
|
April | 3,100 |
| 23,000 |
|
May | 3,800 |
| 28,250 |
|
June | 3,300 |
| 22,000 |
|
July | 4,100 |
| 24,750 |
|
August | 3,500 |
| 22,750 |
|
September | 2,000 |
| 15,500 |
|
October | 3,700 |
| 26,000 |
|
November | 4,700 |
| 31,000 |
|
December | 4,200 |
| 27,750 |
|
Summary Output | |
Regression Statistics | |
Multiple R | 0.965 |
R Square | 0.932 |
Adjusted R2 | 0.925 |
Standard Error | 1,425.18 |
Observations | 12.00 |
| Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% |
Intercept | 3,726.88 | 1,682.82 | 2.21 | 0.05 | (22.69) | 7,476.45 |
Machine Hours | 5.77 | 0.49 | 11.7 | 0.00 | 4.67 | 6.87 |
The correlation coefficient for the regression equation for electricity costs is:
A) 0.965.
B) 0.932.
C) 0.925.
D) 0.982.
80) Thane Company is interested in establishing the relationship between electricity costs and machine hours. Data have been collected and a regression analysis prepared using Excel. The monthly data and the regression output follow:
Month | Machine Hours | Electricity Costs | ||
January | 2,500 | $ | 18,400 |
|
February | 2,900 |
| 21,000 |
|
March | 1,900 |
| 13,500 |
|
April | 3,100 |
| 23,000 |
|
May | 3,800 |
| 28,250 |
|
June | 3,300 |
| 22,000 |
|
July | 4,100 |
| 24,750 |
|
August | 3,500 |
| 22,750 |
|
September | 2,000 |
| 15,500 |
|
October | 3,700 |
| 26,000 |
|
November | 4,700 |
| 31,000 |
|
December | 4,200 |
| 27,750 |
|
Summary Output | |
Regression Statistics | |
Multiple R | 0.965 |
R Square | 0.932 |
Adjusted R2 | 0.925 |
Standard Error | 1,425.18 |
Observations | 12.00 |
| Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% |
Intercept | 3,726.88 | 1,682.82 | 2.21 | 0.05 | (22.69) | 7,476.45 |
Machine Hours | 5.77 | 0.49 | 11.7 | 0.00 | 4.67 | 6.87 |
The percent of the total variance that can be explained by the regression is:
A) 96.5%.
B) 93.2%.
C) 92.5%.
D) 98.2%.
81) Balcom Enterprises is planning to introduce a new product that will sell for $110 per unit. Manufacturing cost estimates for 20,000 units for the first year of production are:
∙ Direct materials $1,000,000.
∙ Direct labor $720,000 (based on $18 per hour × 40,000 hours).
Although overhead has not be estimated for the new product, monthly data for Balcom's total production for the last two years has been analyzed using simple linear regression. The analysis results are as follows:
|
| |||
Dependent variable | Factory overhead costs | |||
Independent variable | Direct labor hours | |||
Intercept | $ | 120,000 |
| |
Coefficient on independent variable | $ | 5.00 |
| |
Coefficient of correlation |
| 0.911 |
| |
R2 |
| 0.814 |
|
Based on this information, what percentage of the variation in overhead costs is explained by the independent variable?
A) 24%
B) 81.4%
C) 91.1 %
D) 9.7%
82) Balcom Enterprises is planning to introduce a new product that will sell for $110 per unit. Manufacturing cost estimates for 20,000 units for the first year of production are:
∙ Direct materials $1,000,000.
∙ Direct labor $720,000 (based on $18 per hour × 40,000 hours).
Although overhead has not be estimated for the new product, monthly data for Balcom's total production for the last two years has been analyzed using simple linear regression. The analysis results are as follows:
|
| |||
Dependent variable | Factory overhead costs | |||
Independent variable | Direct labor hours | |||
Intercept | $ | 120,000 |
| |
Coefficient on independent variable | $ | 5.00 |
| |
Coefficient of correlation |
| 0.911 |
| |
R2 |
| 0.814 |
|
Based on this information, what is the total overhead cost for an estimated activity level of 45,000 direct labor-hours?
A) $125,000
B) $345,000
C) $600,000
D) $225,000
83) Balcom Enterprises is planning to introduce a new product that will sell for $110 per unit. Manufacturing cost estimates for 20,000 units for the first year of production are:
∙ Direct materials $1,000,000.
∙ Direct labor $720,000 (based on $18 per hour × 40,000 hours).
Although overhead has not be estimated for the new product, monthly data for Balcom's total production for the last two years has been analyzed using simple linear regression. The analysis results are as follows:
|
| |||
Dependent variable | Factory overhead costs | |||
Independent variable | Direct labor hours | |||
Intercept | $ | 120,000 |
| |
Coefficient on independent variable | $ | 5.00 |
| |
Coefficient of correlation |
| 0.911 |
| |
R2 |
| 0.814 |
|
Based on this information, how much is the variable manufacturing cost per unit, using the variable overhead estimated by the regression (assuming that direct materials and direct labor are variable costs)?
A) $78
B) $91
C) $96
D) $71
84) Balcom Enterprises is planning to introduce a new product that will sell for $110 per unit. Manufacturing cost estimates for 20,000 units for the first year of production are:
∙ Direct materials $1,000,000.
∙ Direct labor $720,000 (based on $18 per hour × 40,000 hours).
Although overhead has not be estimated for the new product, monthly data for Balcom's total production for the last two years has been analyzed using simple linear regression. The analysis results are as follows:
|
| |||
Dependent variable | Factory overhead costs | |||
Independent variable | Direct labor hours | |||
Intercept | $ | 120,000 |
| |
Coefficient on independent variable | $ | 5.00 |
| |
Coefficient of correlation |
| 0.911 |
| |
R2 |
| 0.814 |
|
Based on this information, what is the expected contribution margin per unit to be earned during the first year on 20,000 units of the new product? (Assume that all marketing and administrative costs are fixed.)
A) $14
B) $13
C) $99
D) $32
85) Given actual amounts of a semi-variable cost for various levels of output, the method that will always give the most reliable measure of the fixed and variable components is the:
A) high-low method.
B) linear regression method.
C) scattergraph method.
D) account analysis method.
86) Which of the following statements regarding regression analysis is (are) true?
(A) One way to control the effects of a nonlinear relationship between total costs and activity is reduce the relevant range.
(B) The linear cost estimate tends to understate the slope of the cost line in ranges close to capacity.
A) Only A is true.
B) Only B is true.
C) Both of these are true.
D) Neither of these is true.
87) Which of the following is a common assumption of cost estimation?
A) Cost behavior depends on many cost drivers.
B) Cost behavior patterns are nonlinear outside of the relevant range.
C) Cost behavior patterns are linear within the relevant range.
D) Costs are curvilinear.
88) Which of the following is not a data problem an analyst must watch for when estimating cost behavior?
A) Missing data.
B) Outliers.
C) Allocated costs.
D) Depreciable assets.
89) Which of the following is not a data problem an analyst must watch for when estimating cost behavior?
A) Non-numeric data.
B) Inflation.
C) Discretionary costs.
D) Mismatched time periods.
90) In the learning curve equation Y = aXb, the Y term represents:
A) the labor time required to produce the first unit.
B) the labor time required to produce the last single unit.
C) the cumulative number of units.
D) the index of learning.
91) In the learning curve equation Y = aXb, the X term represents:
A) the labor time required to produce the first unit.
B) the labor time required to produce the last single unit.
C) the cumulative number of units.
D) the index of learning.
92) In the learning curve equation Y = aXb, the "a" term represents:
A) the labor time required to produce the first unit.
B) the labor time required to produce the last single unit.
C) the cumulative number of units.
D) the index of learning.
93) In the learning curve equation Y = aXb, the "b" term represents:
A) the labor time required to produce the first unit.
B) the labor time required to produce the last single unit.
C) the cumulative number of units.
D) the index of learning.
94) Which of the following statements regarding the learning phenomenon is true?
A) The more units that are produced, the greater the average time to produce a single unit.
B) The relationship between number of units produced and the marginal time to produce the latest unit is linear.
C) Total labor cost is a linear function of the total units produced.
D) As production doubles, the time to produce the latest unit decreases.
95) Bachmann Products, Inc., has found that new products follow a learning curve. The first two units have been completed with the following results:
Units Produced | Marginal Labor Time |
1 | 80.00 |
2 | 68.00 |
How much time will be needed to complete the 4th unit?
A) 74.00 hours.
B) 57.80 hours.
C) 56.00 hours.
D) 54.40 hours.
96) Bachmann Products, Inc., has found that new products follow a learning curve. The first two units have been completed with the following results:
Units Produced | Marginal Labor Time |
1 | 80.00 |
2 | 68.00 |
How much time will be needed to complete the 8th unit?
A) 74.00 hours.
B) 57.80 hours.
C) 56.00 hours.
D) 49.13 hours.
97) The following manufacturing costs were incurred by the Miracle Mile Company in 2019:
|
|
|
|
Direct materials | $ | 225,000 |
|
Direct labor |
| 350,000 |
|
Manufacturing overhead |
| 470,000 |
|
These costs were incurred to produce 50,000 units of product. Variable manufacturing overhead was 70% of the direct materials cost.
In 2020, the direct material and variable overhead costs per unit will increase by 12%, but the direct labor costs per unit are not expected to change. Fixed manufacturing costs are expected to increase by 8%.
Required:
(a.) Prepare a cost estimate for an activity level of 40,000 units of product in 2020.
(b.) Determine the total product costs per unit for 2019 and 2020.
98) The following manufacturing costs were incurred by the Trinitram Company in 2019:
|
|
|
|
Direct materials | $ | 112,500 |
|
Direct labor |
| 175,000 |
|
Manufacturing overhead |
| 235,000 |
|
These costs were incurred to produce 25,000 units of product. Variable manufacturing overhead was 80% of the direct materials cost.
In 2020, the direct material and variable overhead costs per unit will increase by 15%, but the direct labor costs per unit are not expected to change. Fixed manufacturing costs are expected to increase by 7.5%.
Required:
(a.) Prepare a cost estimate for an activity level of 20,000 units of product in 2020.
(b.) Determine the total product costs per unit for 2019 and 2020.
99) The Thomas Company's total overhead costs at various levels of activity are presented below:
Month | Direct Labor Hours |
| Total Overhead |
| ||||
July |
| 7,500 |
|
| $ | 272,000 |
|
|
August |
| 6,000 |
|
|
| 234,000 |
|
|
September |
| 9,000 |
|
|
| 319,000 |
|
|
October |
| 10,500 |
|
|
| 340,500 |
|
|
Assume that the overhead costs above consist of utilities, supervisory salaries, and maintenance. The breakdown of these costs at the 9,000 direct labor hour level of activity is as follows:
|
|
|
|
|
Utilities (V) | $ | 137,700 |
|
|
Supervisory Salaries (F) |
| 80,000 |
|
|
Maintenance (M) |
| 101,300 |
|
|
|
| 319,000 |
|
|
Required:
(a.) Using the high-low method, determine the cost formula for maintenance.
(b.) Express the company's total overhead costs in linear equation form.
100) The Feline Company has been having some difficulties estimating its manufacturing overhead costs. In the past, manufacturing overhead costs have been related to production levels. However, some production managers have indicated that the size of their production lots might also be having an impact on the amount of their monthly manufacturing overhead costs. In order to investigate this possibility, the company collected information on its monthly manufacturing overhead costs, production in units, and average production lot size for 2020.
Month | Production (Units) |
| Manufacturing Overhead Cost |
| Average Monthly Production Lot Size |
| |||||||
1 |
| 75,000 |
|
| $ | 925,800 |
|
| 20 |
| |||
2 |
| 90,000 |
|
|
| 843,875 |
|
| 19 |
| |||
3 |
| 65,000 |
|
|
| 910,125 |
|
| 24 |
| |||
4 |
| 80,000 |
|
|
| 946,000 |
|
| 19 |
| |||
5 |
| 55,000 |
|
|
| 879,000 |
|
| 24 |
| |||
6 |
| 50,000 |
|
|
| 825,000 |
|
| 18 |
| |||
7 |
| 85,000 |
|
|
| 960,000 |
|
| 22 |
| |||
8 |
| 105,000 |
|
|
| 1,053,500 |
|
| 25 |
| |||
9 |
| 102,000 |
|
|
| 1,020,000 |
|
| 23 |
| |||
10 |
| 68,000 |
|
|
| 905,000 |
|
| 20 |
| |||
11 |
| 75,000 |
|
|
| 938,000 |
|
| 22 |
| |||
12 |
| 95,000 |
|
|
| 995,000 |
|
| 24 |
|
Required:
(a.) Use the high-low method to estimate next month's manufacturing overhead costs, assuming the company is planning to produce 92,000 units.
(b.) Use the high-low method to estimate next month's manufacturing overhead costs, assuming the company is planning to run a 21-lot size.
101) Argo Company ran a regression analysis using direct labor hours as the independent variable and manufacturing overhead costs as the dependent variable. The results are summarized below:
|
|
|
|
Intercept | $ | 14,600 |
|
Slope | $ | 12.55 |
|
Correlation coefficient |
| 0.931 |
|
R-squared |
| 0.867 |
|
Argo is planning on operating at a level that would require 12,000 direct labor hours per month in the upcoming year.
Required:
(a.) Use the information from the regression analysis to write the cost estimation equation for the manufacturing overhead costs.
(b.) Compute the estimated manufacturing overhead costs per month for the upcoming year.
102) The Feline Company has been having some difficulties estimating its manufacturing overhead costs. In the past, manufacturing overhead costs have been related to production levels. However, some production managers have indicated that the size of their production lots might also be having an impact on the amount of their monthly manufacturing overhead costs. In order to investigate this possibility, the company collected information on its monthly manufacturing overhead costs, production in units, and average production lot size for 2020.
Month | Production (Units) |
| Manufacturing Overhead Cost |
| Average Monthly Production Lot Size |
| |||||||
1 |
| 75,000 |
|
| $ | 925,800 |
|
| 20 |
| |||
2 |
| 90,000 |
|
|
| 843,875 |
|
| 19 |
| |||
3 |
| 65,000 |
|
|
| 910,125 |
|
| 24 |
| |||
4 |
| 80,000 |
|
|
| 946,000 |
|
| 19 |
| |||
5 |
| 55,000 |
|
|
| 879,000 |
|
| 24 |
| |||
6 |
| 50,000 |
|
|
| 825,000 |
|
| 18 |
| |||
7 |
| 85,000 |
|
|
| 960,000 |
|
| 22 |
| |||
8 |
| 105,000 |
|
|
| 1,053,500 |
|
| 25 |
| |||
9 |
| 102,000 |
|
|
| 1,020,000 |
|
| 23 |
| |||
10 |
| 68,000 |
|
|
| 905,000 |
|
| 20 |
| |||
11 |
| 75,000 |
|
|
| 938,000 |
|
| 22 |
| |||
12 |
| 95,000 |
|
|
| 995,000 |
|
| 24 |
|
Regression analysis results of the information presented above are as follows:
Ordinary regression:
Equation: | $691,741 + $3.0692 × units |
r-square: | 0.628 |
Multiple regression:
Equation: | $482,172 + $2.4918 × units + $11,770.939 × lot size |
r-square: | 0.777 |
Required:
(a.) Use the results from the ordinary regression and estimate next month's manufacturing overhead costs, assuming the company is planning to produce 92,000 units. (final answer should be rounded to the nearest whole dollar)
(b.) Use the results from the multiple regression and estimate the next month's manufacturing costs, assuming the company is planning to produce 92,000 units with an average lot size of 21. (final answer should be rounded to the nearest whole dollar)
(c.) Comment on which regression seems to be more appropriate under these circumstances. What additional information would you like to see? Be specific.
103) The Ornate Company produces a single product and has total costs ranging from $321,875 (at 20,000 units) to $966,875 (at 80,000 units). Sales volume in 2020 was 32,000, and operating income was $45,125. Ornate's product is highly specialized; therefore, no units are kept in inventory.
Required:
(a.) Determine the cost equation for Ornate's costs.
(b.) Prepare a contribution margin income statement for 2020 including separate columns for total dollars, per unit dollars, and percentages.
(c.) Determine the break-even point (in units and in dollars).
104) Iowa Enterprises had an average cost of $10.75 during a month when 50,000 units were produced. When production doubled several months later, the average cost dropped to $8.25.
Required:
(a.) Determine the fixed and variable portions of production costs.
(b.) What will unit cost be when production equals 80,000 units?
105) Washington Products had costs of $600,000 when sales equaled 75,000 units. When sales increased by 25,000 units, costs increased by $125,000. The selling price is $9 per unit.
Required:
(a.) Determine the fixed and variable portions of costs.
(b.) Prepare a contribution margin income statement for a month with sales of 80,000 units.
106) New Venture, Inc. has received a contract for 8 units of a new product. The contract is a cost-plus contract, with the total to be received equal to the total labor cost + 20%. New Venture found that the first unit of a new product required 120 hours to complete. The second unit was completed using only 114 hours. New Venture believes that the rate of learning that was observed will continue for all 8 units of the contract. The labor wage paid is $25/hour. The following factors are available for various rates of learning: 80% learning, b = –0.3219; 85%, b = –0.2345; 90%, b = –0.1520; 95%, b = –0.0740.
Required:
(a.) What will the total labor cost be for the contract?
(b.) What will the total fee be for the contract?
107) Market Products, Inc., has found that new products follow a learning curve. The first two units have been completed with the following results:
Units Produced | Marginal Labor Time |
1 | 250.00 |
2 | 225.00 |
Required:
(a.) How much time will be needed to complete the 4th unit?
(b.) How much time will be needed to complete the 8th unit?
(c.) How much time will be needed to complete the 16th unit?
108) Clough Company is interested in establishing the relationship between utility costs and machine hours. Data have been collected and a regression analysis prepared using Excel. The monthly data and the regression output follow:
Month | Machine Hours | Utility Costs | ||
January | 3,250 | $ | 22,080 |
|
February | 3,770 |
| 25,200 |
|
March | 2,470 |
| 16,200 |
|
April | 4,030 |
| 27,600 |
|
May | 4,940 |
| 33,900 |
|
June | 4,290 |
| 26,400 |
|
July | 5,330 |
| 29,700 |
|
August | 4,550 |
| 27,300 |
|
September | 2,600 |
| 18,600 |
|
October | 4,810 |
| 31,200 |
|
November | 6,110 |
| 37,200 |
|
December | 5,460 |
| 33,300 |
|
SUMMARY OUTPUT | ||
Regression Statistics | ||
Multiple R | 96.5 | % |
R Square | 93.2 | % |
Adjusted R-Square | 92.5 | % |
Standard Error | 1,710.21 |
|
Observations | 12.00 |
|
| Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% |
Intercept | 4,472.26 | 2,019.39 | 2.21 | 0.051 | –27.23 | 8971.74 |
Machine Hours | 5.329 | 0.455 | 11.70 | 3.69E–07 | 4.314 | 6.343 |
Required:
(a.) What is the equation for utility costs using the regression analysis?
(b.) Does the variable "machine hours" have statistical significance? Explain.
(c.) Prepare an estimate of utility costs for a month when 3,000 machine hours are worked.
109) Clough Company is interested in establishing the relationship between utility costs and machine hours. Data have been collected and a regression analysis prepared using Excel. The monthly data and the regression output follow:
Month | Machine Hours | Utility Costs | ||
January | 3,250 | $ | 22,080 |
|
February | 3,770 |
| 25,200 |
|
March | 2,470 |
| 16,200 |
|
April | 4,030 |
| 27,600 |
|
May | 4,940 |
| 33,900 |
|
June | 4,290 |
| 26,400 |
|
July | 5,330 |
| 29,700 |
|
August | 4,550 |
| 27,300 |
|
September | 2,600 |
| 18,600 |
|
October | 4,810 |
| 31,200 |
|
November | 6,110 |
| 37,200 |
|
December | 5,460 |
| 33,300 |
|
Required:
(a.) What is the equation for utility costs using the high-low method?
(b.) Prepare an estimate of utility costs for a month when 3,000 machine hours are worked.
110) Yates Corp. wants to develop a cost equation for its administrative costs. The controller believes the appropriate cost driver is units produced. Last year's data are presented below:
Month | Units Produced |
| Administrative Costs | ||||||||
January |
| 32,500 |
|
|
| $ | 24,288 |
|
|
| |
February |
| 37,700 |
|
|
|
| 27,720 |
|
|
| |
March |
| 24,700 |
|
|
|
| 17,820 |
|
|
| |
April |
| 40,300 |
|
|
|
| 30,360 |
|
|
| |
May |
| 49,400 |
|
|
|
| 37,290 |
|
|
| |
June |
| 42,900 |
|
|
|
| 29,040 |
|
|
| |
July |
| 53,300 |
|
|
|
| 32,670 |
|
|
| |
August |
| 45,500 |
|
|
|
| 30,030 |
|
|
| |
September |
| 26,000 |
|
|
|
| 20,460 |
|
|
| |
October |
| 48,100 |
|
|
|
| 34,320 |
|
|
| |
November |
| 61,100 |
|
|
|
| 40,920 |
|
|
| |
December |
| 54,600 |
|
|
|
| 36,630 |
|
|
| |
Total |
| 516,100 |
|
|
| $ | 361,548 |
|
|
| |
Average |
| 43,008 |
|
|
| $ | 30,129 |
|
|
|
Required:
(a.) What is the equation for administrative costs using the high-low method?
(b.) Prepare an estimate of administrative costs for a month when 30,000 units are produced.
111) Yates Corp. wants to develop a cost equation for its administrative costs. The controller believes the appropriate cost driver is units produced. Last year's data are presented below:
Month | Units Produced | Administrative Costs | ||||||
January |
| 32,500 |
| $ | 24,288 |
|
|
|
February |
| 37,700 |
|
| 27,720 |
|
|
|
March |
| 24,700 |
|
| 17,820 |
|
|
|
April |
| 40,300 |
|
| 30,360 |
|
|
|
May |
| 49,400 |
|
| 37,290 |
|
|
|
June |
| 42,900 |
|
| 29,040 |
|
|
|
July |
| 53,300 |
|
| 32,670 |
|
|
|
August |
| 45,500 |
|
| 30,030 |
|
|
|
September |
| 26,000 |
|
| 20,460 |
|
|
|
October |
| 48,100 |
|
| 34,320 |
|
|
|
November |
| 61,100 |
|
| 40,920 |
|
|
|
December |
| 54,600 |
|
| 36,630 |
|
|
|
SUMMARY OUTPUT | |
Regression Statistics | |
Multiple R | 0.965383 |
R Square | 0.931965 |
Adjusted R-Square | 0.925162 |
Standard Error | 1,881.232 |
Observations | 12 |
| Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% |
Intercept | 4,919.48 | 2,221.329 | 2.21 | 0.051156 | –29.9485 | 9,868.909 |
Units produced | 0.586154 | 0.050082 | 11.70 | 3.69E–07 | 0.474566 | 0.697743 |
Required:
(a.) What is the equation for administrative costs using the regression analysis?
(b.) Does the variable "units produced" have statistical significance? Explain.
(c.) Prepare an estimate of administrative costs for a month when 30,000 units are produced.
112) The Wonder Drug Company's total overhead costs at various levels of activity are presented below:
Month | Direct Labor Hours |
| Total Overhead |
| ||||
September |
| 15,000 |
|
| $ | 472,000 |
|
|
October |
| 12,000 |
|
|
| 409,400 |
|
|
November |
| 18,000 |
|
|
| 542,000 |
|
|
December |
| 21,000 |
|
|
| 604,700 |
|
|
Assume that the overhead costs above consist of indirect labor, scheduling salaries, and maintenance. The breakdown of these costs for the month of November is as follows:
Indirect labor (V) $219,600
Maintenance (M) 197,400
Scheduling Salaries (F) 125,000
$542,000
Required:
(a.) Using the high-low method, determine the cost formula for maintenance.
(b.) Express the company's total overhead costs in linear equation form.
113) The Norcross Company has traditionally estimated manufacturing overhead costs using production volume. Some of the production managers believe that the number of setups may also have an impact on monthly manufacturing overhead costs. In order to investigate this possibility, the company collected information on its monthly manufacturing overhead costs, production in units, and number of setups for 2020.
Month | Production (Units) |
| Manufacturing Overhead Cost |
| Number of Setups |
| |||||||
1 |
| 50,000 |
|
| $ | 800,100 |
|
| 17 |
| |||
2 |
| 65,000 |
|
|
| 752,500 |
|
| 16 |
| |||
3 |
| 40,000 |
|
|
| 795,100 |
|
| 21 |
| |||
4 |
| 55,000 |
|
|
| 822,750 |
|
| 16 |
| |||
5 |
| 30,000 |
|
|
| 771,225 |
|
| 21 |
| |||
6 |
| 25,000 |
|
|
| 706,200 |
|
| 15 |
| |||
7 |
| 60,000 |
|
|
| 843,000 |
|
| 19 |
| |||
8 |
| 80,000 |
|
|
| 935,200 |
|
| 22 |
| |||
9 |
| 77,000 |
|
|
| 901,750 |
|
| 20 |
| |||
10 |
| 43,000 |
|
|
| 786,400 |
|
| 17 |
| |||
11 |
| 50,000 |
|
|
| 819,600 |
|
| 19 |
| |||
12 |
| 70,000 |
|
|
| 880,900 |
|
| 21 |
|
Regression analysis results of the information presented above are as follows:
Ordinary regression:
Equation: $650,398 + $3.1061 × units
r-square: .707
Multiple regression:
Equation: [$464,481 + ($2.5356 × units)] + [($11,631.6048 × number of set ups)]
r-square: .867
Required:
(a.) Use the results from the ordinary regression and estimate next month's manufacturing overhead costs, assuming the company is planning to produce 75,000 units. (final answer should be rounded to the nearest whole dollar)
(b.) Use the results from the multiple regression and estimate the next month's manufacturing overhead costs, assuming the company is planning to produce 75,000 units with 18 set ups. (final answer should be rounded to the nearest whole dollar)
(c.) Comment on which regression seems to be more appropriate under these circumstances. What additional information would you like to see? Be specific.
114) Barnard Enterprises had an average cost of $8.60 during a month when 75,000 units were produced. When production was 125,000 units several months later, the average cost dropped to $6.98.
Required:
(a.) Determine the fixed and variable portions of production costs.
(b.) What will unit cost be when production equals 110,000 units?
115) Doran Products had costs of $950,000 when sales equaled 55,000 units. When sales increased to 85,000 units, total costs increased to $1,400,000. The selling price is $21 per unit.
Required:
(a.) Determine the fixed and variable portions of total costs.
(b.) Prepare a contribution margin income statement for a month with sales of 70,000 units.
116) Markham, Inc. has received a contract for 8 units of a new product. The contract is a cost-plus contract, with the total to be received equal to the total labor cost + 30%. Markham found that the first unit of a new product required 90 hours to complete. The second unit was completed using only 76.5 hours. Markham believes that the rate of learning that was observed will continue for all 8 units of the contract. The labor wage paid is $40/hour. The following factors are available for various rates of learning: 80% learning, b = −0.3219; 85%, b = −0.2345; 90%, b = −0.1520; 95%, b = −0.0740.
Required:
(a.) What will the total labor cost be for the contract?f
(b.) What will be the total fee for the contract?
117) Woodman Products, Inc., has found that new products follow a learning curve. The first two units have been completed with the following results:
Units Produced | Marginal Labor Time |
1 | 112.50 |
2 | 90.00 |
Required:
(a.) How much time will be needed to complete the 4th unit?
(b.) How much time will be needed to complete the 8th unit?
(c.) How much time will be needed to complete the 16th unit?
118) Below are several examples of costs that are labeled fixed or variable according to their typical accounting designations. Under which circumstances would any of these costs behave in a manner opposite to that listed?
a. Direct labor—variable.
b. Equipment depreciation—fixed.
c. Utilities (with a minimum charge)—variable.
d. Supervisory salaries—fixed.
e. Indirect materials purchased in given lot sizes that become spoiled within a few days—variable.
119) When using past data to predict a cost that has fixed and variable components, it is possible to have an equation with a negative intercept. Does this mean that at a zero production level, the company will make money on its fixed costs? Explain.
120) Describe the engineering method of cost estimation. Provide two advantages and two disadvantages associated with the engineering approach to cost estimation.
121) Explain the difference between the engineering method of cost estimation and the account analysis method.
122) When preparing cost estimates for account analysis purposes, should the costs be extracted from the historical accounting records?
123) Describe two advantages and two disadvantages of the high-low method of cost estimation.
124) Is it possible to compensate for the effects of price instability when preparing cost estimates using high-low or regression techniques?
125) J.C. Riley, who owns Riley's Auto Repair Shop is trying to determine whether the company's advertising program is successful. He has used a spreadsheet program to estimate the relationship between advertising expenditures and sales dollars. Monthly data for the past two years were entered into the program. The regression results indicated the following:
Sales dollars = $169, 000 − ($200 × Advertising expenditures)
Correlation coefficient = −0.864
To J.C., the results imply that advertising is actually reducing sales. Can you help explain to him what might cause the negative relationship between advertising expenditures and sales?
126) Southside Hospital is trying to get a better idea of the costs in its cardiac surgical unit. Unit cost data for supplies, labor, etc. have been collected for a three-year period. After analyzing the data using Excel, the following output was generated, based on 1,500 procedures.
Intercept = $2,169, 000
Coefficient on procedures $972
Correlation coefficient = 0.448
R2 = 0.189
The controller asks you for advice on whether to rely on this estimate. Based on the output, what would you say?
127) What are "outliers" and what effect does their presence have when using regression analysis for cost estimation?
128) Describe the effect on cost estimation of four of the following five problems: 1) missing data, 2) outliers, 3) allocated and discretionary costs, 4) inflation, or 5) mismatched time periods.
129) Your manager asks you for a cost estimate to open a new retail outlet and says, "I want you to use statistical analysis, so it will be objective because it is based on real data." How would you respond?
130) Fast-food restaurants, like Taco Bell and McDonalds, are known for high employee turnover, high quality, and low costs. Using your knowledge of the learning phenomenon, how do these fast-food chains get high quality and low costs when they have so much employee turnover?
131) Assume that as part of their recent merger, Dell and EMC are perfecting a new device that will access and coordinate the internet of things. The new company is interested in estimating the impact of learning on the cost of producing this new device and plan to use data from previous products to estimate the learning parameter. What are the advantages of doing this? What are the disadvantages?