Question 1

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:
$\begin{array}{lrr}
& \text { Administrative } & \text { Credit } \
\text { Month } & \text { Costs } & \text { Hours }\
\text { July } & \$ 129,301 & 250 \
\text { August } & 82,613 & 115 \
\text { September } & 225,580 & 1,392 \
\text { October } & 216,394 & 1,000 \
\text { November } & 258,263 & 1,309\
\text { December } & 184,445 & 1,112 \
\text { January } & 219,137 & 1,335 \
\text { February } & 245,000 & 1,373 \
\text { March } & 209,462 & 1,064 \
\text { April } & 191,925 & 1,123 \
\text { May } & 249,978 & 1,360\
\text { June } & 170,41 \varepsilon & 420 \
\text { July } & 128,167 & 315 \
\text { Total } & \$ 2,510,687 & 12,172 \
\text { Average } & \$ 193,130 & 936
\end{array}$

The controller's office has analyzed the data and has given you the results from the regression analysis:
$$\begin{array}{c} 
  { \text { SUMMARY OUTPUT } } \
 { \text { Regression Statistics } } \
\begin{array} { | l | r | } 
\hline \text { Multiple R } & 0.9317157 \
\hline \text { R Square } & 0.868094147 \
\hline \text { Adjusted R Square } & 0.856102705 \
\hline \text { Standard Error } & 20,134.92395 \
\hline \text { Observations } & 13 \
\hline
\end{array}\end{array}$$
$$\begin{array} { | l | r | r | r | r | r | } 
\hline \text { ANOVA } & & & & & \
\hline & \text { df} &  \text { S S } &  \text {  M S } &  \text {  F } & \text { Significance }  \text {  F } \
\hline \text { Repression } & 1 & 29,349,143,514 & 29,349,143,514 & 72.3928117 & 3.61909 \mathrm { E } - 06 \
\hline \text { Residual } & 11 & 4,459,566,787 & 405,415,162.4 & & \
\hline \text { Total } & 12 & 33,808,710,301 & & & \
\hline
\end{array}$$

-
The correlation coefficient (rounded to the 3rd decimal) for the regression equation for administrative costs is:

Accepted Answer

A)  0.932. 
B)  0.868. 
C)  0.856. 
D)  0.966.

Question 2

Which of the following is the difference between variable costs and fixed costs? (CMA adapted)

Accepted Answer

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.

Question 3

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.

Accepted Answer

The answer of When using past data to predict a...

Question 4

Market Products, Inc., has found that new products follow a learning curve. The first two units have been completed with the following results:
 $\begin{array}{|c|c|}
\hline \text { Units Produced } & \text { Marginal Labor Time } \
\hline 1 & 250.00 \
\hline2 & 225  \
\hline
\end{array}$
 
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?

Accepted Answer

The answer of Market Products, Inc., has found that new...

Question 5

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:
 $\begin{array}{lcc}
\text {Month}&\text {Units Produced}&\text {Administrative Costs}\
\text { January } & 32,500 & \$24,288 \
 \text { February } & 37,700 &27,720 \
 \text { March } & 24,700 &17,820 \
\text { April } & 40,300 &30,360 \
 \text { May } & 49,400 &37,290 \
 \text { June } & 42,900 &29,040 \
\text { July } & 53,300 &32,670 \
 \text { Alugust } & 45,500 &30,030 \
 \text { September } & 26,000 &20,460 \
\text { October } & 48,100 & 34,320\
 \text { November } & 61,100 &40,920 \
 \text { December } & 54,600 &36,630 \
\end{array}$
 
 $$\begin{array}{c}
 { \text { SUMMARY OUTPUT } } \
 { \text { Regrerrian Statirticr } } \
\begin{array} { | l | r | } 
\hline \text { Multiple R } & 0.96538 \
\hline \text { R Squjare } & 0.931965 \
\hline \text { Adjusted R-Square } & 0.925162 \
\hline \text { Starddard Error } & 1,881.23 \
\hline \text { Observations } & 12 \
\hline
\end{array}\end{array}$$ 
 $$\begin{array} { | l | r | r | r | r | r | r | } 
\hline & \text { Coefficiend } & \begin{array} { c } 
\text { Standard } \
\text { Error }
\end{array} & \text { t Stat } & \text { P-valke } & \begin{array} { c } 
\text { Lower } \
\text { 95\% }
\end{array} & \text { Upper 95\% } \
\hline \text { Irtercept } & 4,919.48 & 2,221.329 & 2.21 & 0.051156 & - 29.9485 & 9,868.909 \
\hline \begin{array} { l } 
\text { Units } \
\text { produced }
\end{array} & 0.586154 & 0.050082 & 11.70 & 3.69 \mathrm { E } - 07 & 0.474560 & 0.697743 \
\hline
\end{array}$$ 
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.

Accepted Answer

The answer of Yates Corp. wants to develop a cost...

Question 6

Identifying the relation between the activity and the costs is a key step in which of the following cost estimation methods?

Accepted Answer

A)  Scattergraph. 
B)  High-low method. 
C)  Account analysis. 
D)  Linear regression.

Question 7

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.

Accepted Answer

A)  Only A is true. 
B)  Only B is true. 
C)  Both of these are true. 
D)  Neither of these is true.

Question 8

What are "outliers" and what effect does their presence have when using regression analysis for cost estimation?

Accepted Answer

The answer of What are "outliers" and what effect does...

Question 9

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) $$\begin{array} { l r c } 
& \begin{array} { c } 
\text { Hours of } \
\text { Activity }
\end{array} & \begin{array} { c } 
\text { Maintenance } \
\text { Costs }
\end{array} \
\text { January } & 480 & \$ 4,200 \
\text { February } & 320 & 3,000 \
 \text { March } & 400 & 3,600 \
\text { April }& 300 & 2,820 \
\text { May }  & 500 & 4,350 \
\text { June }& 310 & 2,960 \
\text { July }  & 320 & 3,030 \
\text { August } & 520 & 4,470 \
\text { September } & 490 & 4,260 \
\text { October } & 470 & 4,050 \
\text { November } & 350 & 3,300 \
\text { December }& 340 & 3,160 \
 \text { Sum } & 4,800 & \$ 3,200 \
 \text { Average }& 400 & 3,600 \
\text { A coefficient } & & 684.65 \
\text { B coefficient } & & 7.2884 \
\text { Standard error of the a coefficient } & 49.515 & \
\text { Standard error of the b coefficient } & 0.12126 & \
\text { Standard error of the estimate } & & 34.469 \
\mathrm { R } ^ { 2 } & & 0.99724 \
\text { T-value a } & & 13.827 \
\text { T-value b } & & 60.105
\end{array}$$ 
- What would be the cost equation if the high-low method is used?

Accepted Answer

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).

Question 10

Which of the following is not a data problem an analyst must watch for when estimating cost behavior?

Accepted Answer

A)  Non-numeric data. 
B)  Inflation. 
C)  Discretionary costs. 
D)  Mismatched time periods.

Question 11

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) $$\begin{array} { l r c } 
& \begin{array} { c } 
\text { Hours of } \
\text { Activity }
\end{array} & \begin{array} { c } 
\text { Maintenance } \
\text { Costs }
\end{array} \
\text { January } & 480 & \$ 4,200 \
\text { February } & 320 & 3,000 \
 \text { March } & 400 & 3,600 \
\text { April }& 300 & 2,820 \
\text { May }  & 500 & 4,350 \
\text { June }& 310 & 2,960 \
\text { July }  & 320 & 3,030 \
\text { August } & 520 & 4,470 \
\text { September } & 490 & 4,260 \
\text { October } & 470 & 4,050 \
\text { November } & 350 & 3,300 \
\text { December }& 340 & 3,160 \
 \text { Sum } & 4,800 & \$ 3,200 \
 \text { Average }& 400 & 3,600 \
\text { A coefficient } & & 684.65 \
\text { B coefficient } & & 7.2884 \
\text { Standard error of the a coefficient } & 49.515 & \
\text { Standard error of the b coefficient } & 0.12126 & \
\text { Standard error of the estimate } & & 34.469 \
\mathrm { R } ^ { 2 } & & 0.99724 \
\text { T-value a } & & 13.827 \
\text { T-value b } & & 60.105
\end{array}$$  
-What would be the cost equation if regression analysis is used?

Accepted Answer

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).

Question 12

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.
 $$\begin{array} { c c c r } 
\text { Month } & \begin{array} { c } 
\text { Production } \
\text { (Units) }
\end{array} & \begin{array} { c } 
\text { Manufacturing } \
\text { Overhead Cost }
\end{array} & \begin{array} { c } 
\text { Number } \
\text { of Setups }
\end{array} \
1 & 50,000 & \$ 800,100 & 17 \
2 & 65,000 & 752,500 & 16 \
3 & 40,000 & 795,100 & 21 \
4 & 55,000 & 822,750 & 16 \
5 & 30,000 & 771,225 & 21 \
6 & 25,000 & 706,200 & 15 \
7 & 60,000 & 843,000 & 19 \
8 & 80,000 & 935,200 & 22 \
9 & 77,000 & 901,750 & 20 \
10 & 43,000 & 786,400 & 17 \
11 & 50,000 & 819,600 & 19 \
12 & 70,000 & 880,900 & 21
\end{array}$$ 
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.

Accepted Answer

The answer of The Norcross Company has traditionally estimated manufacturing...

Question 13

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:
 $$\begin{array} { l c c } 
\text { Intercept } & \$ 14,600 \
\text { Slope } & \$  12.55 \
\text { Correlation coefficient } & 0.931 \
\text { R-squared } & 0.867
\end{array}$$ 
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.

Accepted Answer

The answer of Argo Company ran a regression analysis using...

Question 14

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.

Accepted Answer

A) True 
 B)False

Question 15

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) $$\begin{array} { l r c } 
& \begin{array} { c } 
\text { Hours of } \
\text { Activity }
\end{array} & \begin{array} { c } 
\text { Maintenance } \
\text { Costs }
\end{array} \
\text { January } & 480 & \$ 4,200 \
\text { February } & 320 & 3,000 \
 \text { March } & 400 & 3,600 \
\text { April }& 300 & 2,820 \
\text { May }  & 500 & 4,350 \
\text { June }& 310 & 2,960 \
\text { July }  & 320 & 3,030 \
\text { August } & 520 & 4,470 \
\text { September } & 490 & 4,260 \
\text { October } & 470 & 4,050 \
\text { November } & 350 & 3,300 \
\text { December }& 340 & 3,160 \
 \text { Sum } & 4,800 & \$ 3,200 \
 \text { Average }& 400 & 3,600 \
\text { A coefficient } & & 684.65 \
\text { B coefficient } & & 7.2884 \
\text { Standard error of the a coefficient } & 49.515 & \
\text { Standard error of the b coefficient } & 0.12126 & \
\text { Standard error of the estimate } & & 34.469 \
\mathrm { R } ^ { 2 } & & 0.99724 \
\text { T-value a } & & 13.827 \
\text { T-value b } & & 60.105
\end{array}$$  
-What is the variable cost per hour using the high-low method to estimate the cost equation?

Accepted Answer

A)  $9.00. 
B)  $7.50. 
C)  $0.1333. 
D)  $0.1111.

Question 16

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:
$\begin{array}{lrr}
& \text { Administrative } & \text { Credit } \
\text { Month } & \text { Costs } & \text { Hours }\
\text { July } & \$ 129,301 & 250 \
\text { August } & 82,613 & 115 \
\text { September } & 225,580 & 1,392 \
\text { October } & 216,394 & 1,000 \
\text { November } & 258,263 & 1,309\
\text { December } & 184,445 & 1,112 \
\text { January } & 219,137 & 1,335 \
\text { February } & 245,000 & 1,373 \
\text { March } & 209,462 & 1,064 \
\text { April } & 191,925 & 1,123 \
\text { May } & 249,978 & 1,360\
\text { June } & 170,41 \varepsilon & 420 \
\text { July } & 128,167 & 315 \
\text { Total } & \$ 2,510,687 & 12,172 \
\text { Average } & \$ 193,130 & 936
\end{array}$

The controller's office has analyzed the data and has given you the results from the regression analysis:
$$\begin{array}{c} 
  { \text { SUMMARY OUTPUT } } \
 { \text { Regression Statistics } } \
\begin{array} { | l | r | } 
\hline \text { Multiple R } & 0.9317157 \
\hline \text { R Square } & 0.868094147 \
\hline \text { Adjusted R Square } & 0.856102705 \
\hline \text { Standard Error } & 20,134.92395 \
\hline \text { Observations } & 13 \
\hline
\end{array}\end{array}$$
$$\begin{array} { | l | r | r | r | r | r | } 
\hline \text { ANOVA } & & & & & \
\hline & \text { df} &  \text { S S } &  \text {  M S } &  \text {  F } & \text { Significance }  \text {  F } \
\hline \text { Repression } & 1 & 29,349,143,514 & 29,349,143,514 & 72.3928117 & 3.61909 \mathrm { E } - 06 \
\hline \text { Residual } & 11 & 4,459,566,787 & 405,415,162.4 & & \
\hline \text { Total } & 12 & 33,808,710,301 & & & \
\hline
\end{array}$$

-
If the controller uses the high-low method to estimate costs, the cost equation for administrative costs is

Accepted Answer

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.

Question 17

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:
 $\begin{array}{lcc}
\text {Month}&\text {Units Produced}&\text {Administrative Costs}\
\text { January } & 32,500 & \$24,288 \
 \text { February } & 37,700 &27,720 \
 \text { March } & 24,700 &17,820 \
\text { April } & 40,300 &30,360 \
 \text { May } & 49,400 &37,290 \
 \text { June } & 42,900 &29,040 \
\text { July } & 53,300 &32,670 \
 \text { Alugust } & 45,500 &30,030 \
 \text { September } & 26,000 &20,460 \
\text { October } & 48,100 & 34,320\
 \text { November } & 61,100 &40,920 \
 \text { December } & 54,600 &36,630 \
\text { Total } & 516,100&\$361,548 \
 \text { Average } & 43,008 &\$30,129\
\end{array}$ 
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.

Accepted Answer

The answer of Yates Corp. wants to develop a cost...

Question 18

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?

Accepted Answer

A)  $2.78. 
B)  $2.86. 
C)  $3.10. 
D)  $3.38.

Question 19

In the learning curve equation Y = aXb, the "b" term represents:

Accepted Answer

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.

Question 20

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) $$\begin{array} { l r c } 
& \begin{array} { c } 
\text { Hours of } \
\text { Activity }
\end{array} & \begin{array} { c } 
\text { Maintenance } \
\text { Costs }
\end{array} \
\text { January } & 480 & \$ 4,200 \
\text { February } & 320 & 3,000 \
 \text { March } & 400 & 3,600 \
\text { April }& 300 & 2,820 \
\text { May }  & 500 & 4,350 \
\text { June }& 310 & 2,960 \
\text { July }  & 320 & 3,030 \
\text { August } & 520 & 4,470 \
\text { September } & 490 & 4,260 \
\text { October } & 470 & 4,050 \
\text { November } & 350 & 3,300 \
\text { December }& 340 & 3,160 \
 \text { Sum } & 4,800 & \$ 3,200 \
 \text { Average }& 400 & 3,600 \
\text { A coefficient } & & 684.65 \
\text { B coefficient } & & 7.2884 \
\text { Standard error of the a coefficient } & 49.515 & \
\text { Standard error of the b coefficient } & 0.12126 & \
\text { Standard error of the estimate } & & 34.469 \
\mathrm { R } ^ { 2 } & & 0.99724 \
\text { T-value a } & & 13.827 \
\text { T-value b } & & 60.105
\end{array}$$  
-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)

Accepted Answer

A)  $3,797. 
B)  $3,780. 
C)  $3,746. 
D)  $3,600.

Exam 5: Cost Estimation