Management Chapter 5 Income would be higher under variable costing

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C. Under absorption costing, income would be $400 higher than under variable

costing and would be calculated as follows:

31. (LO5, 6—Variable costing and absorption costing: Calculation of net income)

A. Under absorption costing, income would be $3,766,000, calculated as follows:

Net operating income $3,766,000

B. Income would be higher under variable costing.

C. Under variable costing, income would be higher by $20,000

32. (LO5, 6—Absorption costing versus variable costing: Benefits and calculation

of net operating income)

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5-15

Because the company is required to provide GAAP financial statements to the

Problems

33. (LO1 and 2—Regression versus high/low method)

A. With the high/low method, the cost equation for utility cost is $929 + $0.006

(units produced). The variable cost per unit is equal to the change in cost

C.

Regression Statistics

Multiple R 0.654226

Observations 14

ANOVA

df SS MS F

Coefficients

Standard

Error t Stat P-value

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With regression analysis, the cost formula would be

34. (LO1 and 2—Regression analysis interpretation)

35. (LO1, 2—Basic cost behavior, high/low method)

A. For Simon, rental costs are fixed and both utilities and indirect labor costs are

B. Before total overhead costs are estimated, mixed costs must be broken down

into fixed and variable components. Students should note that, for Simon, this

can be done separately or by combining utilities and indirect labor costs.

High/low analysis gives the following results:

Simon: The variable cost per unit for utilities is $5.00 per unit,

The variable cost per unit for indirect labor is $5.20 per unit,

calculated as follows:

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5-17

The company’s total fixed costs are $27,800 ($5,000 utilities + $15,000

TC = $27,800 + $10.20(x)

Garfunkel: The variable-cost component of the mixed utilities expense is

C. At a production volume of 1,300 units, Simon’s total costs are estimated to

be $41,060:

D. At a production volume of 1,300 units, Garfunkel’s total costs are estimated

to be $54,650:

36. (LO1, 2—Regression analysis)

A. Regression analysis is as follows:

Regression Statistics

Multiple R 0.998619

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ANOVA

df SS MS F

Regression 1 4292119 4292119 3612.571

B. The total variance explained by the regression line is equal to the R squared

value of 99.724 percent.

C. ($4,470 – $2,820)/(520 – 300) = $7.50 per maintenance hour

In this particular instance, high/low and regression analysis provide similar

results. That is not always the case, because regression analysis uses more

data to calculate the cost formula than does the high/low method, which uses

only two data points.

37. (LO1, 2—Regression analysis)

SUMMARY OUTPUT

Regression Statistics

Multiple R 0.977603619

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5-19

ANOVA

df SS MS F

Regression 1 670039.5006 670039.501 215.7787

Coefficients

Standard

Error t Stat P-value Significance F

Lower 95% Upper 95% Lower 95.0% Upper 95.0%

A. Budgeted maintenance costs = $2,005.12 + $3.900 (430 hours)

B. The total variance explained by the regression line is equal to the R-squared

value of 95.57 percent.

38. (LO1, 2—Regression analysis: Impact of outliers)

A. The preparation costs of $11,000 associated with 25,000 pounds in February

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B. Removing both data points should improve the predictive ability of the

regression model (the R square). The revised regression output is as follows:

SUMMARY OUTPUT

Regression Statistics

Multiple R 0.874065091

ANOVA

df SS MS F

Regression 1 83984305.37 83984305 16.18552

Coefficients Standard Error t Stat P-value

Intercept 2539.449541 4721.045089 0.5379 0.613716

Removing the two data points has a significant impact on the regression

model. The new coefficient of the intercept (the fixed cost) decreases to

39. (LO1, 2—Cost behavior, high/low method)

A. Linear feet of framing: high: 30,000 (June) low: 20,000 (Jan.)

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5-21

Number of mats: high: 10,600 (June) low: 7,100 (Jan.)

B. The two formulas are similar in their estimate of fixed costs, but give quite

different predictions when used on different months’ data. Clearly, the

number of linear feet of framing and the number of mats are not perfectly

correlated with each other or with framing costs.

40. (LO4, 5, and 6—Absorption costing versus variable costing: Benefits & calculation

of net operating income)

A. Absorption cost per unit:

Direct material $55

B. Variable cost per unit:

Direct material $55

D. The net operating income will be the same when production is equal to sales.

E. The absorption-costing method is required in order for financial statements to

comply with GAAP.

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41. (LO4, 5, and 6—Absorption costing versus variable costing: Benefits and

calculation of net operating income)

A. Direct material cost $25

B. Direct material cost $25

E. The net operating incomes will be equal when sales equal production.

F. Absorption costing is required by GAAP.

42. (LO4, 5, and 6—Absorption versus variable costing: Benefits and calculation of

net operating income)

A. Direct materials $ 70

B. Variable-costing income statement

Sales $ 3,600,000

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C. Variable costing $105

Fixed overhead per unit 25 ($500,000/20,000 = 25)

Total $130

D. Absorption-costing income statement

E. The two incomes are different because sales and production are not equal.

The income is different by the amount of fixed overhead per unit times the

F. In this case, variable-costing income would be higher by $55,560.

Cases

43. (LO1, 2—Decision focus: Comprehensive regression analysis)

A. With the following regression statistics, the cost formula would be

SUMMARY OUTPUT

Regression Statistics

Multiple R 0.474867

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ANOVA

df SS MS F

B. The regression analysis indicates that the model is not a very good predictor

E. The total cost of a cruise is likely a function of the length of the cruise as well

as the number of passengers. One way to capture that information is to

calculate the number of passenger days for each cruise by multiplying the

SUMMARY OUTPUT

Regression Statistics

ANOVA

df SS MS F

Standard

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44. (LO1, 2—Decision focus: Comprehensive regression analysis)

A. The total cost equation with hours as the independent variable is

C.

(1) Gail’s objective is to determine the “best” model.

(2) Gail’s options include basing the prediction on total hours, on the

number of orders, or on some other variable or combination of

45. (LO4, 5, and 6—Absorption costing versus variable costing: Benefits and

calculation of net operating income)

A. Crystal Glass is using variable costing because all variable costs are

deducted from sales to arrive at the contribution margin. Absorption costing

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C. The financial statements could be misleading to the bank because all other