Fundamentals of Cost Accounting 3rd Edition by William N. Lanen, Shannon W. Anderson, Michael Maher

Exercise 32

Interpretation of Regression Results: Multiple Choice

Cortez Company is planning to introduce a new product that will sell for $96 a unit. The following manufacturing cost estimates have been made on 20,000 units to be produced the first year:

Direct materials	$800,000
Direct labor	640,000 (= $16 per hour × 40,000 hours)

Manufacturing overhead costs have not yet been estimated for the new product, but monthly data on total production and overhead costs for the past 24 months have been analyzed using simple linear regression. The following results were derived from the simple regression and provide the basis for overhead cost estimates for the new product.

Simple Regression Analysis Results
Dependent variable—Factory overhead costs Independent variable—Direct labor-hours Computed values
Intercept	$120,000
Coefficient on independent variable	$ 5.00
Coefficient of correlation	0.921
R2	0.848

Required

a. What percentage of the variation in overhead costs is explained by the independent variable?

(1) 84.8%.

(2) 45.0%.

(3) 92.1%.

(4) 8.48%.

(5) Some other amount.

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b. What is the total overhead cost for an estimated activity level of 50,000 direct labor-hours?

(1) $120,000.

(2) $370,000.

(3) $250,000.

(4) $320,000.

(5) Some other amount.

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c. 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)?

(1) $88.00.

(2) $82.00.

(3) $86.80.

(4) $72.00.

(5) Some other amount.

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d. 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.)

(1) $96.

(2) $24.

(3) $56.

(4) $14.

(5) Some other amount.

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e. What is the manufacturing cost equation implied by these results?

(1) Total cost = $640,000 + $5.00 × Number of units.

(2) Total cost = $120,000 + $86.80 × Number of units.

(3) Total cost = $120,000 + $72.00 × Number of units.

(4) Some other equation.

Step 1 of 5

a.?(1) R2 = .848 (84.8%), the explanation of variation in Y from the X regressor.