ACCOUNTING 3334

Fall 2010
MIDTERM EXAM # 2A
Dr. Jeff Power
Suggested Solution
NOTES:
ANSWER ALL QUESTIONS IN THE SPACE PROVIDED (Back of page if necessary)
DO NOT SEPARATE THE PAGES OF THE EXAM.
YOU HAVE 75 MINUTES TO COMPLETE THE EXAM
SHOW ALL OF YOUR CALCULATIONS FOR POSSIBLE PART MARKS
PART I: Multiple Choice (Circle the most correct response) {2 points each}
The following data apply to questions 1 and 2.
Iota Inc. planned and actually manufactured 200,000 units of its single product in 2006, its first year
of operations. Variable manufacturing costs were $30 per unit of product. Planned and actual fixed
manufacturing costs were $600,000, and marketing and administrative costs totaled $400,000 in
2006. Alvin sold 120,000 units of product in 2006 at a selling price of $40 per unit.
1.
Iota’s 2006 operating income using variable costing is
a.
$440,000.
b.
$200,000
.
c.
$600,000.
d.
$800,000.
2.
Iota’s 2006 operating income using absorption costing is
3.
The proponents of throughput costing
4.
A company may experience the downward demand spiral when
5.
Of the following methods, the one that would
not
be appropriate for analyzing how a specific
cost behaves is
a.
the scattergraph method.
b.
linear programming.
c.
the industrial engineering approach.
d.
statistical regression analysis.
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6.
Theta Company derived the following cost relationship from a regression analysis of its
monthly manufacturing overhead cost.
y = $80,000 + $12X
where: y = monthly manufacturing overhead cost
X = machine hours
The standard error of estimate of the regression is $6,000. The standard time required to
manufacture one sixunit case of Tory’s single product is four machine hours. Theta applies
manufacturing overhead to production on the basis of machine hours, and its normal annual
production is 50,000 cases.
Theta’s estimated variable manufacturing overhead cost for a month in which scheduled
production is 10,000 cases would be
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 Summer '10
 farrington
 Accounting, Cost Accounting, Regression Analysis, manufacturing overhead costs, a. b. c., 12 ANOVA df Regression

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