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Exam 3: Cost Behaviour

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Question 41

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Which of the following statements is true regarding regression analysis?

A) It is usually the most accurate technique used to determine equivalent units.
B) It is usually the most accurate technique used to determine net income.
C) It is usually the most accurate technique used to determine the total units of production.
D) It is usually the most accurate technique used to determine mixed cost behaviour.

E) A) and B)
F) A) and C)

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Question 42

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Lockhart Products produces a single product.During 2009 the company incurred the following costs: $\begin{array}{lr} \text { Variable product costs } & \text { \$ 8.00 per unit } \\ \text { Variable period costs } & \text {\( \$ 2.00 \) per unit } \\ \text {Total fixed product costs } &\$21000\\ \text { Total fixed period costs } &\$10000\\\end{array}$ Lockhart had no units in beginning inventory.During 2009,6000 units were produced and 5000 units were sold.Which of the following statements is true when comparing net income using absorption versus variable costing?

A) Net income will be $3500 higher using absorption costing than using variable costing.
B) Net income will be $3500 lower using absorption costing than using variable costing.
C) Net income will be $4200 higher using absorption costing than using variable costing.
D) Net income will be $4200 lower using absorption costing than using variable costing.

E) None of the above
F) B) and C)

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Question 43

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A cost that has both a fixed and variable component is called a:

Cornell Products Cornell Products has the following cost information available for 2009: $\begin{array} { l r } \text { Direct materials } & \$ 1.00 \text { per unit } \\\text { Direct labour } & \$ 2.00 \text { per unit } \\\text { Variable manufacturing overhead } & \$ 1.50 \text { per unit } \\\text { Variable selling and administrative costs } & \$ 50 \text { per unit } \\\text { Fixed manufacturing overhead } & \$ 30000 \\\text { Fixed selling and administrative costs } & \$ 25000\end{array}$ During 2009, Cornell produced 6000 units out of which 5400 units were sold for $20 each. -What is net income under absorption costing?

Which of the following types of costs are the most likely to be classified as fixed?

The after-tax benefit of a taxable cash receipt can be calculated as follows:

Bob’s Burgers currently produces and sells 4000 burgers per month with the following costs: $\begin{array}{ll}\text { Variable costs } & \$ .50 \text { per unit } \\\text { Fixed costs } & \$ 2000\end{array}$ Bob has recently switched food suppliers and anticipates that variable costs will decrease by $.05 per unit. In addition, Bob has renegotiated his store lease and fixed costs will be dropping by $40 per month. -What will be Bob's new cost equation?

B & B Manufacturing B & B Manufacturing produces a single product. Last year, the company produced 10 000 units out of which 9500 were sold. There were no units in beginning inventory. The company had the following costs: $\begin{array}{cr}\underline{\text { Variable costs per unit: }}\\\text { Production } & \$ 6.00 \\\text { Selling and administrative } & \$ 2.00 \\\underline{\text { Fixed costs (total) :} } & \\ \text { Production } & \$ 15000 \\\text { Selling and administrative } &\$ 10000 \end{array}$ -What is the unit product cost using variable costing?

The primary difference between variable and absorption costing is the treatment of:

You run a regression analysis and receive the following results: SUMMARY OUTPUT $\begin{array}{l}\begin{array} { l r } \hline{ \text { Regression Statistics } } \\\hline \text { Multiple R } & 0.88000000 \\\text { R Square } & 0.78219168 \\\text { Adjusted R Square } & 0.70958891 \\\text { Standard Error } & 1165.19000 \\\text { Observations } & 5 \\\hline\end{array}\\\\\begin{array} { l c r c c r } \hline & d f & S S & M S & F & \text { Significance } F \\\hline \text { Regression } & 1 & 14626984.4 & 1 \mathrm { E } + 07 & 10.7736 & 0.0463451 \\\text { Residual } & 3 & 4073015.604 & 1 \mathrm { E } + 06 & & \\\text { Total } & 4 & 18700000 & & & \\\hline\end{array}\\\\\begin{array} { l r r r c } \hline & \text { Coefficients } & \text { Standard Error } & t \text { Stat } & P \text {-value } \\\hline \text { Intercept } & 16146.37 & 8167.49 & 1.977 & 0.14249 \\\text { X Variable 1 } & 2.380 & 0.730 & 3.282 & 0.04635 \\\hline\end{array}\end{array}$ -To the nearest dollar,what would be the estimated total costs if 500 units were produced?

You run a regression analysis and receive the following results: SUMMARY OUTPUT $\begin{array}{l}\begin{array} { l r } \hline{ \text { Regression Statistics } } \\\hline \text { Multiple R } & 0.88000000 \\\text { R Square } & 0.78219168 \\\text { Adjusted R Square } & 0.70958891 \\\text { Standard Error } & 1165.19000 \\\text { Observations } & 5 \\\hline\end{array}\\\\\begin{array} { l c r c c r } \hline & d f & S S & M S & F & \text { Significance } F \\\hline \text { Regression } & 1 & 14626984.4 & 1 \mathrm { E } + 07 & 10.7736 & 0.0463451 \\\text { Residual } & 3 & 4073015.604 & 1 \mathrm { E } + 06 & & \\\text { Total } & 4 & 18700000 & & & \\\hline\end{array}\\\\\begin{array} { l r r r c } \hline & \text { Coefficients } & \text { Standard Error } & t \text { Stat } & P \text {-value } \\\hline \text { Intercept } & 16146.37 & 8167.49 & 1.977 & 0.14249 \\\text { X Variable 1 } & 2.380 & 0.730 & 3.282 & 0.04635 \\\hline\end{array}\end{array}$ -When using regression analysis to predict mixed cost behaviour,which of the following would be the independent variable?

You run a regression analysis and receive the following results: SUMMARY OUTPUT $\begin{array}{l}\begin{array} { l r } \hline{ \text { Regression Statistics } } \\\hline \text { Multiple R } & 0.88000000 \\\text { R Square } & 0.78219168 \\\text { Adjusted R Square } & 0.70958891 \\\text { Standard Error } & 1165.19000 \\\text { Observations } & 5 \\\hline\end{array}\\\\\begin{array} { l c r c c r } \hline & d f & S S & M S & F & \text { Significance } F \\\hline \text { Regression } & 1 & 14626984.4 & 1 \mathrm { E } + 07 & 10.7736 & 0.0463451 \\\text { Residual } & 3 & 4073015.604 & 1 \mathrm { E } + 06 & & \\\text { Total } & 4 & 18700000 & & & \\\hline\end{array}\\\\\begin{array} { l r r r c } \hline & \text { Coefficients } & \text { Standard Error } & t \text { Stat } & P \text {-value } \\\hline \text { Intercept } & 16146.37 & 8167.49 & 1.977 & 0.14249 \\\text { X Variable 1 } & 2.380 & 0.730 & 3.282 & 0.04635 \\\hline\end{array}\end{array}$ -To the nearest dollar,what would be the estimated total costs if 3000 units were produced?

As production increases,variable costs per unit ____.

Which of the following statements is false regarding regression analysis?

____ are costs that do not change in total when production volume increases or decreases within the relevant range.

For each of the following statements,fill in the blank with either the word increase,decrease,or stay the same. a.As production increases,total fixed costs ______________. b.As production increases,fixed costs per unit _____________. c.As production decreases,variable costs per unit _____________. d.As production decreases,total variable costs _______________.

Hellman Manufacturing has the following cost information available for 2009: $\begin{array}{lr} \text { Direct materials } &\text { \$ 6.00 per unit}\\ \text { Direct labour } &\text {\( \$ 4.00 \) per unit}\\ \text { Variable manufacturing overhead} &\text {\( \$ 2.00 \) per unit}\\ \text { Variable selling and administrative costs } &\text {\( \$ 1.00 \) per unit}\\ \text { Fixed manufacturing overhead} &\$80000\\ \text {Fixed selling and administrative costs } &\$25000\\\end{array}$ During 2009,Merriman produced 12 500 units out of which 11 000 units were sold for $60 each. Required: A. Calculate Hellman's net income assuming the company uses variable costing. B. Calculate Hellman's net income assuming the company uses absorption costing

You run a regression analysis and receive the following results: SUMMARY OUTPUT $\begin{array}{l}\begin{array} { l r } \hline{ \text { Regression Statistics } } \\\hline \text { Multiple R } & 0.88000000 \\\text { R Square } & 0.78219168 \\\text { Adjusted R Square } & 0.70958891 \\\text { Standard Error } & 1165.19000 \\\text { Observations } & 5 \\\hline\end{array}\\\\\begin{array} { l c r c c r } \hline & d f & S S & M S & F & \text { Significance } F \\\hline \text { Regression } & 1 & 14626984.4 & 1 \mathrm { E } + 07 & 10.7736 & 0.0463451 \\\text { Residual } & 3 & 4073015.604 & 1 \mathrm { E } + 06 & & \\\text { Total } & 4 & 18700000 & & & \\\hline\end{array}\\\\\begin{array} { l r r r c } \hline & \text { Coefficients } & \text { Standard Error } & t \text { Stat } & P \text {-value } \\\hline \text { Intercept } & 16146.37 & 8167.49 & 1.977 & 0.14249 \\\text { X Variable 1 } & 2.380 & 0.730 & 3.282 & 0.04635 \\\hline\end{array}\end{array}$ -What would be the equation to predict total mixed costs?

After-tax net income can be calculated as follows:

Label whether each of the following costs is most likely fixed (F)or variable (V). $\begin{array}{lc} \text { Direct materials} &\underline{\quad\quad}\\ \text { Factory rent} &\underline{\quad\quad}\\ \text {Sales commissions expense } &\underline{\quad\quad}\\ \text { Direct labour } &\underline{\quad\quad}\\ \text { Depreciation on factory building } &\underline{\quad\quad}\\\end{array}$