Thane Company is interested in establishing the relationship between electricity costs and machine hours. Data have been collected and a regression analysis prepared using Excel. The monthly data and the regression output follow: $\begin{array}{lll} \text {Month}&\text {Machine Hours}&\text {Electricity Costs}\\ \text { January } & 2,500 & \$ 18,400 \\ \text { February } & 2,900 & 21,000 \\ \text { March } & 1,900& 13,500 \\ \text { April } & 3,100 & 23,000 \\ \text { May } & 3,800& 28,250 \\ \text { June } & 3,300& 22,000 \\ \text { July } & 4,100 & 24,750\\ \text { August } & 3,500 & 22,750 \\ \text { September } & 2,000 & 15,500 \\ \text { October } & 3,700 & 26,000 \\ \text { November } & 4,700 & 31,000 \\ \text { December } & 4,200 & 27,750 \end{array}$ \[\begin{array}{c} { \text { Semmary Output } } \\ { \text { Regrencion Statirticr } } \\ \begin{array}{ | l | c | } \hline \text { Multiple R } & 0.965 \\ \hline \text { R Squuare } & 0.932 \\ \hline \text { Adjusted R } ^2 & 0.925 \\ \hline \text { Standard Error } & 1,425.18 \\ \hline \text { Observations } & 12.00 \\ \hline \end{array}\end{array}\] $\begin{array}{|l|r|r|r|r|r|r|} \hline && \text { Standard } & && \text { Lower } & \text { Upper } \\ &\text { Coefficients } & \text { Error } & \text { t Stat } & \text { P-value } & 95 \% & 95 \% \\ \hline \text { Intercept } & 3,726.88 & 1,682.82 & 2.21 & 0.05 & (22.69) & 7,476.45 \\ \hline \text { Machine } & 5.77 & 0.49 & 11.7 & 0.00 & 4.67 & 6.87 \\ \text { Hours } & & & & & \\ \hline \end{array}$ - If the controller uses regression analysis to estimate costs, the cost equation for electricity costs is:

A) Electricity Costs = $1,425.18 + ($12.00 × Machine hours). B) Electricity Costs = $3,726.88 + ($1,682.82 × Machine hours). C) Electricity Costs = $1,682.82 + ($0.49 × Machine hours). D) Electricity Costs = $3,726.88 + ($5.77 × Machine hours). A) Electricity Costs = $1,425.18 + ($12.00 × Machine hours). B) Electricity Costs = $3,726.88 + ($1,682.82 × Machine hours). C) Electricity Costs = $1,682.82 + ($0.49 × Machine hours). D) Electricity Costs = $3,726.88 + ($5.77 × Machine hours).

Given the following information, compute the total number of units for the period: \[\begin{array} { l l} \text { Direct labor hours } & { 12,000 } \\ \text { Direct labor cost } & \$ 2.70 \text { per hour } \\ \text { Direct materials cost } & \$ 75 \text { per unit } \\ \text { Total maruffacturing cost } & \$ 132,600 \\ \text { Fixed overhead cost } & \$ 36,000\\ \text { Variahle owerhead cost }&\text { $ 500 \% $ of total labor cost} \end{array}\]

A) 360. B) 432. C) 640. D) 840. A) 360. B) 432. C) 640. D) 840.

Thane Company is interested in establishing the relationship between electricity costs and machine hours. Data have been collected and a regression analysis prepared using Excel. The monthly data and the regression output follow: $\begin{array}{lll} \text {Month}&\text {Machine Hours}&\text {Electricity Costs}\\ \text { January } & 2,500 & \$ 18,400 \\ \text { February } & 2,900 & 21,000 \\ \text { March } & 1,900& 13,500 \\ \text { April } & 3,100 & 23,000 \\ \text { May } & 3,800& 28,250 \\ \text { June } & 3,300& 22,000 \\ \text { July } & 4,100 & 24,750\\ \text { August } & 3,500 & 22,750 \\ \text { September } & 2,000 & 15,500 \\ \text { October } & 3,700 & 26,000 \\ \text { November } & 4,700 & 31,000 \\ \text { December } & 4,200 & 27,750 \end{array}$ \[\begin{array}{c} { \text { Summary Output } } \\ { \text { Regression Statistics } } \\ \begin{array}{ | l | c | } \hline \text { Multiple R } & 0.965 \\ \hline \text { R Squuare } & 0.932 \\ \hline \text { Adjusted R } ^2 & 0.925 \\ \hline \text { Standard Error } & 1,425.18 \\ \hline \text { Observations } & 12.00 \\ \hline \end{array}\end{array}\] $\begin{array}{|l|r|r|r|r|r|r|} \hline && \text { Standard } & && \text { Lower } & \text { Upper } \\ &\text { Coefficients } & \text { Error } & \text { t Stat } & \text { P-value } & 95 \% & 95 \% \\ \hline \text { Intercept } & 3,726.88 & 1,682.82 & 2.21 & 0.05 & (22.69) & 7,476.45 \\ \hline \text { Machine } & 5.77 & 0.49 & 11.7 & 0.00 & 4.67 & 6.87 \\ \text { Hours } & & & & & \\ \hline \end{array}$ - If the controller uses regression analysis to estimate costs, the estimate of the fixed portion of electricity costs is:

A) Fixed Cost = $5.77. B) Fixed Cost = $1,682.82. C) Fixed Cost = $1,425.18. D) Fixed Cost = $3,726.88 A) Fixed Cost = $5.77. B) Fixed Cost = $1,682.82. C) Fixed Cost = $1,425.18. D) Fixed Cost = $3,726.88

Thane Company is interested in establishing the relationship between electricity costs and machine hours. Data have been collected and a regression analysis prepared using Excel. The monthly data and the regression output follow: $\begin{array}{lll} \text {Month}&\text {Machine Hours}&\text {Electricity Costs}\\ \text { January } & 2,500 & \$ 18,400 \\ \text { February } & 2,900 & 21,000 \\ \text { March } & 1,900& 13,500 \\ \text { April } & 3,100 & 23,000 \\ \text { May } & 3,800& 28,250 \\ \text { June } & 3,300& 22,000 \\ \text { July } & 4,100 & 24,750\\ \text { August } & 3,500 & 22,750 \\ \text { September } & 2,000 & 15,500 \\ \text { October } & 3,700 & 26,000 \\ \text { November } & 4,700 & 31,000 \\ \text { December } & 4,200 & 27,750 \end{array}$ \[\begin{array}{c} { \text { Summary Output } } \\ { \text { Regression Statistics } } \\ \begin{array}{ | l | c | } \hline \text { Multiple R } & 0.965 \\ \hline \text { R Squuare } & 0.932 \\ \hline \text { Adjusted R } ^2 & 0.925 \\ \hline \text { Standard Error } & 1,425.18 \\ \hline \text { Observations } & 12.00 \\ \hline \end{array}\end{array}\] $\begin{array}{|l|r|r|r|r|r|r|} \hline && \text { Standard } & && \text { Lower } & \text { Upper } \\ &\text { Coefficients } & \text { Error } & \text { t Stat } & \text { P-value } & 95 \% & 95 \% \\ \hline \text { Intercept } & 3,726.88 & 1,682.82 & 2.21 & 0.05 & (22.69) & 7,476.45 \\ \hline \text { Machine } & 5.77 & 0.49 & 11.7 & 0.00 & 4.67 & 6.87 \\ \text { Hours } & & & & & \\ \hline \end{array}$ - If the controller uses the high-low method to estimate costs, the fixed cost portion of the cost equation for electricity costs is:

A) $3,726.88. B) $1,425.18. C) $1,625.00. D) $22,825.00. A) $3,726.88. B) $1,425.18. C) $1,625.00. D) $22,825.00.

Thane Company is interested in establishing the relationship between electricity costs and machine hours. Data have been collected and a regression analysis prepared using Excel. The monthly data and the regression output follow: $\begin{array}{lll} \text {Month}&\text {Machine Hours}&\text {Electricity Costs}\\ \text { January } & 2,500 & \$ 18,400 \\ \text { February } & 2,900 & 21,000 \\ \text { March } & 1,900& 13,500 \\ \text { April } & 3,100 & 23,000 \\ \text { May } & 3,800& 28,250 \\ \text { June } & 3,300& 22,000 \\ \text { July } & 4,100 & 24,750\\ \text { August } & 3,500 & 22,750 \\ \text { September } & 2,000 & 15,500 \\ \text { October } & 3,700 & 26,000 \\ \text { November } & 4,700 & 31,000 \\ \text { December } & 4,200 & 27,750 \end{array}$ \[\begin{array}{c} { \text { Summary Output } } \\ { \text { Regression Statistics } } \\ \begin{array}{ | l | c | } \hline \text { Multiple R } & 0.965 \\ \hline \text { R Squuare } & 0.932 \\ \hline \text { Adjusted R } ^2 & 0.925 \\ \hline \text { Standard Error } & 1,425.18 \\ \hline \text { Observations } & 12.00 \\ \hline \end{array}\end{array}\] $\begin{array}{|l|r|r|r|r|r|r|} \hline && \text { Standard } & && \text { Lower } & \text { Upper } \\ &\text { Coefficients } & \text { Error } & \text { t Stat } & \text { P-value } & 95 \% & 95 \% \\ \hline \text { Intercept } & 3,726.88 & 1,682.82 & 2.21 & 0.05 & (22.69) & 7,476.45 \\ \hline \text { Machine } & 5.77 & 0.49 & 11.7 & 0.00 & 4.67 & 6.87 \\ \text { Hours } & & & & & \\ \hline \end{array}$ - If the controller uses the high-low method to estimate costs, the variable cost per machine hour is:

A) $6.25. B) $6.90. C) $5.77. D) $11.70. A) $6.25. B) $6.90. C) $5.77. D) $11.70.

Balcom Enterprises is planning to introduce a new product that will sell for $110 per unit. Manufacturing cost estimates for 20,000 units for the first year of production are: ? Direct materials $1,000,000. ? Direct labor $720,000 (based on $18 per hour × 40,000 hours). Although overhead has not be estimated for the new product, monthly data for Balcom's total production for the last two years has been analyzed using simple linear regression. The analysis results are as follows: $\begin{array}{lrr} \text {Dependent variable}&\text {Factory overhead costs}\\ \text {Independent variable}&\text {Direct labor hours}\\ \text { Intercept } & \$ 120,000 \\ \text { Coefficient on independent variable } & \$ 5.00 \\ \text { Coefficient of correlation } & 0.911 \\ \text { R }^2 & 0.814 \end{array}$ - Based on this information, 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.)

A) $14 B) $13 C) $99 D) $32 A) $14 B) $13 C) $99 D) $32

Bachmann Products, Inc., has found that new products follow a learning curve. The first two units have been completed with the following results: \[\begin{array} { | r | r | } \hline \text { Units Produced } & \text { Marginal Labor Time } \\ \hline 1 & 80.00 \\ \hline 2 & 68.00 \\ \hline \end{array}\] - How much time will be needed to complete the 8th unit?

A) 74.00 hours. B) 57.80 hours. C) 56.00 hours. D) 49.13 hours. A) 74.00 hours. B) 57.80 hours. C) 56.00 hours. D) 49.13 hours.

Exam 5: Cost Estimation

Thane Company is interested in establishing the relationship between electricity costs and machine hours. Data have been collected and a regression analysis prepared using Excel. The monthly data and the regression output follow: Month Machine Hours Electricity Costs January 2,500 \ 18,400 February 2,900 21,000 March 1,900 13,500 April 3,100 23,000 May 3,800 28,250 June 3,300 22,000 July 4,100 24,750 August 3,500 22,750 September 2,000 15,500 October 3,700 26,000 November 4,700 31,000 December 4,200 27,750 Semmary Output Regrencion Statirticr Multiple R 0.965 R Squuare 0.932 0.925 Standard Error 1,425.18 Observations 12.00 Standard Lower Upper Coefficients Error t Stat P-value 95\% 95\% Intercept 3,726.88 1,682.82 2.21 0.05 (22.69) 7,476.45 Machine 5.77 0.49 11.7 0.00 4.67 6.87 Hours - If the controller uses regression analysis to estimate costs, the cost equation for electricity costs is:

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Question 61

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: Administrative Credit Month Costs Hours July \ 129,301 250 August 82,613 115 September 225,580 1,392 October 216,394 1,000 November 258,263 1,309 December 184,445 1,112 January 219,137 1,335 February 245,000 1,373 March 209,462 1,064 April 191,925 1,123 May 249,978 1,360 June 170,41\varepsilon 420 July 128,167 315 Total \ 2,510,687 12,172 Average \ 193,130 936 The controller's office has analyzed the data and has given you the results from the regression analysis: SUMMARY OUTPUT Regression Statistics Multiple R 0.9317157 R Square 0.868094147 Adjusted R Square 0.856102705 Standard Error 20,134.92395 Observations 13 ANOVA df S S M S F Significance F Repression 1 29,349,143,514 29,349,143,514 72.3928117 3.61909-06 Residual 11 4,459,566,787 405,415,162.4 Total 12 33,808,710,301 $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} - Based on the results of the regression analysis, the estimate of administrative costs in a month with 1,000 credit hours would be: (rounded to the nearest whole dollar)$ - Based on the results of the regression analysis, the estimate of administrative costs in a month with 1,000 credit hours would be: (rounded to the nearest whole dollar)

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Question 62

Describe the effect on cost estimation of four of the following five problems: 1) missing data, 2) outliers, 3) allocated and discretionary costs, 4) inflation, or 5) mismatched time periods.

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Question 63

Given the following information, compute the total number of units for the period: Direct labor hours 12,000 Direct labor cost \ 2.70 per hour Direct materials cost \ 75 per unit Total maruffacturing cost \ 132,600 Fixed overhead cost \ 36,000 Variahle owerhead cost 500 \% of total labor cost

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Question 64

Thane Company is interested in establishing the relationship between electricity costs and machine hours. Data have been collected and a regression analysis prepared using Excel. The monthly data and the regression output follow: Month Machine Hours Electricity Costs January 2,500 \ 18,400 February 2,900 21,000 March 1,900 13,500 April 3,100 23,000 May 3,800 28,250 June 3,300 22,000 July 4,100 24,750 August 3,500 22,750 September 2,000 15,500 October 3,700 26,000 November 4,700 31,000 December 4,200 27,750 Summary Output Regression Statistics Multiple R 0.965 R Squuare 0.932 0.925 Standard Error 1,425.18 Observations 12.00 Standard Lower Upper Coefficients Error t Stat P-value 95\% 95\% Intercept 3,726.88 1,682.82 2.21 0.05 (22.69) 7,476.45 Machine 5.77 0.49 11.7 0.00 4.67 6.87 Hours - If the controller uses regression analysis to estimate costs, the estimate of the fixed portion of electricity costs is:

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Question 65

Washington Products had costs of $600,000 when sales equaled 75,000 units. When sales increased by 25,000 units, costs increased by $125,000. The selling price is $9 per unit. Required: (a.) Determine the fixed and variable portions of costs. (b.) Prepare a contribution margin income statement for a month with sales of 80,000 units.

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Question 66

Obtaining regression estimates for cost estimation requires establishing the existence of a logical relation between activities and the cost to be estimated. Which of the following is not used to refer to these activities?

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Question 67

Brewsky's is a chain of micro-breweries. Managers are interested in the costs of the stores and believe that the costs can be explained in large part by the number of customers patronizing the stores. Monthly data regarding customer visits and costs for the preceding year for one of the stores have been entered into the regression analysis and the analysis is as follows: Average monthly customer visits 1,462 Average monthly total costs \4 ,629 Regression Results Intercept \1 ,496 b coefficient \2 .08 0.86814 - Based on the data derived from the regression analysis, what are the estimated costs for 1,600 customer visits in a month? (CMA adapted)

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Question 68

Thane Company is interested in establishing the relationship between electricity costs and machine hours. Data have been collected and a regression analysis prepared using Excel. The monthly data and the regression output follow: Month Machine Hours Electricity Costs January 2,500 \ 18,400 February 2,900 21,000 March 1,900 13,500 April 3,100 23,000 May 3,800 28,250 June 3,300 22,000 July 4,100 24,750 August 3,500 22,750 September 2,000 15,500 October 3,700 26,000 November 4,700 31,000 December 4,200 27,750 Summary Output Regression Statistics Multiple R 0.965 R Squuare 0.932 0.925 Standard Error 1,425.18 Observations 12.00 Standard Lower Upper Coefficients Error t Stat P-value 95\% 95\% Intercept 3,726.88 1,682.82 2.21 0.05 (22.69) 7,476.45 Machine 5.77 0.49 11.7 0.00 4.67 6.87 Hours - If the controller uses the high-low method to estimate costs, the fixed cost portion of the cost equation for electricity costs is:

(Multiple Choice)

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Question 69

Thane Company is interested in establishing the relationship between electricity costs and machine hours. Data have been collected and a regression analysis prepared using Excel. The monthly data and the regression output follow: Month Machine Hours Electricity Costs January 2,500 \ 18,400 February 2,900 21,000 March 1,900 13,500 April 3,100 23,000 May 3,800 28,250 June 3,300 22,000 July 4,100 24,750 August 3,500 22,750 September 2,000 15,500 October 3,700 26,000 November 4,700 31,000 December 4,200 27,750 Summary Output Regression Statistics Multiple R 0.965 R Squuare 0.932 0.925 Standard Error 1,425.18 Observations 12.00 Standard Lower Upper Coefficients Error t Stat P-value 95\% 95\% Intercept 3,726.88 1,682.82 2.21 0.05 (22.69) 7,476.45 Machine 5.77 0.49 11.7 0.00 4.67 6.87 Hours - If the controller uses the high-low method to estimate costs, the variable cost per machine hour is:

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Question 70

The Ornate Company produces a single product and has total costs ranging from $321,875 (at 20,000 units) to $966,875 (at 80,000 units). Sales volume in 2020 was 32,000, and operating income was $45,125. Ornate's product is highly specialized; therefore, no units are kept in inventory. Required: (a.) Determine the cost equation for Ornate's costs. (b.) Prepare a contribution margin income statement for 2020 including separate columns for total dollars, per unit dollars, and percentages. (c.) Determine the break-even point (in units and in dollars).

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Question 71

Woodman Products, Inc., has found that new products follow a learning curve. The first two units have been completed with the following results: Units Produced Marginal Labor Time 1 112.50 2 90.00 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?

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Question 72

In general, the use of multiple independent variables increases the proportion of the variation in the dependent variable explained by the cost equation.

(True/False)

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Question 73

Brewsky's is a chain of micro-breweries. Managers are interested in the costs of the stores and believe that the costs can be explained in large part by the number of customers patronizing the stores. Monthly data regarding customer visits and costs for the preceding year for one of the stores have been entered into the regression analysis and the analysis is as follows: Average monthly customer visits 1,462 Average monthly total costs \4 ,629 Regression Results Intercept \1 ,496 b coefficient \2 .08 0.86814 - In a regression equation expressed as y = a + bx, how is the letter y best described? (CMA adapted)

(Multiple Choice)

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Question 74

Obtaining regression estimates for cost estimation requires establishing the existence of a logical relation between activities and the cost to be estimated. Which of the following is not used to refer to the cost to be estimated?

(Multiple Choice)

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Question 75

Balcom Enterprises is planning to introduce a new product that will sell for $110 per unit. Manufacturing cost estimates for 20,000 units for the first year of production are: ? Direct materials $1,000,000. ? Direct labor $720,000 (based on $18 per hour × 40,000 hours). Although overhead has not be estimated for the new product, monthly data for Balcom's total production for the last two years has been analyzed using simple linear regression. The analysis results are as follows: Dependent variable Factory overhead costs Independent variable Direct labor hours Intercept \ 120,000 Coefficient on independent variable \ 5.00 Coefficient of correlation 0.911 0.814 - Based on this information, 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.)

(Multiple Choice)

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Question 76

Bachmann Products, Inc., has found that new products follow a learning curve. The first two units have been completed with the following results: Units Produced Marginal Labor Time 1 80.00 2 68.00 - How much time will be needed to complete the 8th unit?

(Multiple Choice)

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Question 77

In general, accounting records accumulate cost information according to its behavior (i.e., variable and fixed).

(True/False)

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Question 78

Which of the following statements regarding regression analysis is (are) true? (A) One way to control the effects of a nonlinear relationship between total costs and activity is reduce the relevant range. (B) The linear cost estimate tends to understate the slope of the cost line in ranges close to capacity.

(Multiple Choice)

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Question 79

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: Administrative Credit Month Costs Hours July \ 129,301 250 August 82,613 115 September 225,580 1,392 October 216,394 1,000 November 258,263 1,309 December 184,445 1,112 January 219,137 1,335 February 245,000 1,373 March 209,462 1,064 April 191,925 1,123 May 249,978 1,360 June 170,41\varepsilon 420 July 128,167 315 Total \ 2,510,687 12,172 Average \ 193,130 936 The controller's office has analyzed the data and has given you the results from the regression analysis: SUMMARY OUTPUT Regression Statistics Multiple R 0.9317157 R Square 0.868094147 Adjusted R Square 0.856102705 Standard Error 20,134.92395 Observations 13 ANOVA df S S M S F Significance F Repression 1 29,349,143,514 29,349,143,514 72.3928117 3.61909-06 Residual 11 4,459,566,787 405,415,162.4 Total 12 33,808,710,301 $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} - Based on the results of the regression analysis, the estimate of the variable portion of administrative costs in a month with 200 credit hours would be:$ - Based on the results of the regression analysis, the estimate of the variable portion of administrative costs in a month with 200 credit hours would be:

(Multiple Choice)

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Question 80

Showing 61 - 80 of 131

Describe the effect on cost estimation of four of the following five problems: 1) missing data, 2) outliers, 3) allocated and discretionary costs, 4) inflation, or 5) mismatched time periods.

Given the following information, compute the total number of units for the period: Direct labor hours 12,000 Direct labor cost \ 2.70 per hour Direct materials cost \ 75 per unit Total maruffacturing cost \ 132,600 Fixed overhead cost \ 36,000 Variahle owerhead cost 500 \% of total labor cost

Obtaining regression estimates for cost estimation requires establishing the existence of a logical relation between activities and the cost to be estimated. Which of the following is not used to refer to these activities?

In general, the use of multiple independent variables increases the proportion of the variation in the dependent variable explained by the cost equation.

Obtaining regression estimates for cost estimation requires establishing the existence of a logical relation between activities and the cost to be estimated. Which of the following is not used to refer to the cost to be estimated?

Bachmann Products, Inc., has found that new products follow a learning curve. The first two units have been completed with the following results: Units Produced Marginal Labor Time 1 80.00 2 68.00 - How much time will be needed to complete the 8th unit?

In general, accounting records accumulate cost information according to its behavior (i.e., variable and fixed).

Cost Accounting: Information for Decision Making

Cost Concepts and Behavior

Fundamentals of Cost-Volume-Profit Analysis

Fundamentals of Cost Analysis for Decision Making

Fundamentals of Product and Service Costing

Job Costing

Process Costing

Activity-Based Costing

Fundamentals of Cost Management

Service Department and Joint Cost Allocation

Fundamentals of Management Control Systems

Planning and Budgeting

Business Unit Performance Measurement

Transfer Pricing

Fundamentals of Variance Analysis

Additional Topics in Variance Analysis

Performance Measurement to Support Business Strategy

Filters