33) The managers of the production department have decided to use the production levels of 2010 and 2012 as examples of the highest and lowest years of operating levels. Data for those years are as follows:

2010140,000 gallons\$115,000

2012120,000 gallons\$100,000

Required:

Using the high-low method, determine the overhead cost equation for the department if gallons of chemicals are used as the cost driver?

34) The cost of the personnel department at the Miller Company has always been charged to the production departments based upon number of employees. Recently, opinions gathered from the department managers indicated that the number of new hires might also be a predictor of personnel costs to be assigned. Total personnel department costs are \$120,000.

DepartmentDepartmentDepartment

Cost DriverABC

Number of employees30025050

The number of new hires152510

Required:

Using the above data, prepare a report that contrasts the different amounts of personnel department cost that would be allocated to each of the production departments if the cost driver used is

a.number of employees.

b.the number of new hires.

c.Which cost estimation method is being used by Miller Company?

10.3   Apply OLS linear regression to analyze goodness of fit and the values of a and b to predict the MOH cost pool.

1) The use of a single predictor variable (X) to estimate the outcome variable (y) is known as

A) high-low method.

B) multiple linear regression.

C) simple linear regression.

D) singular regression.

E) least squares regression.

2) Simple linear regression analysis provides the means to evaluate a line of regression which is fitted to a plot of data and represents

A) the way costs change in respect to the predictor variable.

B) the way costs change in respect to the outcome variable.

C) the variability of expense with dollars of operation.

D) the variability of expense with dollars of production.

E) the estimated variability in costs.

3) Regression analysis differs from high-low analysis in that regression analysis

A) measures the average amount of change in the outcome variable.

B) measures the total amount of change in the outcome variable.

C) ignores the high and low observations of the outcome variable.

D) ignores non-representative data.

E) ignores both the high and low observations of the outcome variable, and non-representative data.

4) The slope of the line of regression is

A) the rate at which the outcome variable varies.

B) the rate at which the predictor variable varies.

C) the level of total fixed costs.

D) the level of total variable costs.

E) equal to the intercept.

5) Pam’s Stables used two different predictor variables (trainer hours and number of horses) in two different equations to evaluate the cost of training horses. The most recent results of the two regressions are as follows:

Trainer’s hours:

 Variable Coefficient Standard Error t-Value Constant \$913.32 \$198.12 4.61 Predictor Variable \$20.90 \$2.94 7.11

r2 = 0.56

Number of horses:

 Variable Coefficient Standard Error t-Value Constant \$4,764.50 \$1,073.09 4.44 Predictor Variable \$864.98 \$247.14 3.50

r2 = 0.63

What is the estimated total cost for the coming year if 16,000 trainer hours are incurred and the stable has 400 horses to be trained, based on the best cost driver?

A) \$99,929.09

B) \$350,756.50

C) \$335,313.32

D) \$84,233.50

E) \$47,238.12