Question : 15) The coefficient of determination is A) 22.00000. B) 12.00000. C) 2.350000. D) 0.918300. E) : 1185964

 

15) The coefficient of determination is

A) 22.00000.

B) 12.00000.

C) 2.350000.

D) 0.918300.

E) 0.437525.

 

16) Simple linear regression differs from multiple linear regression in that

A) multiple linear regression uses all available data to estimate the cost function whereas simple linear regression only uses simple data.

B) simple linear regression is limited to the use of only the outcome variables and multiple linear regression can use both outcome and predictor variables.

C) simple linear regression uses only one predictor variable and multiple linear regression uses more than one predictor variable.

D) simple linear regression uses only one outcome variable and multiple linear regression uses more than one outcome variable.

E) the lease squares technique cannot be used for simple linear regression whereas it can be used for multiple linear regression.

 

17) A major concern that arises with multiple linear regression is multicollinearity, which exists

A) in simple linear regression, when the dependent variable is not normally distributed.

B) in simple linear regression, when the r2 statistic is low.

C) in multiple linear regression, when the r2 statistic is low.

D) in multiple linear regression, when two or more independent variables are correlated with one another.

E) in multiple linear regression, when spurious correlation exists.

 

18) A Manufacturing Company uses two different independent variables in two different equations to evaluate the cost activities of the packaging department, machine-hours and number of packages. The most recent month’s results of the two regressions are as follows:

 

Machine hours:

Variable

Coefficient

Standard Error

t-Value

Constant

652.32

209.75

3.11

Predictor Variable

44.30

24.61

1.88

 

r2 = 0.29

 

Number of packages:

Variable

Coefficient

Standard Error

t-Value

Constant

65.08

75.04

2.20

Predictor Variable

4.30

2.00

2.15

 

r2 = 0.61

 

Required:

a.What are the estimating equations for each cost driver?

b.Which cost driver is best and why?

19) Newton Company used least squares regression analysis to obtain the following output:

 

Payroll Department Cost

Explained by Number of Employees

Constant$5,800

Standard error of Y estimate630

r20.8924

Number of observations20

 

X coefficient(s)$1.902

Standard error of coefficient(s)0.0966

 

Required:

a.What is the total fixed cost?

b.What is the variable cost per employee?

c.Prepare the linear cost function.

d.What is the coefficient of determination?  Comment on the goodness of fit.

 

 

20) Schotte Manufacturing Company uses two different independent variables (machine-hours and number of packages) in two different equations to evaluate costs of the packaging department. The most recent results of the two regressions are as follows:

 

Machine-hours:

VariableCoefficientStandard Errort-Value

Constant$748.30$341.202.19

Predictor Variable $52.90$35.201.50

 

r2 = 0.33

 

Number of packages:

VariableCoefficientStandard Errort-Value

Constant$242.90$75.043.24

Predictor Variable$5.60$2.002.80

 

r2 = 0.73

 

Required:

a.What are the estimating equations for each cost driver?

b.Which cost driver is best and why?