Question : Objective 10.A 1) The coefficient of determination important in explaining variances : 1216896

 

Objective 10.A

 

1) The coefficient of determination is important in explaining variances in estimating equations. For a certain estimating equation, the unexplained variation was given as 26,505. The total variation was given as 46,500. What is the coefficient of determination for the equation?

A) 0.34

B) 0.43

C) 0.57

D) 0.66

2) The Bhaskara Corporation used regression analysis to predict the annual cost of indirect materials. The results were as follows:

 

Indirect Materials Cost Explained by Units Produced

Constant$21,890

Standard error of Y estimate$4,560

r20.7832

Number of observations22

 

X coefficient(s)11.75

Standard error of coefficient(s)2.1876

 

What is the linear cost function?

A) Y = $21,890 + $11.75X

B) Y = $4,560 + $5.15X

C) Y = $20,100 + $4.60X

D) None of these answers is correct.

 

3) Craig’s Cola was to manufacture 1,000 cases of cola next week. The accountant provided the following analysis of total manufacturing costs.

 

VariableCoefficientStandard Errort-Value

Constant10071.941.39

Independent variable20091.742.18

 

r2 = 0.82

 

What is the estimated cost of producing the 1,000 cases of cola?

A) $200,100

B) $142,071

C) $100,200

D) $9,000

4) Pam’s Stables used two different independent 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:

VariableCoefficientStandard Errort-Value

Constant$913.32$198.124.61

Independent Variable$20.90$2.947.11

 

r2 = 0.56

 

Number of horses:

VariableCoefficientStandard Errort-Value

Constant$4,764.50$1,073.094.44

Independent Variable$864.98$247.143.50

 

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) $13,844,444.50

 

5) A major concern that arises with multiple regression is multicollinearity, which exists when:

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

B) in simple regression, when the R2 statistic is low

C) in multiple regression, when the R2 statistic is low

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

6) In multiple regression, when two or more independent variables are correlated with one another, the situation is known as:

A) heteroscedasticity

B) homoscedasticity

C) multicollinearity

D) autocorrelation

 

7) The coefficient of determination (r2) measures the percentage of variation in X (the independent variable) explained by Y (the dependent variable).

 

8) Generally a coefficient of determination (r2) that is higher than 0.30 indicates a goodness of fit.

 

9) Multicollinearity is a concern in multiple regression but NOT a concern in simple regression.

 

10) Multicollinearity exists in multiple regression when two or more independent variables are highly correlated with each other.