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Please answer with explanation of how you arrived at the issue-(Answered)

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Please answer with explanation of how you arrived at the issue


Situation 7.2.1:

 


 

A real estate builder wishes to determine how house size (House) is influenced by family income (Income), family size (Size), and

 

House size is measured in hundreds of square feet, income is measured in thousands of dollars, and education is in years. The b

 

the multiple regression. The output is provided below:

 


 

Variable

 


 

Coefficient

 


 

t-statistic

 


 

Constant

 


 

-1.633

 


 

-0.281

 


 

Income

 


 

0.448

 


 

3.954

 


 

Size

 


 

4.216

 


 

5.286

 


 

School

 


 

-0.6517

 


 

-1.509

 


 

R2 =0.75; Adjusted R2 = 0.73

 

F = 6.43

 


 

12.

 

Referring to Situation 7.2.1, which of the following values for the level of significance is the smallest for which at least two explana

 

A) 0.01

 

B) 0.025

 

C) 0.05

 

D) 0.15

 


 

Please explain how the answer was derived using a one tail or two tail?

 


 

14.

 

Referring to Situation 7.2.1, which of the following values for the level of significance is the smallest for which the regression mod

 

A) 0.00005

 

B) 0.001

 

C) 0.01

 

D) 0.05

 


 

Please explain how the answer was derived using a one tail or two tail?

 

15.

 

Referring to Situation 7.2.1, what is the predicted house size (in hundreds of square feet) for an individual

 

earning an annual income of $40,000, having a family size of four, and going to school a total of 13 years?

 


 

A) 11.43

 

B) 15.15

 

C) 24.68

 

D) 53.87

 


 

Please show the equation used and how you arrived at answer

 


 

16.

 

Referring to Situation 7.2.1, one individual in the sample had an annual income of $100,000, a family size of

 

10, and an education of 16 years. This individual owned a home with an area of 7,000 square feet (House =

 

70.00). What is the residual (in hundreds of square feet) for this data point?

 

A) 7.40

 

B) 2.52

 

C) ? 2.52

 

D) ? 4.89

 


 

Please show the equation used and how you arrived at answer.

 

A quality control expert was investigating the relationship between training (in hours) and worker efficiency

 

(number of product errors made per day). His results indicated a correlation coefficient of zero. Which of the

 

following is NOT a reason for this result?

 

A) Training is not effective at changing worker efficiency.

 

B) Correlation

 


 

can only capture positive relationships between variables not the negative

 


 

relationship apparent in the use of these variables.

 

C) The relationship between training and worker efficiency is non-linear.

 

D) A third

 


 

variable not included in the analysis may be affecting both hours of training and

 


 

worker efficiency.

 

R2, the coefficient of determination, detects the strength of the relationship between the dependent variable and

 

all independent variables.

 

A) True

 

B) False

 


 

 

Paper#9255774 | Written in 27-Jul-2016

Price : $16
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