# Thompson Machine Works Regression Problem

Thompson Machine Works purchased several new, highly sophisticated machines. The production department needed some guidance with respect to qualifications needed by an operator. Is age a factor? Is the length of service as a machine operator important? In order to explore further the factors needed to estimate performance on the new machines, four variables were listed:

X1 _ Length of time employee was a machinist. X3 _ Prior on-the-job rating.

X2 _ Mechanical aptitude test score. X4 _ Age.

Performance on the new machine is designated Y.Thirty machinists were selected at

random. Data were collected for each, and their performances on the new machines

were recorded. A few results are listed in the attached file.

The equation is: Y _ 11.6 _ 0.4X1 _ 0.286X2 _ 0.112X3 _ 0.002X4

a. What is the full designation of the equation?

b. How many dependent variables are there? Independent variables?

c. What is the number 0.286 called?

d. As age increases by one year, how much does estimated performance on the new machine increase?

e. Carl Knox applied for a job on a new machine. He has been a machinist for six years, and scored 280 on the mechanical aptitude test. Carl's prior on-the-job performance rating is 97, and he is 35 years old. Estimate Carl's performance on the new machine.

See attached file for full problem description.

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#### Solution Summary

This provides a solution to a regression problem.

Excel on the topic of multiple regression

I need assistance completing this assignment in excel format

CHAPTER 13 EXERCISE 6

The owner of Maumee Ford-Mercury-Volvo wants to study the relationship between the age of a car and its selling price. Listed below is a random sample of 12 used cars sold at the dealership during the last year.

Car Age (years) Selling Price ($000) Car Age (years) Selling Price ($000)

1 9 8.1 7 8 7.6

2 7 6.0 8 11 8.0

3 11 3.6 9 10 8.0

4 12 4.0 10 12 6.0

5 8 5.0 11 6 8.6

6 7 10.0 12 6 8.0

________________________________________

Click here for the Excel Data File

a. If we want to estimate selling price on the basis of the age of the car, which variable is the dependent variable and which is the independent variable?

is the independent variable and is the dependent variable.

b-1. Determine the correlation coefficient. (Negative amounts should be indicated by a minus sign. Round your answers to 3 decimal places.)

X Y ( )2 ( )2 ( )( )

9.0 8.1

1.192 0.007 1.420 0.099

7.0 6.0

-0.908 3.674 0.825 1.741

11.0 3.6 2.083

4.340 10.945 -6.892

12.0 4.0 3.083

9.507 8.458 -8.967

8.0 5.0 -0.917 -1.908

3.642 1.749

7.0 10.0 -1.917 3.092

9.558 -5.926

8.0 7.6 -0.917 0.692 0.840

-0.634

11.0 8.0 2.083 1.092 4.340

2.274

10.0 8.0 1.083 1.092 1.174 1.192

12.0 6.0 3.083 -0.908 9.507 0.825

6.0 8.6 -2.917 1.692 8.507 2.862 -4.934

6.0 8.0 -2.917 1.092 8.507 1.192 -3.184

107.000 82.900

________________________________________

=

=

sx =

sy =

r =

b-2. Determine the coefficient of determination. (Round your answer to 3 decimal places.)

c. Interpret the correlation coefficient. Does it surprise you that the correlation coefficient is negative?(Round your answer to nearest whole number.)

correlation between age of car and selling price. So, % of the variation in the selling price is explained by the variation in the age of the car.

CHAPTER 13 EXERCISE 12

The Student Government Association at Middle Carolina University wanted to demonstrate the relationship between the number of beers a student drinks and his or her blood alcohol content (BAC). A random sample of 18 students participated in a study in which each participating student was randomly assigned a number of 12-ounce cans of beer to drink. Thirty minutes after they consumed their assigned number of beers, a member of the local sheriff's office measured their blood alcohol content. The sample information is reported below.

Student Beers BAC Student Beers BAC

1 6 0.10 10 3 0.07

2 7 0.09 11 3 0.05

3 7 0.09 12 7 0.08

4 4 0.10 13 1 0.04

5 5 0.10 14 4 0.07

6 3 0.07 15 2 0.06

7 3 0.10 16 7 0.12

8 6 0.12 17 2 0.05

9 6 0.09 18 1 0.02

________________________________________

Use a statistical software package to answer the following questions.

Click here for the Excel Data File

1.

value:

10.00 points

Required information

a-1. Choose a scatter diagram that best fits the data.

CHAPTER 13 EXERCISE 14

The following sample observations were randomly selected.

Click here for the Excel Data File

X: 5 3 6 3 4 4 6 8

Y: 13 15 7 12 13 11 9 5

________________________________________

a. Determine the regression equation. (Negative amounts should be indicated by a minus sign. Round your answers to 3 decimal places.)

X Y ( )2 ( )2 ( )( )

5 13

2.375

5.641

3 15 −1.875

3.516

−8.203

6 7

13.141 −4.078

3 12 −1.875 1.375

4 13 −0.875

0.766

−2.078

4 11

0.375

0.141

6 9 1.125 −1.625

8 5

31.641 −17.578

________________________________________

=

=

sx =

sy =

r =

b =

a =

Y' = + X

b. Determine the value of when X is 7. (Round your answer to 3 decimal places.)

CHAPTER 13 EXERCISE 22

The owner of Maumee Ford-Mercury-Volvo wants to study the relationship between the age of a car and its selling price. Listed below is a random sample of 12 used cars sold at the dealership during the last year.

Car Age (years) Selling Price ($000) Car Age (years) Selling Price ($000)

1 9 8.1 7 8 7.6

2 7 6.0 8 11 8.0

3 11 3.6 9 10 8.0

4 12 4.0 10 12 6.0

5 8 5.0 11 6 8.6

6 7 10.0 12 6 8.0

________________________________________

Click here for the Excel Data File

The regression equation is , the sample size is 12, and the standard error of the slope is 0.23. Use the .05 significance level. Can we conclude that the slope of the regression line is less than zero?

H0 and conclude the slope is zero.

CHAPTER 13 EXERCISE 26

The owner of Maumee Ford-Mercury-Volvo wants to study the relationship between the age of a car and its selling price. Listed below is a random sample of 12 used cars sold at the dealership during the last year.

Car Age (years) Selling Price ($000)

1 9 8.1

2 7 6.0

3 11 3.6

4 12 4.0

5 8 5.0

6 7 10.0

7 8 7.6

8 11 8.0

9 10 8.0

10 12 6.0

11 6 8.6

12 6 8.0

________________________________________

Click here for the Excel Data File

a. Determine the standard error of estimate. (Round your answer to 3 decimal places.)

Standard error of estimate

b. Determine the coefficient of determination. (Round your answer to 3 decimal places.)

c. Interpret the coefficient of determination. (Round your answer to the nearest whole number.)

percent of the variation in the selling price is explained by the variation in the age of the car.

CHAPTER 14 EXERCISE2

Thompson Photo Works purchased several new, highly sophisticated processing machines. The production department needed some guidance with respect to qualifications needed by an operator. Is age a factor? Is the length of service as an operator (in years) important? In order to explore further the factors needed to estimate performance on the new processing machines, four variables were listed:

X1 = Length of time an employee was in the industry

X2 = Mechanical aptitude test score

X3 = Prior on-the-job rating

X4 = Age

Performance on the new machine is designated y.

Thirty employees were selected at random. Data were collected for each, and their performances on the new machines were recorded. A few results are:

Name Performance

on New

Machine,

Y Length of

Time in

Industry,

X1 Mechanical

Aptitude

Score,

X2 Prior

On-the-Job

Performance,

X3 Age,

X4

Mike Miraglia 112 12 312 121 52

Sue Trythall 113 2 380 123 27

________________________________________

The equation is:

= 11.6 + 0.4X1 + 0.286X2 + 0.112X3 + 0.002X4

a. What is this equation called?

Multiple regression equation

Multiple standard error of estimate

Coefficient of determination

b. How many dependent and independent variables are there?

dependent, independent

c. What is the number 0.286 called?

Regression coefficient

Coefficient of determination

Homoscedasticity

Multicollinearity

d. As age increases by one year, how much does estimated performance on the new machine increase?(Round your answer to 3 decimal places.)

e. Carl Knox applied for a job at Photo Works. He has been in the business for 6 years and scored 280 on the mechanical aptitude test. Carl's prior on-the-job performance rating is 97, and he is 35 years old. Estimate Carl's performance on the new machine. (Round your answer to 3 decimal places.)

CHAPTER 14 EXERCISE 6

Consider the ANOVA table that follows.

Analysis of Variance

Source DF SS MS F

Regression 5 3710.00 742.00 12.89

Residual Error 46 2647.38 57.55

Total 51 6357.38

________________________________________

a-1. Determine the standard error of estimate. (Round your answer to 2 decimal places.)

Standard error of estimate

a-2. About 95% of the residuals will be between what two values? (Round your answers to 2 decimal places.)

95% of the residuals will be between and .

b-1. Determine the coefficient of multiple determination. (Round your answer to 3 decimal places.)

Coefficient of multiple determination value is .

b-2. Determine the percentage variation for the independent variables. (Round your answer to 1 decimal place. Omit the "%" sign in your response.)

The independent variables explain % of the variation.

c. Determine the coefficient of multiple determination, adjusted for the degrees of freedom. (Round your answer to 3 decimal places.)

Coefficient of multiple determination

CHAPTER 14 EXERCISE 8

The following regression output was obtained from a study of architectural firms. The dependent variable is the total amount of fees in millions of dollars.

Predictor Coeff SE Coeff t p-value

Constant 7.987 2.967 2.690 0.010

X1 0.122 0.031 3.920 0.000

X2 -1.120 0.053 -2.270 0.028

X3 -0.063 0.039 -1.610 0.114

X4 0.523 0.142 3.690 0.001

X5 -0.065 0.040 -1.620 0.112

________________________________________

Analysis of Variance

Source DF SS MS F p-value

Regression 5 3710.00 742.00 12.89 0.000

Residual Error 46 2647.38 57.55

Total 51 6357.38

________________________________________

X1 is the number of architects employed by the company.

X2 is the number of engineers employed by the company.

X3 is the number of years involved with health care projects.

X4 is the number of states in which the firm operates.

X5 is the percent of the firm's work that is health care-related.

a. Write out the regression equation. (Round your answers to 3 decimal places. Negative answers should be indicated by a minus sign.)

Ŷ = + X1 + X2 + X3 + X4 + X5.

b. How large is the sample? How many independent variables are there?

Sample n

Independent variables k

________________________________________

c-1. State the decision rule for .05 significance level: H0: β1 = β2 = β3 =β4 =β5 =0; H1: Not all β's are 0.(Round your answer to 2 decimal places.)

Reject H0 if F >

c-2. Compute the value of the F statistic. (Round your answer to 2 decimal places.)

Computed value of F is

c-3. Can we conclude that the set of regression coefficients could be different from 0? Use the .05 significance level.

H0. of the regression coefficients are zero.

For X1 For X2 For X3 For X4 For X5

H0: β1 = 0 H0: β2 = 0 H0: β3 = 0 H0: β4 = 0 H0: β5 = 0

H1: β1 ≠ 0 H1: β2 ≠ 0 H1: β3 ≠ 0 H1: β4 ≠ 0 H1: β5 ≠ 0

________________________________________

d-1. State the decision rule for .05 significance level. (Round your answers to 3 decimal places.)

Reject H0 if t < or t > .

d-2. Compute the value of the test statistic. (Round your answers to 2 decimal places. Negative answers should be indicated by a minus sign.)

t − value

X1

X2

X3

X4

X5

________________________________________

d-3. Which variable would you consider eliminating?

Consider eliminating variables .

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