PART 3

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.

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.

=
=
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.

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.

Use a statistical software package to answer the following questions.


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




b. Fill in the blanks below.






sx

sy

________________________________________

c. Determine the coefficient of correlation and coefficient of determination.


Coefficient of correlation

Coefficient of determination

________________________________________

c-1. State the decision rule for .01 significance level: H0: ρ ≤ 0; H1: ρ > 0.

Reject H0 if t >


c-2. Compute the value of the test statistic.

Value of the test statistic


c-3. What is the p-value? (Hint: use Megastat)

p-value


c-4. At the .01 significance level, is it reasonable to conclude that there is a positive relationship in the population between the number of beers consumed and the BAC?


H0 . There is
between beers consumed and BAC.
1.
value:
10.00 points

The following sample observations were randomly selected.


X: 5 3 6 3 4 4 6 8
Y: 13 15 7 12 13 11 9 5
________________________________________

a. Determine the regression equation.
________________________________________

=
=
sx =


sy =
r =


b =
a =


Y' = + X


b. Determine the value of when X is 7.





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.

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.

1.
value:
10.00 points

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.

________________________________________


a. Determine the standard error of estimate.

Standard error of estimate


b. Determine the coefficient of determination.




c. Interpret the coefficient of determination.

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


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:

________________________________________


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?





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.



References
eBook & Resources

1.
value:
10.00 points

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.

The independent variables explain % of the variation.


c. Determine the coefficient of multiple determination, adjusted for the degrees of freedom.

Coefficient of multiple determination


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.

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.

Reject H0 if F >



c-2. Compute the value of the F statistic.

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.

Reject H0 if t < or t > .


d-2. Compute the value of the test statistic.

t − value
X1

X2

X3

X4

X5

________________________________________

d-3. Which variable would you consider eliminating?

Consider eliminating variables
.


Answer will be sent by email as attachment.