Question 1

The equation that describes how the dependent variable y) is related to the independent variable x) is called

Accepted Answer

A)  the correlation model 
B)  the regression model 
C)  correlation analysis 
D)  None of these alternatives is correct. 
A)  the correlation model 
B)  the regression model 
C)  correlation analysis 
D)  None of these alternatives is correct.

Question 2

Exhibit 12-7
You are given the following information about y and x.
 $$\begin{array} { c c } 
\text { Dependent Varinble } Y )& \text { Independent Varinble X)} \ \end{array}$$  5 4
7 6
9 2
11 4
-Refer to Exhibit 12-7. The least squares estimate of b? intercept) equals

Accepted Answer

A)  -10 
B)  10 
C)  0.5 
D)  -0.5 
A)  -10 
B)  10 
C)  0.5 
D)  -0.5

Question 3

Exhibit 12-5
The following information regarding a dependent variable Y) and an independent variable X) is provided.
 $\begin{array} { l l } 
Y&X\
1&1\2&2\3&3&\4&4\5&5
\end{array}$
-Refer to Exhibit 12-5. The coefficient of correlation is

Accepted Answer

A)  0 
B)  -1 
C)  0.5 
D)  1 
A)  0 
B)  -1 
C)  0.5 
D)  1

Question 4

Exhibit 12-10
The following information regarding a dependent variable Y and an independent variable X is provided.
 $$\begin{array} { l } 
\mathrm { n } = 4 \
\Sigma \mathrm { X } = 16 \
\Sigma \mathrm { Y } = 28 \
\Sigma \mathrm { Y } - { \bar { Y )} } \mathrm { X } - \bar { X } ) = - 8 \
\Sigma \mathrm { X } - \bar { X } ) ^ { 2 } = 8 \
\mathrm { SST } = 42 \
\mathrm { SSE } = 34
\end{array}$$
-Refer to Exhibit 12-10. The MSE is

Accepted Answer

A)  17 
B)  8 
C)  34 
D)  42 
A)  17 
B)  8 
C)  34 
D)  42

Question 5

The following data shows the yearly income in $1,000) and age of a sample of seven individuals.
 $\begin{array}{ll}\text { Income in } \$ 1,000 \text { ) }&\text { Age }\
20 & 18 \
24 & 20 \
24 & 23 \
25 & 34 \
26 & 24 \
27 & 27 \
34 & 77
\end{array}$ 
a. Develop the least squares regression equation.
b. Estimate the yearly income of a 30-year-old individual.
c. Compute the coefficient of determination.
d. Use a t test to determine whether the slope is significantly different from zero. Let α = 0.05.
e. At 95% confidence, perform an F test and determine whether or not the model is significant.

Accepted Answer

a. @#IMG-DLM& = 16.204 + 0.3848X 
b. $27,748
c. 0.

Question 6

In a regression analysis, the coefficient of correlation is 0.16. The coefficient of determination in this situation is

Accepted Answer

A)  0.4000 
B)  0.0256 
C)  4 
D)  2.56 
A)  0.4000 
B)  0.0256 
C)  4 
D)  2.56

Question 7

Regression analysis was applied between sales Y in $1,000) and advertising X in $100), and the following estimated regression equation was obtained. $\hat { Y }$ = 80 + 6.2 X
Based on the above estimated regression line, if advertising is $10,000, then the point estimate for sales in dollars) is

Accepted Answer

A)  $62,080 
B)  $142,000 
C)  $700 
D)  $700,000 
A)  $62,080 
B)  $142,000 
C)  $700 
D)  $700,000

Question 8

A regression analysis between sales in $1000) and price in dollars) resulted in the following equation = 60 - 8X
$\hat { Y }$ The above equation implies that an

Accepted Answer

A)  increase of $1 in price is associated with a decrease of $8 in sales 
B)  increase of $8 in price is associated with an decrease of $52,000 in sales 
C)  increase of $1 in price is associated with a decrease of $52 in sales 
D)  increase of $1 in price is associated with a decrease of $8000 in sales 
A)  increase of $1 in price is associated with a decrease of $8 in sales 
B)  increase of $8 in price is associated with an decrease of $52,000 in sales 
C)  increase of $1 in price is associated with a decrease of $52 in sales 
D)  increase of $1 in price is associated with a decrease of $8000 in sales

Question 9

Exhibit 12-8
The following information regarding a dependent variable Y and an independent variable X is provided
 $$\begin{array} { l } 
\mathrm { n } = 4 \
\Sigma \mathrm { X } = 90 \
\Sigma \mathrm { Y } = 340 \
\Sigma \mathrm { Y } -  { \bar { Y) } \mathrm { X } } - \bar { X } ) = - 156 \
\Sigma \mathrm { X } - \bar { X } ) ^ { 2 } = 234 \
\Sigma \mathrm { Y } - \bar { Y } ) ^ { 2 } = 1974 \
\mathrm { SSR } = 104
\end{array}$$
-Refer to Exhibit 12-8. The mean square error MSE) is

Accepted Answer

A)  1870 
B)  13 
C)  1974 
D)  935 
A)  1870 
B)  13 
C)  1974 
D)  935

Question 10

If the coefficient of correlation is a positive value, then

Accepted Answer

A)  the intercept must also be positive 
B)  the coefficient of determination can be either negative or positive, depending on the value of the slope 
C)  the regression equation could have either a positive or a negative slope 
D)  the slope of the line must be positive 
A)  the intercept must also be positive 
B)  the coefficient of determination can be either negative or positive, depending on the value of the slope 
C)  the regression equation could have either a positive or a negative slope 
D)  the slope of the line must be positive

Question 11

In simple linear regression analysis, which of the following is not true?

Accepted Answer

A)  The F test and the t test yield the same conclusion. 
B)  The F test and the t test may or may not yield the same conclusion. 
C)  The relationship between X and Y is represented by means of a straight line. 
D)  The value of F = t2. 
A)  The F test and the t test yield the same conclusion. 
B)  The F test and the t test may or may not yield the same conclusion. 
C)  The relationship between X and Y is represented by means of a straight line. 
D)  The value of F = t2.

Question 12

Exhibit 12-3
You are given the following information about y and x.
 $\begin{array}{cc}
\text { Dependent Variable Y) }&\text { Independent Variable } \mathbf{X} \text { ) }\
12 & 4 \
3 & 6 \
7 & 2 \
6 & 4
\end{array}$
-Refer to Exhibit 12-3. The coefficient of determination equals

Accepted Answer

A)  -0.4364 
B)  0.4364 
C)  -0.1905 
D)  0.1905 
A)  -0.4364 
B)  0.4364 
C)  -0.1905 
D)  0.1905

Question 13

Exhibit 12-1
The following information regarding a dependent variable Y) and an independent variable X) is provided.
 $\begin{array} { l l } 
Y&X\4&2\3&1\4&4\6&3\8&5
\end{array}$ SSE = 6
SST = 16
-Refer to Exhibit 12-1. The least squares estimate of the Y intercept is

Accepted Answer

A)  1 
B)  2 
C)  3 
D)  4 
A)  1 
B)  2 
C)  3 
D)  4

Question 14

The interval estimate of an individual value of y for a given value of x is

Accepted Answer

A)  prediction interval estimate 
B)  confidence interval estimate 
C)  average regression 
D)  x versus y correlation interval 
A)  prediction interval estimate 
B)  confidence interval estimate 
C)  average regression 
D)  x versus y correlation interval

Question 15

In regression analysis, the unbiased estimate of the variance is

Accepted Answer

A)  coefficient of correlation 
B)  coefficient of determination 
C)  mean square error 
D)  slope of the regression equation 
A)  coefficient of correlation 
B)  coefficient of determination 
C)  mean square error 
D)  slope of the regression equation

Question 16

Exhibit 12-1
The following information regarding a dependent variable Y) and an independent variable X) is provided.
 $\begin{array} { l l } 
Y&X\4&2\3&1\4&4\6&3\8&5
\end{array}$ SSE = 6
SST = 16
-Refer to Exhibit 12-1. The MSE is

Accepted Answer

A)  1 
B)  2 
C)  3 
D)  4 
A)  1 
B)  2 
C)  3 
D)  4

Question 17

Exhibit 12-6
For the following data the value of SSE = 0.4130.
 $$\begin{array} { c c } 
\text { Dependent Varinble } Y )& \text { Independent Varinble X)} \
15 & 4 \
17 & 6 \
23 & 2 \
17 & 4
\end{array}$$
-Refer to Exhibit 12-6. The total sum of squares SST) equals

Accepted Answer

A)  36 
B)  18 
C)  9 
D)  1296 
A)  36 
B)  18 
C)  9 
D)  1296

Question 18

Exhibit 12-7
You are given the following information about y and x.
 $$\begin{array} { c c } 
\text { Dependent Varinble } Y )& \text { Independent Varinble X)} \ \end{array}$$  5 4
7 6
9 2
11 4
-Refer to Exhibit 12-7. The sample correlation coefficient equals

Accepted Answer

A)  0.3162 
B)  -0.3162 
C)  0.10 
D)  -0.10 
A)  0.3162 
B)  -0.3162 
C)  0.10 
D)  -0.10

Question 19

Exhibit 12-6
For the following data the value of SSE = 0.4130.
 $$\begin{array} { c c } 
\text { Dependent Varinble } Y )& \text { Independent Varinble X)} \
15 & 4 \
17 & 6 \
23 & 2 \
17 & 4
\end{array}$$
-Refer to Exhibit 12-6. The slope of the regression equation is

Accepted Answer

A)  18 
B)  24 
C)  0.707 
D)  -1.5 
A)  18 
B)  24 
C)  0.707 
D)  -1.5

Question 20

In a regression analysis if SST = 4500 and SSE = 1575, then the coefficient of determination is

Accepted Answer

A)  0.35 
B)  0.65 
C)  2.85 
D)  0.45 
A)  0.35 
B)  0.65 
C)  2.85 
D)  0.45

The equation that describes how the dependent variable y) is related to the independent variable x) is called

Exhibit 12-7 You are given the following information about y and x. Dependent Varinble Y) Independent Varinble X) 5 4 7 6 9 2 11 4 -Refer to Exhibit 12-7. The least squares estimate of b? intercept) equals

Exhibit 12-5 The following information regarding a dependent variable Y) and an independent variable X) is provided. Y X 1 1 2 2 3 3 4 4 5 5 -Refer to Exhibit 12-5. The coefficient of correlation is

Exhibit 12-10 The following information regarding a dependent variable Y and an independent variable X is provided. =4 \Sigma=16 \Sigma=28 \Sigma- -)=-8 \Sigma-=8 =42 =34 -Refer to Exhibit 12-10. The MSE is

In a regression analysis, the coefficient of correlation is 0.16. The coefficient of determination in this situation is

Regression analysis was applied between sales Y in $1,000) and advertising X in $100), and the following estimated regression equation was obtained. $\hat { Y }$ = 80 + 6.2 X Based on the above estimated regression line, if advertising is $10,000, then the point estimate for sales in dollars) is

A regression analysis between sales in $1000) and price in dollars) resulted in the following equation = 60 - 8X $\hat { Y }$ The above equation implies that an

Exhibit 12-8 The following information regarding a dependent variable Y and an independent variable X is provided =4 \Sigma=90 \Sigma=340 \Sigma- -)=-156 \Sigma-=234 \Sigma-=1974 =104 -Refer to Exhibit 12-8. The mean square error MSE) is

If the coefficient of correlation is a positive value, then

In simple linear regression analysis, which of the following is not true?

Exhibit 12-3 You are given the following information about y and x. Dependent Variable Y) Independent Variable ) 12 4 3 6 7 2 6 4 -Refer to Exhibit 12-3. The coefficient of determination equals

Exhibit 12-1 The following information regarding a dependent variable Y) and an independent variable X) is provided. Y X 4 2 3 1 4 4 6 3 8 5 SSE = 6 SST = 16 -Refer to Exhibit 12-1. The least squares estimate of the Y intercept is

The interval estimate of an individual value of y for a given value of x is

In regression analysis, the unbiased estimate of the variance is

Exhibit 12-1 The following information regarding a dependent variable Y) and an independent variable X) is provided. Y X 4 2 3 1 4 4 6 3 8 5 SSE = 6 SST = 16 -Refer to Exhibit 12-1. The MSE is

Exhibit 12-6 For the following data the value of SSE = 0.4130. Dependent Varinble Y) Independent Varinble X) 15 4 17 6 23 2 17 4 -Refer to Exhibit 12-6. The total sum of squares SST) equals

Exhibit 12-7 You are given the following information about y and x. Dependent Varinble Y) Independent Varinble X) 5 4 7 6 9 2 11 4 -Refer to Exhibit 12-7. The sample correlation coefficient equals

Exhibit 12-6 For the following data the value of SSE = 0.4130. Dependent Varinble Y) Independent Varinble X) 15 4 17 6 23 2 17 4 -Refer to Exhibit 12-6. The slope of the regression equation is

In a regression analysis if SST = 4500 and SSE = 1575, then the coefficient of determination is

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Exam 12: Simple Linear Regression

The equation that describes how the dependent variable y) is related to the independent variable x) is called

Exhibit 12-7 You are given the following information about y and x. Dependent Varinble Y) Independent Varinble X) 5 4 7 6 9 2 11 4 -Refer to Exhibit 12-7. The least squares estimate of b? intercept) equals

Exhibit 12-5 The following information regarding a dependent variable Y) and an independent variable X) is provided. Y X 1 1 2 2 3 3 4 4 5 5 -Refer to Exhibit 12-5. The coefficient of correlation is

Exhibit 12-10 The following information regarding a dependent variable Y and an independent variable X is provided. =4 \Sigma=16 \Sigma=28 \Sigma- -)=-8 \Sigma-=8 =42 =34 -Refer to Exhibit 12-10. The MSE is

In a regression analysis, the coefficient of correlation is 0.16. The coefficient of determination in this situation is

Regression analysis was applied between sales Y in $1,000) and advertising X in $100), and the following estimated regression equation was obtained. Y^\hat { Y }Y^ = 80 + 6.2 X Based on the above estimated regression line, if advertising is $10,000, then the point estimate for sales in dollars) is

A regression analysis between sales in $1000) and price in dollars) resulted in the following equation = 60 - 8X Y^\hat { Y }Y^ The above equation implies that an

Exhibit 12-8 The following information regarding a dependent variable Y and an independent variable X is provided =4 \Sigma=90 \Sigma=340 \Sigma- -)=-156 \Sigma-=234 \Sigma-=1974 =104 -Refer to Exhibit 12-8. The mean square error MSE) is

If the coefficient of correlation is a positive value, then

In simple linear regression analysis, which of the following is not true?

Exhibit 12-3 You are given the following information about y and x. Dependent Variable Y) Independent Variable ) 12 4 3 6 7 2 6 4 -Refer to Exhibit 12-3. The coefficient of determination equals

Exhibit 12-1 The following information regarding a dependent variable Y) and an independent variable X) is provided. Y X 4 2 3 1 4 4 6 3 8 5 SSE = 6 SST = 16 -Refer to Exhibit 12-1. The least squares estimate of the Y intercept is

The interval estimate of an individual value of y for a given value of x is

In regression analysis, the unbiased estimate of the variance is

Exhibit 12-1 The following information regarding a dependent variable Y) and an independent variable X) is provided. Y X 4 2 3 1 4 4 6 3 8 5 SSE = 6 SST = 16 -Refer to Exhibit 12-1. The MSE is

Exhibit 12-6 For the following data the value of SSE = 0.4130. Dependent Varinble Y) Independent Varinble X) 15 4 17 6 23 2 17 4 -Refer to Exhibit 12-6. The total sum of squares SST) equals

Exhibit 12-7 You are given the following information about y and x. Dependent Varinble Y) Independent Varinble X) 5 4 7 6 9 2 11 4 -Refer to Exhibit 12-7. The sample correlation coefficient equals

Exhibit 12-6 For the following data the value of SSE = 0.4130. Dependent Varinble Y) Independent Varinble X) 15 4 17 6 23 2 17 4 -Refer to Exhibit 12-6. The slope of the regression equation is

In a regression analysis if SST = 4500 and SSE = 1575, then the coefficient of determination is

Data and Statistics

Descriptive Statistics: Tabular and Graphical Displays

Descriptive Statistics: Numerical Measures

Introduction to Probability

Discrete Probability Distributions

Continuous Probability Distributions

Sampling and Sampling Distributions

Interval Estimation

Hypothesis Tests

Comparisons Involving Means, Experimental Design, and Analysis of Variance

Comparisons Involving Proportions and a Test of Independence

Multiple Regression

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Regression analysis was applied between sales Y in $1,000) and advertising X in $100), and the following estimated regression equation was obtained. $\hat { Y }$ = 80 + 6.2 X Based on the above estimated regression line, if advertising is $10,000, then the point estimate for sales in dollars) is

A regression analysis between sales in $1000) and price in dollars) resulted in the following equation = 60 - 8X $\hat { Y }$ The above equation implies that an