Question 1

In a regression and correlation analysis, if r2 = 1, then

Accepted Answer

A)  SSE must also be equal to one. 
B)  SSE must be equal to zero. 
C)  SSE can be any positive value. 
D)  SSE must be negative. 
A)  SSE must also be equal to one. 
B)  SSE must be equal to zero. 
C)  SSE can be any positive value. 
D)  SSE must be negative.

Question 2

The primary tool for determining whether the assumptions made about the regression model are appropriate is

Accepted Answer

A)  ​interval estimation. 
B)  ​significance testing. 
C)  ​least squares regression. 
D)  ​residual analysis. 
A)  ​interval estimation. 
B)  ​significance testing. 
C)  ​least squares regression. 
D)  ​residual analysis.

Question 3

A regression and correlation analysis resulted in the following information regarding a dependent variable (y) and an independent variable (x). $$\begin{array} { l l } 
\Sigma x = 90 & \sum \left( y - \frac { y } { x } \right) \left( x - { } ^ { x } \right) = 466 \
\Sigma y = 170 & \sum ( x - ) ^ { 2 } = 234 \
n = 10 & \Sigma \left( y - y ^ { 2 } \right) ^ { 2 } = 1434 \
\mathrm { SSE } = 505.98 &
\end{array}$$  The least squares estimate of the intercept or b0 equals

Accepted Answer

A)  .923. 
B)  1.991. 
C)  -1.991. 
D)  -.923. 
A)  .923. 
B)  1.991. 
C)  -1.991. 
D)  -.923.

Question 4

You are given the following information about y and x. $$\begin{array} { l l } 
\text { Dependent Variable } ( y ) & \text { Independent Variable } ( x ) \
12 & 4 \
3 & 6 \
7 & 2 \
6 & 4
\end{array}$$  The least squares estimate of the slope or b1 equals

Accepted Answer

A)  1. 
B)  -1. 
C)  -11. 
D)  11. 
A)  1. 
B)  -1. 
C)  -11. 
D)  11.

Question 5

Regression analysis was applied between sales data (y in $1000s) and advertising data (x in $100s) and the following information was obtained.   $$\hat { y }$$ = 12 + 1.8x
 
N = 17
SSR = 225
SSE = 75
Sb1 = .2683
The t statistic for testing the significance of the slope is

Accepted Answer

A)  1.80. 
B)  1.96. 
C)  6.71. 
D)  .56. 
A)  1.80. 
B)  1.96. 
C)  6.71. 
D)  .56.

Question 6

Compared to the confidence interval estimate for a particular value of y in a linear regression model, the interval estimate for an average value of y will be

Accepted Answer

A)  narrower. 
B)  wider. 
C)  the same. 
D)  easy to determine. 
A)  narrower. 
B)  wider. 
C)  the same. 
D)  easy to determine.

Question 7

Regression analysis was applied between sales (in $1000) and advertising (in $100) and the following regression function was obtained.   $\hat { y }$ = 500 + 4x
 
Based on the above estimated regression line, if advertising is $10,000, then the point estimate for sales (in dollars) is

Accepted Answer

A)  $900. 
B)  $900,000. 
C)  $40,500. 
D)  $505,000. 
A)  $900. 
B)  $900,000. 
C)  $40,500. 
D)  $505,000.

Question 8

A least squares regression line

Accepted Answer

A)  can be used to predict a value of y if the corresponding x value is given. 
B)  implies a cause-and-effect relationship between x and y. 
C)  can only be determined if a good linear relationship exists between x and y. 
D)  ensures that the predictions of y outside the range of the values of x are valid. 
A)  can be used to predict a value of y if the corresponding x value is given. 
B)  implies a cause-and-effect relationship between x and y. 
C)  can only be determined if a good linear relationship exists between x and y. 
D)  ensures that the predictions of y outside the range of the values of x are valid.

Question 9

A regression analysis between sales (y in $1000) and advertising (x in dollars) resulted in the following equation:   $\hat { y }$ = 30,000 + 4x
 
The above equation implies that an

Accepted Answer

A)  increase of $4 in advertising is associated with an increase of $4000 in sales. 
B)  increase of $1 in advertising is associated with an increase of $4 in sales. 
C)  increase of $1 in advertising is associated with an increase of $34,000 in sales. 
D)  increase of $1 in advertising is associated with an increase of $4000 in sales. 
A)  increase of $4 in advertising is associated with an increase of $4000 in sales. 
B)  increase of $1 in advertising is associated with an increase of $4 in sales. 
C)  increase of $1 in advertising is associated with an increase of $34,000 in sales. 
D)  increase of $1 in advertising is associated with an increase of $4000 in sales.

Question 10

In regression analysis, the error term $\varepsilon$is a random variable with a mean or expected value of

Accepted Answer

A)  0. 
B)  1. 
C)  $\mu$. 
D)  $\bar { x }$ . 
A)  0. 
B)  1. 
C)  $\mu$. 
D)  $\bar { x }$ .

Question 11

The coefficient of determination

Accepted Answer

A)  cannot be negative. 
B)  is the square root of the coefficient of correlation. 
C)  is the same as the coefficient of correlation. 
D)  can be negative or positive. 
A)  cannot be negative. 
B)  is the square root of the coefficient of correlation. 
C)  is the same as the coefficient of correlation. 
D)  can be negative or positive.

Question 12

If the coefficient of determination is a positive value, then the coefficient of correlation

Accepted Answer

A)  must also be positive. 
B)  must be zero. 
C)  can be either positive or negative. 
D)  can be larger than 1. 
A)  must also be positive. 
B)  must be zero. 
C)  can be either positive or negative. 
D)  can be larger than 1.

Question 13

In regression analysis, if the independent variable is measured in pounds, the dependent variable

Accepted Answer

A)  must also be in pounds. 
B)  must be in some unit of weight. 
C)  cannot be in pounds. 
D)  can be measured in any units. 
A)  must also be in pounds. 
B)  must be in some unit of weight. 
C)  cannot be in pounds. 
D)  can be measured in any units.

Question 14

In regression analysis, the independent variable is

Accepted Answer

A)  used to predict other independent variables. 
B)  used to predict the dependent variable. 
C)  the variable that is not used for prediction. 
D)  the variable that is being predicted. 
A)  used to predict other independent variables. 
B)  used to predict the dependent variable. 
C)  the variable that is not used for prediction. 
D)  the variable that is being predicted.

Question 15

You are given the following information about y and x. $$\begin{array} { l l } 
\text { Dependent Variable } ( y ) & \text { Independent Variable } ( x ) \
5 & 1 \
4 & 2 \
3 & 3 \
2 & 4 \
1 & 5
\end{array}$$   The point estimate of y when x = 2 is

Accepted Answer

A)  -10. 
B)  10. 
C)  -4. 
D)  4. 
A)  -10. 
B)  10. 
C)  -4. 
D)  4.

Question 16

If all the points of a scatter diagram lie on the least squares regression line, then the coefficient of determination for these variables based on these data

Accepted Answer

A)  is 0. 
B)  is 1. 
C)  is either 1 or -1, depending upon whether the relationship is positive or negative. 
D)  could be any value between -1 and 1. 
A)  is 0. 
B)  is 1. 
C)  is either 1 or -1, depending upon whether the relationship is positive or negative. 
D)  could be any value between -1 and 1.

Question 17

The following data show the results of the first job performance measured (in scores) of 10 employees and their grade point average. $$\begin{array} { l l } 
\text { First Job Performance } & \text { GPA } ( x ) \
\text { Score } ( y ) & 1.8 \
26 & 2.3 \
31 & 2.6 \
28 & 2.4 \
30 & 2.8 \
34 & 3.0 \
38 & 3.4 \
41 & 3.2 \
44 & 3.6 \
40 & 3.8
\end{array}$$ ​ 
a.
Develop a least squares estimated regression equation.
b.
Compute the coefficient of determination and comment on the strength of the regression relationship.
c.
Is the slope significant? Use a t test and let α = .05.
d.
At the 5% level of significance, test to determine if the model is significant (i.e., perform an F test).

Accepted Answer

​
a. @#IMG-DLM& = 8.171 + 9.4564x
b.
.83; there is

Question 18

The following information regarding a dependent variable y and an independent variable x is provided: $$\begin{array} { l l } 
\Sigma x = 90 & \sum \left( y - \frac { y } { ) } \right) ( x - x ) = - 156 \
\Sigma y = 340 & \Sigma \left( x - \frac { x } { 2 } \right) ^ { 2 } = 234 \
n = 4 & \sum ( y - y ) ^ { 2 } = 1974 \
\mathrm { SSR } = 104 &
\end{array}$$  The slope of the regression equation is

Accepted Answer

A)  -.667. 
B)  .667. 
C)  100. 
D)  -100. 
A)  -.667. 
B)  .667. 
C)  100. 
D)  -100.

Question 19

In a regression analysis, if SSE =500 and SSR = 300, then the coefficient of determination is?

Accepted Answer

A)  .600. 
B)  .167. 
C)   .625. 
D)  .375. 
A)  .600. 
B)  .167. 
C)   .625. 
D)  .375.

Question 20

If a data set produces SST =2000 and SSE = 800, then the coefficient of determination is?

Accepted Answer

A)  .4. 
B)  .6. 
C)  .5. 
D)  .8. 
A)  .4. 
B)  .6. 
C)  .5. 
D)  .8.

In a regression and correlation analysis, if r² = 1, then

The primary tool for determining whether the assumptions made about the regression model are appropriate is

A regression and correlation analysis resulted in the following information regarding a dependent variable (y) and an independent variable (x). \Sigmax=90 y- x- =466 \Sigmay=170 (x-=234 n=10 \Sigma=1434 =505.98 The least squares estimate of the intercept or b₀ equals

You are given the following information about y and x. Dependent Variable (y) Independent Variable (x) 12 4 3 6 7 2 6 4 The least squares estimate of the slope or b₁ equals

Regression analysis was applied between sales data (y in $1000s) and advertising data (x in $100s) and the following information was obtained. $\hat { y }$ = 12 + 1.8x N = 17 SSR = 225 SSE = 75 Sb₁ = .2683 The t statistic for testing the significance of the slope is

Compared to the confidence interval estimate for a particular value of y in a linear regression model, the interval estimate for an average value of y will be

Regression analysis was applied between sales (in $1000) and advertising (in $100) and the following regression function was obtained. $\hat { y }$ = 500 + 4x Based on the above estimated regression line, if advertising is $10,000, then the point estimate for sales (in dollars) is

A least squares regression line

A regression analysis between sales (y in $1000) and advertising (x in dollars) resulted in the following equation: $\hat { y }$ = 30,000 + 4x The above equation implies that an

In regression analysis, the error term $\varepsilon$ is a random variable with a mean or expected value of

The coefficient of determination

If the coefficient of determination is a positive value, then the coefficient of correlation

In regression analysis, if the independent variable is measured in pounds, the dependent variable

In regression analysis, the independent variable is

You are given the following information about y and x. Dependent Variable (y) Independent Variable (x) 5 1 4 2 3 3 2 4 1 5 The point estimate of y when x = 2 is

If all the points of a scatter diagram lie on the least squares regression line, then the coefficient of determination for these variables based on these data

The following information regarding a dependent variable y and an independent variable x is provided: \Sigmax=90 y- (x-x)=-156 \Sigmay=340 \Sigma=234 n=4 (y-y=1974 =104 The slope of the regression equation is

In a regression analysis, if SSE =500 and SSR = 300, then the coefficient of determination is?

If a data set produces SST =2000 and SSE = 800, then the coefficient of determination is?

Data and Statistics

Descriptive Statistics: Tabulargraphical

Descriptive Statistics: Numerical

Introduction to Probability

Discrete Probability Distributions

Continuous Probability Distributions

Sampling and Sampling Distributions

Interval Estimation

Hypothesis Tests

Inference About Means and Proportions With Two Populations

Inferences About Population Variances

Comparing Multiple Proportions, Test of Independence and Goodness of Fit

Experimental Design and Analysis of Variance

Multiple Regression

Filters

Exam 14: Simple Linear Regression

In a regression and correlation analysis, if r2 = 1, then

The primary tool for determining whether the assumptions made about the regression model are appropriate is

A regression and correlation analysis resulted in the following information regarding a dependent variable (y) and an independent variable (x). \Sigmax=90 y- x- =466 \Sigmay=170 (x-=234 n=10 \Sigma=1434 =505.98 The least squares estimate of the intercept or b0 equals

You are given the following information about y and x. Dependent Variable (y) Independent Variable (x) 12 4 3 6 7 2 6 4 The least squares estimate of the slope or b1 equals

Regression analysis was applied between sales data (y in $1000s) and advertising data (x in $100s) and the following information was obtained. y^\hat { y }y^​ = 12 + 1.8x N = 17 SSR = 225 SSE = 75 Sb1 = .2683 The t statistic for testing the significance of the slope is

Compared to the confidence interval estimate for a particular value of y in a linear regression model, the interval estimate for an average value of y will be

Regression analysis was applied between sales (in $1000) and advertising (in $100) and the following regression function was obtained. y^\hat { y }y^​ = 500 + 4x Based on the above estimated regression line, if advertising is $10,000, then the point estimate for sales (in dollars) is

A least squares regression line

A regression analysis between sales (y in $1000) and advertising (x in dollars) resulted in the following equation: y^\hat { y }y^​ = 30,000 + 4x The above equation implies that an

In regression analysis, the error term ε\varepsilonε is a random variable with a mean or expected value of

The coefficient of determination

If the coefficient of determination is a positive value, then the coefficient of correlation

In regression analysis, if the independent variable is measured in pounds, the dependent variable

In regression analysis, the independent variable is

You are given the following information about y and x. Dependent Variable (y) Independent Variable (x) 5 1 4 2 3 3 2 4 1 5 The point estimate of y when x = 2 is

If all the points of a scatter diagram lie on the least squares regression line, then the coefficient of determination for these variables based on these data

The following information regarding a dependent variable y and an independent variable x is provided: \Sigmax=90 y- (x-x)=-156 \Sigmay=340 \Sigma=234 n=4 (y-y=1974 =104 The slope of the regression equation is

In a regression analysis, if SSE =500 and SSR = 300, then the coefficient of determination is?

If a data set produces SST =2000 and SSE = 800, then the coefficient of determination is?

Data and Statistics

Descriptive Statistics: Tabulargraphical

Descriptive Statistics: Numerical

Introduction to Probability

Discrete Probability Distributions

Continuous Probability Distributions

Sampling and Sampling Distributions

Interval Estimation

Hypothesis Tests

Inference About Means and Proportions With Two Populations

Inferences About Population Variances

Comparing Multiple Proportions, Test of Independence and Goodness of Fit

Experimental Design and Analysis of Variance

Multiple Regression

Filters

In a regression and correlation analysis, if r² = 1, then

A regression and correlation analysis resulted in the following information regarding a dependent variable (y) and an independent variable (x). \Sigmax=90 y- x- =466 \Sigmay=170 (x-=234 n=10 \Sigma=1434 =505.98 The least squares estimate of the intercept or b₀ equals

You are given the following information about y and x. Dependent Variable (y) Independent Variable (x) 12 4 3 6 7 2 6 4 The least squares estimate of the slope or b₁ equals

Regression analysis was applied between sales data (y in $1000s) and advertising data (x in $100s) and the following information was obtained. $\hat { y }$ = 12 + 1.8x N = 17 SSR = 225 SSE = 75 Sb₁ = .2683 The t statistic for testing the significance of the slope is

Regression analysis was applied between sales (in $1000) and advertising (in $100) and the following regression function was obtained. $\hat { y }$ = 500 + 4x 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 (y in $1000) and advertising (x in dollars) resulted in the following equation: $\hat { y }$ = 30,000 + 4x The above equation implies that an

In regression analysis, the error term $\varepsilon$ is a random variable with a mean or expected value of