Question 1

The proportion of SSY that is not predicted by the regression equation is equal to r2.

Accepted Answer

A) True 
 B)False  False

Question 2

Which of the following is the standard error of estimate for a linear regression equation?​

Accepted Answer

A) ​the square root of (SSresidual/(n - 2)) 
B) ​the square root of (SSresidual/(n - 3)) 
C) ​the square root of (SSregression/(n - 2)) 
D) ​the square root of (SSregression/(n - 3)) 
A) ​the square root of (SSresidual/(n - 2)) 
B) ​the square root of (SSresidual/(n - 3)) 
C) ​the square root of (SSregression/(n - 2)) 
D) ​the square root of (SSregression/(n - 3)) A

Question 3

If other factors are held constant,a larger numerical value for the Pearson correlation will result in a smaller standard error of estimate.

Accepted Answer

A) True 
 B)False  True

Question 4

The following X and Y scores produce SSX = 2 and SP = 8.What is the regression equation for predicting Y? $$\begin{array} { l l } 
\mathrm { X } & \mathrm { Y } \
\hline 1 & 2 \
2 & 3 \
3 & 10 \
\hline
\end{array}$$

Accepted Answer

A) ?Y = 0.25X + 4.5 
B) ?Y = 0.25X - 4.5 
C) ?Y = 4X + 3 
D) ?Y = 4X - 3 
A) ?Y = 0.25X + 4.5 
B) ?Y = 0.25X - 4.5 
C) ?Y = 4X + 3 
D) ?Y = 4X - 3

Question 5

For linear regression,the value of SSresidual can be computed directly by Σ(Y - )2.

Accepted Answer

A) True 
 B)False

Question 6

For either linear regression or multiple regression,the standard error of estimate is equal to the square root of MSresidual.

Accepted Answer

A) True 
 B)False

Question 7

The Pearson correlation between X1 and Y is r = 0.70.When a second variable,X2,is added to the regression equation,we obtain R2 = 0.64.How much variance for the Y scores is predicted by using only X1 as a predictor variable?​

Accepted Answer

A) ​0.06 or 6% 
B) ​0.15 or 15% 
C) ​0.49 or 49% 
D) ​0.70 or 70% 
A) ​0.06 or 6% 
B) ​0.15 or 15% 
C) ​0.49 or 49% 
D) ​0.70 or 70%

Question 8

A researcher who is evaluating the significance of a multiple regression equation with two predictor variables obtains an F-ratio with df = 2,24.How many individuals were needed to produce the sample data used to find the regression equation?​

Accepted Answer

A) 24​ 
B) ​25 
C) ​26 
D) ​27 
A) 24​ 
B) ​25 
C) ​26 
D) ​27

Question 9

The standardized form of the regression equation is zY = (beta)zX.In the equation,what is the value of beta?​

Accepted Answer

A) ​Beta is equal to the correlation between X and Y. 
B) ​Beta is equal to SP/ SSX. 
C) ​Beta is equal to r/(n - 1). 
D) ​Beta is equal to r/n. 
A) ​Beta is equal to the correlation between X and Y. 
B) ​Beta is equal to SP/ SSX. 
C) ​Beta is equal to r/(n - 1). 
D) ​Beta is equal to r/n.

Question 10

For the linear equation Y = 2X - 3,which of the following points will not be on the line?​

Accepted Answer

A) 0, 3​ 
B) ​2, 1 
C) ​3, 3 
D) ​4, 5 
A) 0, 3​ 
B) ​2, 1 
C) ​3, 3 
D) ​4, 5

Question 11

A linear regression equation is computed for a sample of n = 13 pairs of X and Y scores.For the analysis of regression testing the significance of the equation,what are the df values for the F-ratio?​

Accepted Answer

A) df = 1, 11​ 
B) ​df = 1, 12 
C) ​df = 2, 10 
D) ​df = 2, 11 
A) df = 1, 11​ 
B) ​df = 1, 12 
C) ​df = 2, 10 
D) ​df = 2, 11

Question 12

The Pearson correlation between X1 and Y is r = 0.50 and the correlation between X2 and Y is r = 0.20.How much variance for the Y scores is predicted by using both X1 and X2 as predictor variables in a multiple regression equation?​

Accepted Answer

A) ​0.25 or 25% 
B) ​0.29 or 29% 
C) ​0.70 or 70% 
D) ​It cannot be determined from the information given. 
A) ​0.25 or 25% 
B) ​0.29 or 29% 
C) ​0.70 or 70% 
D) ​It cannot be determined from the information given.

Question 13

For a linear regression,if X = MX,then the predicted Y value is MY.

Accepted Answer

A) True 
 B)False

Question 14

For which of the following correlations would the data points be most widely scattered around the regression line?​

Accepted Answer

A) ​r = 0.10 
B) ​r = 0.50 
C) ​r = 0.80 
D) ​r = 0.99 
A) ​r = 0.10 
B) ​r = 0.50 
C) ​r = 0.80 
D) ​r = 0.99

Question 15

A partial correlation measures the relationship that exists between two variables while a third variable is controlled or held constant.

Accepted Answer

A) True 
 B)False

Question 16

A researcher who is evaluating the significance of a multiple regression equation with two predictor variables obtains an F-ratio with df = 2,18.How many individuals were needed to produce the sample data used to find the regression equation?​

Accepted Answer

A) ​18 
B) ​19 
C) ​20 
D) ​21 
A) ​18 
B) ​19 
C) ​20 
D) ​21

Question 17

Suppose that a sample of n = 12 pairs of X and Y scores has SSY = 90 and a Pearson correlation of r = +0.40.
a. What proportion of the variance for the Y scores is predicted by the regression equation?
b. Does the regression equation predict a significant portion of the variance? Test with α = .05.

Accepted Answer

a.r² = 0.16 or 16% b.F = 14.4/7.56 = 1.90

Question 18

The best-fitting line is the one that has the smallest total squared error,so the resulting line is commonly called the least-squared-error solution.

Accepted Answer

A) True 
 B)False

Question 19

For a linear regression equation,the sum of the squared residuals can be computed directly by finding the difference between each Y and its predicted Y,then squaring the difference and adding the squared values.An alternative procedure is to calculate ____.​

Accepted Answer

A) r2SSY​ 
B) ​(1 - r2)SSY 
C) ​(1 + r2)SSY 
D) ​SSY/SSX 
A) r2SSY​ 
B) ​(1 - r2)SSY 
C) ​(1 + r2)SSY 
D) ​SSY/SSX

Question 20

A linear regression equation has b = 3 and a = - 6.What is the predicted value of Y for X = 4?​

Accepted Answer

A) ​ = 6 
B) ​ = -21 
C) ​ = -2 
D) ​This cannot be determined without additional information. 
A) ​ = 6 
B) ​ = -21 
C) ​ = -2 
D) ​This cannot be determined without additional information.

The proportion of SS_Y that is not predicted by the regression equation is equal to r².

Which of the following is the standard error of estimate for a linear regression equation?

If other factors are held constant,a larger numerical value for the Pearson correlation will result in a smaller standard error of estimate.

The following X and Y scores produce SS_X = 2 and SP = 8.What is the regression equation for predicting Y? 1 2 2 3 3 10

For linear regression,the value of SS_residual can be computed directly by Σ(Y - )².

For either linear regression or multiple regression,the standard error of estimate is equal to the square root of MS_residual.

The Pearson correlation between X₁ and Y is r = 0.70.When a second variable,X₂,is added to the regression equation,we obtain R² = 0.64.How much variance for the Y scores is predicted by using only X₁ as a predictor variable?

A researcher who is evaluating the significance of a multiple regression equation with two predictor variables obtains an F-ratio with df = 2,24.How many individuals were needed to produce the sample data used to find the regression equation?

The standardized form of the regression equation is z_Y = (beta)z_X.In the equation,what is the value of beta?

For the linear equation Y = 2X - 3,which of the following points will not be on the line?

A linear regression equation is computed for a sample of n = 13 pairs of X and Y scores.For the analysis of regression testing the significance of the equation,what are the df values for the F-ratio?

The Pearson correlation between X₁ and Y is r = 0.50 and the correlation between X₂ and Y is r = 0.20.How much variance for the Y scores is predicted by using both X₁ and X₂ as predictor variables in a multiple regression equation?

For a linear regression,if X = M_X,then the predicted Y value is M_Y.

For which of the following correlations would the data points be most widely scattered around the regression line?

A partial correlation measures the relationship that exists between two variables while a third variable is controlled or held constant.

A researcher who is evaluating the significance of a multiple regression equation with two predictor variables obtains an F-ratio with df = 2,18.How many individuals were needed to produce the sample data used to find the regression equation?

The best-fitting line is the one that has the smallest total squared error,so the resulting line is commonly called the least-squared-error solution.

For a linear regression equation,the sum of the squared residuals can be computed directly by finding the difference between each Y and its predicted Y,then squaring the difference and adding the squared values.An alternative procedure is to calculate ____.

A linear regression equation has b = 3 and a = - 6.What is the predicted value of Y for X = 4?

Introduction to Statistics

Frequency Distributions

Central Tendency

Variability

Z-Scores: Location of Scores and Standardized Distributions

Probability

Probability and Samples: the Distribution of Sample Means

Introduction to Hypothesis Testing

Introduction to the T Statistic

The T Test for Two Independent Samples

The T Test for Two Related Samples

Introduction to Analysis of Variance

Repeated-Measures Analysis of Variance Anova

Two-Factor Analysis of Variance Independent Measures

Correlation

The Chi-Square Statistic: Tests for Goodness of Fit and Independence

The Binomial Test

Filters

Exam 16: Introduction to Regression

The proportion of SSY that is not predicted by the regression equation is equal to r2.

Which of the following is the standard error of estimate for a linear regression equation?​

If other factors are held constant,a larger numerical value for the Pearson correlation will result in a smaller standard error of estimate.

The following X and Y scores produce SSX = 2 and SP = 8.What is the regression equation for predicting Y? 1 2 2 3 3 10

For linear regression,the value of SSresidual can be computed directly by Σ(Y - )2.

For either linear regression or multiple regression,the standard error of estimate is equal to the square root of MSresidual.

The Pearson correlation between X1 and Y is r = 0.70.When a second variable,X2,is added to the regression equation,we obtain R2 = 0.64.How much variance for the Y scores is predicted by using only X1 as a predictor variable?​

A researcher who is evaluating the significance of a multiple regression equation with two predictor variables obtains an F-ratio with df = 2,24.How many individuals were needed to produce the sample data used to find the regression equation?​

The standardized form of the regression equation is zY = (beta)zX.In the equation,what is the value of beta?​

For the linear equation Y = 2X - 3,which of the following points will not be on the line?​

A linear regression equation is computed for a sample of n = 13 pairs of X and Y scores.For the analysis of regression testing the significance of the equation,what are the df values for the F-ratio?​

The Pearson correlation between X1 and Y is r = 0.50 and the correlation between X2 and Y is r = 0.20.How much variance for the Y scores is predicted by using both X1 and X2 as predictor variables in a multiple regression equation?​

For a linear regression,if X = MX,then the predicted Y value is MY.

For which of the following correlations would the data points be most widely scattered around the regression line?​

A partial correlation measures the relationship that exists between two variables while a third variable is controlled or held constant.

A researcher who is evaluating the significance of a multiple regression equation with two predictor variables obtains an F-ratio with df = 2,18.How many individuals were needed to produce the sample data used to find the regression equation?​

The best-fitting line is the one that has the smallest total squared error,so the resulting line is commonly called the least-squared-error solution.

For a linear regression equation,the sum of the squared residuals can be computed directly by finding the difference between each Y and its predicted Y,then squaring the difference and adding the squared values.An alternative procedure is to calculate ____.​

A linear regression equation has b = 3 and a = - 6.What is the predicted value of Y for X = 4?​

Introduction to Statistics

Frequency Distributions

Central Tendency

Variability

Z-Scores: Location of Scores and Standardized Distributions

Probability

Probability and Samples: the Distribution of Sample Means

Introduction to Hypothesis Testing

Introduction to the T Statistic

The T Test for Two Independent Samples

The T Test for Two Related Samples

Introduction to Analysis of Variance

Repeated-Measures Analysis of Variance Anova

Two-Factor Analysis of Variance Independent Measures

Correlation

The Chi-Square Statistic: Tests for Goodness of Fit and Independence

The Binomial Test

Filters

The proportion of SS_Y that is not predicted by the regression equation is equal to r².

Which of the following is the standard error of estimate for a linear regression equation?

The following X and Y scores produce SS_X = 2 and SP = 8.What is the regression equation for predicting Y? 1 2 2 3 3 10

For linear regression,the value of SS_residual can be computed directly by Σ(Y - )².

For either linear regression or multiple regression,the standard error of estimate is equal to the square root of MS_residual.

The Pearson correlation between X₁ and Y is r = 0.70.When a second variable,X₂,is added to the regression equation,we obtain R² = 0.64.How much variance for the Y scores is predicted by using only X₁ as a predictor variable?

A researcher who is evaluating the significance of a multiple regression equation with two predictor variables obtains an F-ratio with df = 2,24.How many individuals were needed to produce the sample data used to find the regression equation?

The standardized form of the regression equation is z_Y = (beta)z_X.In the equation,what is the value of beta?

For the linear equation Y = 2X - 3,which of the following points will not be on the line?

A linear regression equation is computed for a sample of n = 13 pairs of X and Y scores.For the analysis of regression testing the significance of the equation,what are the df values for the F-ratio?

The Pearson correlation between X₁ and Y is r = 0.50 and the correlation between X₂ and Y is r = 0.20.How much variance for the Y scores is predicted by using both X₁ and X₂ as predictor variables in a multiple regression equation?

For a linear regression,if X = M_X,then the predicted Y value is M_Y.

For which of the following correlations would the data points be most widely scattered around the regression line?

A researcher who is evaluating the significance of a multiple regression equation with two predictor variables obtains an F-ratio with df = 2,18.How many individuals were needed to produce the sample data used to find the regression equation?

For a linear regression equation,the sum of the squared residuals can be computed directly by finding the difference between each Y and its predicted Y,then squaring the difference and adding the squared values.An alternative procedure is to calculate ____.

A linear regression equation has b = 3 and a = - 6.What is the predicted value of Y for X = 4?