Question 1

The value of SSresidual measures the total squared distance between the actual Y values and the Y values predicted by the regression equation.

Accepted Answer

A) True 
 B)False

Question 2

​A set of X and Y scores has MX = 4,SSX = 10,MY = 5,SSY = 40,and SP = 20.What is the regression equation for predicting Y from X?

Accepted Answer

A) ​ = 0.25X + 4 
B) ​ = 4X - 9 
C) ​ = 0.50X +3 
D) ​ = 2X - 3 
A) ​ = 0.25X + 4 
B) ​ = 4X - 9 
C) ​ = 0.50X +3 
D) ​ = 2X - 3

Question 3

A multiple regression equation with two predictor variables is calculated for a set of scores.If the constant values in the equation are b1 = 2,b2 = -3,and a = 7,then what Y value would be predicted for an individual with X1 = 2 and X2 = 4?​

Accepted Answer

A) 1​ 
B) ​-1 
C) ​17 
D) ​41 
A) 1​ 
B) ​-1 
C) ​17 
D) ​41

Question 4

If the correlation between X1 and Y is r = 0.40 and the correlation between X2 and Y is r = 0.30,then a multiple regression equation using both X1 and X2 as predictors will produce R2 = 0.25.

Accepted Answer

A) True 
 B)False

Question 5

A multiple regression equation with two predictor variables produces R2 = 0.10.What portion of the variability for the Y scores is predicted by the equation?​

Accepted Answer

A) ​1% 
B) ​10% 
C) ​90% 
D) ​99% 
A) ​1% 
B) ​10% 
C) ​90% 
D) ​99%

Question 6

A linear regression equation is calculated for a sample of n = 20 pairs of X and Y values.What would be the df value for the standard error of estimate?​

Accepted Answer

A) 1​ 
B) ​2 
C) ​18 
D) ​19 
A) 1​ 
B) ​2 
C) ​18 
D) ​19

Question 7

The line defined by the Y = -3X + 6 slopes up to the right.

Accepted Answer

A) True 
 B)False

Question 8

For either linear regression or multiple regression,the standard error of estimate can be computed as ____.​

Accepted Answer

A) ​the square root of MSresidual 
B) ​MSresidual/(n - 2) 
C) ​the square root of MSregression 
D) ​MSregression/(n - 2) 
A) ​the square root of MSresidual 
B) ​MSresidual/(n - 2) 
C) ​the square root of MSregression 
D) ​MSregression/(n - 2)

Question 9

​If there is a positive correlation between X and Y then in the regression equation,Y = bX + a,____.

Accepted Answer

A) b > 0 B) b 0 D) a < 0 A) b > 0 B) b 0 D) a < 0

Question 10

It is possible for a regression equation to have none of the actual (observed)data points located on the regression line.

Accepted Answer

A) True 
 B)False

Question 11

The statistical technique for finding the best-fitting straight line for a set of data is called regression,and the resulting straight line is called the regression line.

Accepted Answer

A) True 
 B)False

Question 12

A set of X and Y scores has SSX = 10,SSY = 36,and SP = 20.The regression equation for these scores will have a slope constant of 2.

Accepted Answer

A) True 
 B)False

Question 13

If the Pearson correlation between X and Y is negative,then the regression equation will have a negative slope.

Accepted Answer

A) True 
 B)False

Question 14

The Pearson correlation between X1 and Y is r = 0.40 and SSY = 100.When a second variable,X2,is added to the regression equation,we obtain R2 = 0.25.How much additional variability is contributed by adding the second variable as a predictor compared to using X1 alone?​

Accepted Answer

A) ​9 points 
B) ​15 points 
C) ​25 points 
D) ​40 points 
A) ​9 points 
B) ​15 points 
C) ​25 points 
D) ​40 points

Question 15

Multiple regression involves finding a regression equation with more than one predictor variable.

Accepted Answer

A) True 
 B)False

The value of SS_residual measures the total squared distance between the actual Y values and the Y values predicted by the regression equation.

A set of X and Y scores has M_X = 4,SS_X = 10,M_Y = 5,SS_Y = 40,and SP = 20.What is the regression equation for predicting Y from X?

A multiple regression equation with two predictor variables is calculated for a set of scores.If the constant values in the equation are b₁ = 2,b₂ = -3,and a = 7,then what Y value would be predicted for an individual with X₁ = 2 and X₂ = 4?

If the correlation between X₁ and Y is r = 0.40 and the correlation between X₂ and Y is r = 0.30,then a multiple regression equation using both X₁ and X₂ as predictors will produce R² = 0.25.

A multiple regression equation with two predictor variables produces R² = 0.10.What portion of the variability for the Y scores is predicted by the equation?

A linear regression equation is calculated for a sample of n = 20 pairs of X and Y values.What would be the df value for the standard error of estimate?

The line defined by the Y = -3X + 6 slopes up to the right.

For either linear regression or multiple regression,the standard error of estimate can be computed as ____.

If there is a positive correlation between X and Y then in the regression equation,Y = bX + a,____.

It is possible for a regression equation to have none of the actual (observed)data points located on the regression line.

The statistical technique for finding the best-fitting straight line for a set of data is called regression,and the resulting straight line is called the regression line.

A set of X and Y scores has SS_X = 10,SS_Y = 36,and SP = 20.The regression equation for these scores will have a slope constant of 2.

If the Pearson correlation between X and Y is negative,then the regression equation will have a negative slope.

The Pearson correlation between X₁ and Y is r = 0.40 and SS_Y = 100.When a second variable,X₂,is added to the regression equation,we obtain R² = 0.25.How much additional variability is contributed by adding the second variable as a predictor compared to using X₁ alone?

Multiple regression involves finding a regression equation with more than one predictor variable.

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 value of SSresidual measures the total squared distance between the actual Y values and the Y values predicted by the regression equation.

​A set of X and Y scores has MX = 4,SSX = 10,MY = 5,SSY = 40,and SP = 20.What is the regression equation for predicting Y from X?

A multiple regression equation with two predictor variables is calculated for a set of scores.If the constant values in the equation are b1 = 2,b2 = -3,and a = 7,then what Y value would be predicted for an individual with X1 = 2 and X2 = 4?​

If the correlation between X1 and Y is r = 0.40 and the correlation between X2 and Y is r = 0.30,then a multiple regression equation using both X1 and X2 as predictors will produce R2 = 0.25.

A multiple regression equation with two predictor variables produces R2 = 0.10.What portion of the variability for the Y scores is predicted by the equation?​

A linear regression equation is calculated for a sample of n = 20 pairs of X and Y values.What would be the df value for the standard error of estimate?​

The line defined by the Y = -3X + 6 slopes up to the right.

For either linear regression or multiple regression,the standard error of estimate can be computed as ____.​

​If there is a positive correlation between X and Y then in the regression equation,Y = bX + a,____.

It is possible for a regression equation to have none of the actual (observed)data points located on the regression line.

The statistical technique for finding the best-fitting straight line for a set of data is called regression,and the resulting straight line is called the regression line.

A set of X and Y scores has SSX = 10,SSY = 36,and SP = 20.The regression equation for these scores will have a slope constant of 2.

If the Pearson correlation between X and Y is negative,then the regression equation will have a negative slope.

The Pearson correlation between X1 and Y is r = 0.40 and SSY = 100.When a second variable,X2,is added to the regression equation,we obtain R2 = 0.25.How much additional variability is contributed by adding the second variable as a predictor compared to using X1 alone?​

Multiple regression involves finding a regression equation with more than one predictor variable.

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 value of SS_residual measures the total squared distance between the actual Y values and the Y values predicted by the regression equation.

A set of X and Y scores has M_X = 4,SS_X = 10,M_Y = 5,SS_Y = 40,and SP = 20.What is the regression equation for predicting Y from X?

A multiple regression equation with two predictor variables is calculated for a set of scores.If the constant values in the equation are b₁ = 2,b₂ = -3,and a = 7,then what Y value would be predicted for an individual with X₁ = 2 and X₂ = 4?

If the correlation between X₁ and Y is r = 0.40 and the correlation between X₂ and Y is r = 0.30,then a multiple regression equation using both X₁ and X₂ as predictors will produce R² = 0.25.

A multiple regression equation with two predictor variables produces R² = 0.10.What portion of the variability for the Y scores is predicted by the equation?

A linear regression equation is calculated for a sample of n = 20 pairs of X and Y values.What would be the df value for the standard error of estimate?

For either linear regression or multiple regression,the standard error of estimate can be computed as ____.

If there is a positive correlation between X and Y then in the regression equation,Y = bX + a,____.

A set of X and Y scores has SS_X = 10,SS_Y = 36,and SP = 20.The regression equation for these scores will have a slope constant of 2.

The Pearson correlation between X₁ and Y is r = 0.40 and SS_Y = 100.When a second variable,X₂,is added to the regression equation,we obtain R² = 0.25.How much additional variability is contributed by adding the second variable as a predictor compared to using X₁ alone?