Exam 16: Introduction to Regression

The Pearson correlation between X₁ and Y is r = 0.50.When a second variable,X₂,is added to the regression equation,we obtain R² = 0.60.Adding the second variable increases the variability that is predicted by the regression equation for the Y scores by 36% - 25% = 11%.

(True/False)

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Question 41

In a multiple regression equation with two predictor variables,if b₁ is larger than b₂,then X₁ is a better predictor of the Y-score than is X₂.

(True/False)

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Question 42

If the Pearson correlation between X and Y is r = 0.60,then the regression equation predicts 36% of the variance in the Y scores.

(True/False)

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Question 43

The regression equation is determined by finding the minimum value for which of the following?

(Multiple Choice)

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Question 44

If a set of X and Y scores has r > 0,then the regression equation,= bX + a,will have a > 0.

(True/False)

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Question 45

Find the regression equation for the following set of data. 4 1 7 16 3 4 5 7 6 7

(Essay)

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Question 46

If the correlation between X and Y is r = 0.00,then the regression equation,= bX + a,will have b = 0.

(True/False)

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Question 47

The line produced by the equation Y = 4X - 5 crosses the vertical axis at Y = 5.

(True/False)

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Question 48

For the regression equation,= -2X + 6,if the X value is above the mean (positive deviation),then what can be determined about the predicted Y value?

(Multiple Choice)

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Question 49

An analysis of regression is used to test the significance of a linear regression equation based on a sample of n = 20 individuals.What are the df values for the F-ratio?

(Multiple Choice)

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Question 50

For the data below: 5 10 3 6 6 7 4 3 2 4 a. Compute the Pearson correlation. b. Find the regression equation for predicting Y from X. c. Calculate the predicted Y for each X value, find each residual (Y - ), square each residual, and add the squared values to obtain SS_residual

(Essay)

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Question 51

For the regression equation,Y = X - 2,if the mean for Y is M_Y = 6,what is the mean for X?

(Multiple Choice)

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Question 52

For a linear regression calculated for a sample of n = 20 pairs of X and Y values,what is the value for degrees of freedom for the predicted portion of the Y-score variance,MS_regression?

(Multiple Choice)

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Question 53

The F-ratio evaluating the significance of a linear regression equation based on n = 10 pairs of X and Y scores has df = 1,8.

(True/False)

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Question 54

The slope determines how much the Y variable changes when X is increased by one point.

(True/False)

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Question 55

The point defined by X = 2 and Y = -1 is located on the line defined by the equation Y = 2X - 3.

(True/False)

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Question 56

A multiple regression equation with two predictor variables is computed for a sample of n = 35 participants.The standard error of estimate for the equation would have df = 33.

(True/False)

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Question 57

For the linear equation Y = 2X + 4,if X increases by 1 point,how much will Y increase?

(Multiple Choice)

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Question 58

For a linear regression calculated for a sample of n = 20 pairs of X and Y values,what is the value for degrees of freedom for the unpredicted portion of the Y-score variance,MS_residual?

(Multiple Choice)

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Question 59

A set of n = 25 pairs of scores (X and Y values)has a Pearson correlation of r = 0.80.How much of the variance for the Y scores is predicted by the relationship with X?

(Multiple Choice)

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Question 60

Showing 41 - 60 of 75

The Pearson correlation between X₁ and Y is r = 0.50.When a second variable,X₂,is added to the regression equation,we obtain R² = 0.60.Adding the second variable increases the variability that is predicted by the regression equation for the Y scores by 36% - 25% = 11%.

In a multiple regression equation with two predictor variables,if b₁ is larger than b₂,then X₁ is a better predictor of the Y-score than is X₂.

If the Pearson correlation between X and Y is r = 0.60,then the regression equation predicts 36% of the variance in the Y scores.

The regression equation is determined by finding the minimum value for which of the following?

If a set of X and Y scores has r > 0,then the regression equation,= bX + a,will have a > 0.

Find the regression equation for the following set of data. 4 1 7 16 3 4 5 7 6 7

If the correlation between X and Y is r = 0.00,then the regression equation,= bX + a,will have b = 0.

The line produced by the equation Y = 4X - 5 crosses the vertical axis at Y = 5.

For the regression equation,= -2X + 6,if the X value is above the mean (positive deviation),then what can be determined about the predicted Y value?

An analysis of regression is used to test the significance of a linear regression equation based on a sample of n = 20 individuals.What are the df values for the F-ratio?

For the data below: 5 10 3 6 6 7 4 3 2 4 a. Compute the Pearson correlation. b. Find the regression equation for predicting Y from X. c. Calculate the predicted Y for each X value, find each residual (Y - ), square each residual, and add the squared values to obtain SS_residual

For the regression equation,Y = X - 2,if the mean for Y is M_Y = 6,what is the mean for X?

For a linear regression calculated for a sample of n = 20 pairs of X and Y values,what is the value for degrees of freedom for the predicted portion of the Y-score variance,MS_regression?

The F-ratio evaluating the significance of a linear regression equation based on n = 10 pairs of X and Y scores has df = 1,8.

The slope determines how much the Y variable changes when X is increased by one point.

The point defined by X = 2 and Y = -1 is located on the line defined by the equation Y = 2X - 3.

A multiple regression equation with two predictor variables is computed for a sample of n = 35 participants.The standard error of estimate for the equation would have df = 33.

For the linear equation Y = 2X + 4,if X increases by 1 point,how much will Y increase?

For a linear regression calculated for a sample of n = 20 pairs of X and Y values,what is the value for degrees of freedom for the unpredicted portion of the Y-score variance,MS_residual?

A set of n = 25 pairs of scores (X and Y values)has a Pearson correlation of r = 0.80.How much of the variance for the Y scores is predicted by the relationship with X?

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 Pearson correlation between X1 and Y is r = 0.50.When a second variable,X2,is added to the regression equation,we obtain R2 = 0.60.Adding the second variable increases the variability that is predicted by the regression equation for the Y scores by 36% - 25% = 11%.

In a multiple regression equation with two predictor variables,if b1 is larger than b2,then X1 is a better predictor of the Y-score than is X2.

If the Pearson correlation between X and Y is r = 0.60,then the regression equation predicts 36% of the variance in the Y scores.

The regression equation is determined by finding the minimum value for which of the following?​

If a set of X and Y scores has r > 0,then the regression equation,= bX + a,will have a > 0.

Find the regression equation for the following set of data.​ 4 1 7 16 3 4 5 7 6 7

If the correlation between X and Y is r = 0.00,then the regression equation,= bX + a,will have b = 0.

The line produced by the equation Y = 4X - 5 crosses the vertical axis at Y = 5.

For the regression equation,= -2X + 6,if the X value is above the mean (positive deviation),then what can be determined about the predicted Y value?​

An analysis of regression is used to test the significance of a linear regression equation based on a sample of n = 20 individuals.What are the df values for the F-ratio?​

For the data below: 5 10 3 6 6 7 4 3 2 4 ​ a. Compute the Pearson correlation. b. Find the regression equation for predicting Y from X. c. Calculate the predicted Y for each X value, find each residual (Y - ), square each residual, and add the squared values to obtain SSresidual

For the regression equation,Y = X - 2,if the mean for Y is MY = 6,what is the mean for X?​

For a linear regression calculated for a sample of n = 20 pairs of X and Y values,what is the value for degrees of freedom for the predicted portion of the Y-score variance,MSregression?​

The F-ratio evaluating the significance of a linear regression equation based on n = 10 pairs of X and Y scores has df = 1,8.

The slope determines how much the Y variable changes when X is increased by one point.​

The point defined by X = 2 and Y = -1 is located on the line defined by the equation Y = 2X - 3.

A multiple regression equation with two predictor variables is computed for a sample of n = 35 participants.The standard error of estimate for the equation would have df = 33.

For the linear equation Y = 2X + 4,if X increases by 1 point,how much will Y increase?​

For a linear regression calculated for a sample of n = 20 pairs of X and Y values,what is the value for degrees of freedom for the unpredicted portion of the Y-score variance,MSresidual?​

A set of n = 25 pairs of scores (X and Y values)has a Pearson correlation of r = 0.80.How much of the variance for the Y scores is predicted by the relationship with X?​

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 Pearson correlation between X₁ and Y is r = 0.50.When a second variable,X₂,is added to the regression equation,we obtain R² = 0.60.Adding the second variable increases the variability that is predicted by the regression equation for the Y scores by 36% - 25% = 11%.

In a multiple regression equation with two predictor variables,if b₁ is larger than b₂,then X₁ is a better predictor of the Y-score than is X₂.

The regression equation is determined by finding the minimum value for which of the following?

Find the regression equation for the following set of data. 4 1 7 16 3 4 5 7 6 7

For the regression equation,= -2X + 6,if the X value is above the mean (positive deviation),then what can be determined about the predicted Y value?

An analysis of regression is used to test the significance of a linear regression equation based on a sample of n = 20 individuals.What are the df values for the F-ratio?

For the data below: 5 10 3 6 6 7 4 3 2 4 a. Compute the Pearson correlation. b. Find the regression equation for predicting Y from X. c. Calculate the predicted Y for each X value, find each residual (Y - ), square each residual, and add the squared values to obtain SS_residual

For the regression equation,Y = X - 2,if the mean for Y is M_Y = 6,what is the mean for X?

For a linear regression calculated for a sample of n = 20 pairs of X and Y values,what is the value for degrees of freedom for the predicted portion of the Y-score variance,MS_regression?

The slope determines how much the Y variable changes when X is increased by one point.

For the linear equation Y = 2X + 4,if X increases by 1 point,how much will Y increase?

For a linear regression calculated for a sample of n = 20 pairs of X and Y values,what is the value for degrees of freedom for the unpredicted portion of the Y-score variance,MS_residual?

A set of n = 25 pairs of scores (X and Y values)has a Pearson correlation of r = 0.80.How much of the variance for the Y scores is predicted by the relationship with X?