Question 1

For a multiple regression,we typically report which value that is not often reported for a one factor linear regression analysis?

Accepted Answer

A) effect size 
B) $\beta$ coefficient 
C) test statistic 
D) p value 
A) effect size 
B) $\beta$ coefficient 
C) test statistic 
D) p value B

Question 2

To standardize the coefficients,we first convert the original data to standardized z scores.

Accepted Answer

A) True 
 B)False  True

Question 3

A statistical method that includes two or more predictor variables in the equation of a regression line to predict changes in a criterion variable is called

Accepted Answer

A) analysis of variance 
B) standard error of estimate 
C) residual regression 
D) multiple regression 
A) analysis of variance 
B) standard error of estimate 
C) residual regression 
D) multiple regression D

Question 4

We can evaluate the significance of the relative contribution of each factor by first determining the differences between group means.

Accepted Answer

A) True 
 B)False

Question 5

In a sample of 22 participants,suppose we conduct an analysis of regression with one predictor variable.If   = 4.07,then what is the decision for this test at a .05 level of significance?

Accepted Answer

A) X significantly predicts Y. 
B) X does not significantly predict Y. 
C) There is not enough information to answer this question. 
A) X significantly predicts Y. 
B) X does not significantly predict Y. 
C) There is not enough information to answer this question.

Question 6

A researcher computes the following analysis of regression table.Based on the data given,what is the value of the standard error of estimate? (Note: Complete the table first. )

Accepted Answer

A) 2.24 
B) 5.00 
C) 5.74 
D) 8.49 
A) 2.24 
B) 5.00 
C) 5.74 
D) 8.49

Question 7

The standardized beta coefficient,$\beta$,reflects the distinctive contribution of each criterion variable.

Accepted Answer

A) True 
 B)False

Question 8

In an analysis of regression there are three sources of variation: regression,residual,and error.

Accepted Answer

A) True 
 B)False

Question 9

The predictor variable is a known value that is used to predict the value of another variable.

Accepted Answer

A) True 
 B)False

Question 10

If the coefficient of determination is 0.12 and   = 225,then what is the sum of squares regression for an analysis of regression?

Accepted Answer

A) 27 
B) 198 
C) 225 
D) There is not enough information to answer this question. 
A) 27 
B) 198 
C) 225 
D) There is not enough information to answer this question.

Question 11

The data points for pairs of scores are often summarized in a bar chart.

Accepted Answer

A) True 
 B)False

Question 12

Which of the following is not needed to compute the slope using the method of least squares?

Accepted Answer

A)    
B)    
C)    
A)    
B)    
C)

Question 13

When most of the variability in Y is attributed to regression variation,it is more likely that X predicts Y.

Accepted Answer

A) True 
 B)False

Question 14

The numerator of the formula for the slope (b)of a regression line is equal to the sum of products.

Accepted Answer

A) True 
 B)False

Question 15

A researcher computes an analysis of regression with 1 and 25 degrees of freedom.If F = 5.34,then the decision will be that X is a significant predictor of variation in Y.

Accepted Answer

A) True 
 B)False

Question 16

The scores or data points for a regression analysis are typically reported in,

Accepted Answer

A) a scatter plot 
B) a bar chart 
C) a pie chart 
D) all of the above 
A) a scatter plot 
B) a bar chart 
C) a pie chart 
D) all of the above

Question 17

To standardize the beta coefficients,we first,

Accepted Answer

A) analyze the significance of each data point 
B) analyze the residual variation 
C) convert the original data to standardized z scores 
D) compute the standard error of estimate 
A) analyze the significance of each data point 
B) analyze the residual variation 
C) convert the original data to standardized z scores 
D) compute the standard error of estimate

Question 18

Both sources of variation in an analysis of regression measure the variability in

Accepted Answer

A) X and Y 
B) X only 
C) Y only 
A) X and Y 
B) X only 
C) Y only

Question 19

The equation for the standardized regression equation is,

Accepted Answer

A)    
B)    
C)    
D)    
A)    
B)    
C)    
D)

Question 20

Including two or more predictor variables into a single equation of a regression line can be more informative than an analysis using only one predictor variable.

Accepted Answer

A) True 
 B)False

For a multiple regression,we typically report which value that is not often reported for a one factor linear regression analysis?

To standardize the coefficients,we first convert the original data to standardized z scores.

A statistical method that includes two or more predictor variables in the equation of a regression line to predict changes in a criterion variable is called

We can evaluate the significance of the relative contribution of each factor by first determining the differences between group means.

In a sample of 22 participants,suppose we conduct an analysis of regression with one predictor variable.If = 4.07,then what is the decision for this test at a .05 level of significance?

A researcher computes the following analysis of regression table.Based on the data given,what is the value of the standard error of estimate? (Note: Complete the table first. )

The standardized beta coefficient, $\beta$ ,reflects the distinctive contribution of each criterion variable.

In an analysis of regression there are three sources of variation: regression,residual,and error.

The predictor variable is a known value that is used to predict the value of another variable.

If the coefficient of determination is 0.12 and = 225,then what is the sum of squares regression for an analysis of regression?

The data points for pairs of scores are often summarized in a bar chart.

Which of the following is not needed to compute the slope using the method of least squares?

When most of the variability in Y is attributed to regression variation,it is more likely that X predicts Y.

The numerator of the formula for the slope (b)of a regression line is equal to the sum of products.

A researcher computes an analysis of regression with 1 and 25 degrees of freedom.If F = 5.34,then the decision will be that X is a significant predictor of variation in Y.

The scores or data points for a regression analysis are typically reported in,

To standardize the beta coefficients,we first,

Both sources of variation in an analysis of regression measure the variability in

The equation for the standardized regression equation is,

Including two or more predictor variables into a single equation of a regression line can be more informative than an analysis using only one predictor variable.

Introduction to Statistics

Summarizing Data: Frequency Distributions in

Summarizing Data: Central Tendency

Summarizing Data: Variability

Probability, Normal Distributions, and Z Scores

Characteristics of the Sample Mean

Hypothesis Testing: Significance, Effect Size, and Power

Testing Means: One-Sample T Test With Confidence Intervals

Testing Means: Two- Independent-Sample T Test With Confidence Intervals

Testing Means: Related-Samples T Test With Confidence Intervals

One-Way Analysis of Variance: Between- Subjects and Within- Subjects Repeated- Measures Designs

Two-Way Analysis of Variance: Between-Subjects Factorial Design

Correlation and Linear Regression

Chi-Square Tests: Goodness of Fit and the Test for Independence

Nonparametric Tests for Ordinal Data: Understanding and Interpretation

Chi-Square Tests: Goodness-of-Fit and Independence

Understanding Correlation Coefficients in Statistical Analysis

Filters

Exam 17: Understanding Regression Analysis

For a multiple regression,we typically report which value that is not often reported for a one factor linear regression analysis?

To standardize the coefficients,we first convert the original data to standardized z scores.

A statistical method that includes two or more predictor variables in the equation of a regression line to predict changes in a criterion variable is called

We can evaluate the significance of the relative contribution of each factor by first determining the differences between group means.

In a sample of 22 participants,suppose we conduct an analysis of regression with one predictor variable.If = 4.07,then what is the decision for this test at a .05 level of significance?

A researcher computes the following analysis of regression table.Based on the data given,what is the value of the standard error of estimate? (Note: Complete the table first. )

The standardized beta coefficient, β\betaβ ,reflects the distinctive contribution of each criterion variable.

In an analysis of regression there are three sources of variation: regression,residual,and error.

The predictor variable is a known value that is used to predict the value of another variable.

If the coefficient of determination is 0.12 and = 225,then what is the sum of squares regression for an analysis of regression?

The data points for pairs of scores are often summarized in a bar chart.

Which of the following is not needed to compute the slope using the method of least squares?

When most of the variability in Y is attributed to regression variation,it is more likely that X predicts Y.

The numerator of the formula for the slope (b)of a regression line is equal to the sum of products.

A researcher computes an analysis of regression with 1 and 25 degrees of freedom.If F = 5.34,then the decision will be that X is a significant predictor of variation in Y.

The scores or data points for a regression analysis are typically reported in,

To standardize the beta coefficients,we first,

Both sources of variation in an analysis of regression measure the variability in

The equation for the standardized regression equation is,

Including two or more predictor variables into a single equation of a regression line can be more informative than an analysis using only one predictor variable.

Introduction to Statistics

Summarizing Data: Frequency Distributions in

Summarizing Data: Central Tendency

Summarizing Data: Variability

Probability, Normal Distributions, and Z Scores

Characteristics of the Sample Mean

Hypothesis Testing: Significance, Effect Size, and Power

Testing Means: One-Sample T Test With Confidence Intervals

Testing Means: Two- Independent-Sample T Test With Confidence Intervals

Testing Means: Related-Samples T Test With Confidence Intervals

One-Way Analysis of Variance: Between- Subjects and Within- Subjects Repeated- Measures Designs

Two-Way Analysis of Variance: Between-Subjects Factorial Design

Correlation and Linear Regression

Chi-Square Tests: Goodness of Fit and the Test for Independence

Nonparametric Tests for Ordinal Data: Understanding and Interpretation

Chi-Square Tests: Goodness-of-Fit and Independence

Understanding Correlation Coefficients in Statistical Analysis

Filters

The standardized beta coefficient, $\beta$ ,reflects the distinctive contribution of each criterion variable.