Exam 16: Linear Regression and Multiple Regression

A researcher measures the extent to which the speed at which people eat (in minutes)predicts calorie intake (in kilocalories).Which factor is the predictor variable in this example?

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Question 1

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What is the computation for the standard error of estimate?

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Question 2

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The equation for the standardized regression equation is ______.

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Question 3

Correct Answer:

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The larger the standard error of estimate,the more accurately known values of X will predict values of Y.

(True/False)

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Question 4

One key advantage for including multiple predictor variables in the equation of a regression line is that it allows you to ______.

(Multiple Choice)

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Question 5

The "left-over" or remaining variation attributed to error in an analysis of regression is called residual variation.

(True/False)

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Question 6

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 ______.

(Multiple Choice)

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Question 7

The slope (b)is a measure of the change in Y relative to the change in X.

(True/False)

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Question 8

If the coefficient of determination is .09 and the sum of squares regression is 88,then the total variation in Y must be SS_Y = 108.

(True/False)

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Question 9

Which of the following is a step to evaluate the significance for the relative contribution of each factor?

(Multiple Choice)

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Question 10

In a sample of 22 participants,suppose we conduct an analysis of regression with one predictor variable.If F_obt= 2.07,then what is the decision for this test at a .05 level of significance?

(Multiple Choice)

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Question 11

Which of the following is used to determine the linear equation that best fits a set of data points?

(Multiple Choice)

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Question 12

Which of the following is used to determine the significance of predictions made by a best fitting linear equation?

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Question 13

Which of the following statements is true regarding the sources of variation present in an analysis of regression?

(Multiple Choice)

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Question 14

Multiple regression can be used to measure predictive variability for any number of predictor variables.

(True/False)

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Question 15

For a multiple regression analysis with 2 and 12 degrees of freedom,MS regression is 135 and MS residual is 15.What is the decision for this test?

(Multiple Choice)

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Question 16

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

(True/False)

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Question 17

The more that the variability in ______ is associated with regression variation,the more likely it is that X predicts Y.

(Multiple Choice)

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Question 18

If F = 2.04 for the relative contribution of one factor,then what is this value when converted to a t statistic?

(Multiple Choice)

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Question 19

The degrees of freedom residual is equal to the number of criterion variables.

(True/False)

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Question 20

Showing 1 - 20 of 80

A researcher measures the extent to which the speed at which people eat (in minutes)predicts calorie intake (in kilocalories).Which factor is the predictor variable in this example?

What is the computation for the standard error of estimate?

The equation for the standardized regression equation is ______.

The larger the standard error of estimate,the more accurately known values of X will predict values of Y.

One key advantage for including multiple predictor variables in the equation of a regression line is that it allows you to ______.

The "left-over" or remaining variation attributed to error in an analysis of regression is called residual variation.

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 ______.

The slope (b)is a measure of the change in Y relative to the change in X.

If the coefficient of determination is .09 and the sum of squares regression is 88,then the total variation in Y must be SS_Y = 108.

Which of the following is a step to evaluate the significance for the relative contribution of each factor?

In a sample of 22 participants,suppose we conduct an analysis of regression with one predictor variable.If F_obt= 2.07,then what is the decision for this test at a .05 level of significance?

Which of the following is used to determine the linear equation that best fits a set of data points?

Which of the following is used to determine the significance of predictions made by a best fitting linear equation?

Which of the following statements is true regarding the sources of variation present in an analysis of regression?

Multiple regression can be used to measure predictive variability for any number of predictor variables.

For a multiple regression analysis with 2 and 12 degrees of freedom,MS regression is 135 and MS residual is 15.What is the decision for this test?

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

The more that the variability in ______ is associated with regression variation,the more likely it is that X predicts Y.

If F = 2.04 for the relative contribution of one factor,then what is this value when converted to a t statistic?

The degrees of freedom residual is equal to the number of criterion variables.

Introduction to Statistics

Summarizing Data: Frequency Distributions in Tables and Graphs

Summarizing Data: Central Tendency

Summarizing Data: Variability

Probability

Probability, normal Distributions, and Z Scores

Probability and Sampling Distributions

Hypothesis Testing: Significance,effect Size,and Power

Testing Means: One-Sample and Two-Independent-Sample T Tests

Testing Means: Truehe Related-Samples T Test

Estimation and Confidence Intervals

Analysis of Variance: One-Way Between-Subjects Design

Analysis of Variance: One-Way Within-Subjects Repeated-Measuresdesign

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

Correlation

Nonparametric Tests: Chi-Square Tests

Nonparametric Tests: Tests for Ordinal Data

Filters

Exam 16: Linear Regression and Multiple Regression

A researcher measures the extent to which the speed at which people eat (in minutes)predicts calorie intake (in kilocalories).Which factor is the predictor variable in this example?

What is the computation for the standard error of estimate?

The equation for the standardized regression equation is ______.

The larger the standard error of estimate,the more accurately known values of X will predict values of Y.

One key advantage for including multiple predictor variables in the equation of a regression line is that it allows you to ______.

The "left-over" or remaining variation attributed to error in an analysis of regression is called residual variation.

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 ______.

The slope (b)is a measure of the change in Y relative to the change in X.

If the coefficient of determination is .09 and the sum of squares regression is 88,then the total variation in Y must be SSY = 108.

Which of the following is a step to evaluate the significance for the relative contribution of each factor?

In a sample of 22 participants,suppose we conduct an analysis of regression with one predictor variable.If Fobt = 2.07,then what is the decision for this test at a .05 level of significance?

Which of the following is used to determine the linear equation that best fits a set of data points?

Which of the following is used to determine the significance of predictions made by a best fitting linear equation?

Which of the following statements is true regarding the sources of variation present in an analysis of regression?

Multiple regression can be used to measure predictive variability for any number of predictor variables.

For a multiple regression analysis with 2 and 12 degrees of freedom,MS regression is 135 and MS residual is 15.What is the decision for this test?

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

The more that the variability in ______ is associated with regression variation,the more likely it is that X predicts Y.

If F = 2.04 for the relative contribution of one factor,then what is this value when converted to a t statistic?

The degrees of freedom residual is equal to the number of criterion variables.

Introduction to Statistics

Summarizing Data: Frequency Distributions in Tables and Graphs

Summarizing Data: Central Tendency

Summarizing Data: Variability

Probability

Probability, normal Distributions, and Z Scores

Probability and Sampling Distributions

Hypothesis Testing: Significance,effect Size,and Power

Testing Means: One-Sample and Two-Independent-Sample T Tests

Testing Means: Truehe Related-Samples T Test

Estimation and Confidence Intervals

Analysis of Variance: One-Way Between-Subjects Design

Analysis of Variance: One-Way Within-Subjects Repeated-Measuresdesign

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

Correlation

Nonparametric Tests: Chi-Square Tests

Nonparametric Tests: Tests for Ordinal Data

Filters

If the coefficient of determination is .09 and the sum of squares regression is 88,then the total variation in Y must be SS_Y = 108.

In a sample of 22 participants,suppose we conduct an analysis of regression with one predictor variable.If F_obt= 2.07,then what is the decision for this test at a .05 level of significance?