Homework Help is Here – Start Your Trial Now!
Math
Statistics
There are many statistical tools used to estimate relationships between variables. These include covariance, correlation, ANOVA, simple linear regression, and multiple regression. In the table below, enter a Yes (or Y) or No (or N) in each box to indicate the best response. If a box does not apply, enter NA.

There are many statistical tools used to estimate relationships between variables. These include covariance, correlation, ANOVA, simple linear regression, and multiple regression. In the table below, enter a Yes (or Y) or No (or N) in each box to indicate the best response. If a box does not apply, enter NA.

Algebra and Trigonometry (MindTap Course List)
Algebra and Trigonometry (MindTap Course List)
4th Edition
ISBN:9781305071742
Author:James Stewart, Lothar Redlin, Saleem Watson
Publisher:James Stewart, Lothar Redlin, Saleem Watson
Chapter1: Equations And Graphs
Section1.FOM: Focus On Modeling: Fitting Lines To Data
Problem 8P
See similar textbooks
icon
Related questions
Question
  • Estimating Relationships – There are many statistical tools used to estimate relationships between variables. These include covariance, correlation, ANOVA, simple linear regression, and multiple regression. In the table below, enter a Yes (or Y) or No (or N) in each box to indicate the best response. If a box does not apply, enter NA.

 

Covariance

Correlation

ANOVA

Simple Linear Regression

Multiple Regression

Example: Works well with a categorical dependent variable.

NA

(no dependent variable)

NA

(no dependent variable)

N

(should be continuous dependent variable)

N

(logistic regression)

N

(logistic regression)

Example: Can be used to estimation direction of relation between variables

 

 

 

 

 

Works well with one or more categorical variables

 

 

 

 

 

Can be used to measure the magnitude of relationship between variables

 

 

 

 

 

Works well with mostly continuous variables

 

 

 

 

 

Estimated relationship depends on scale

 

 

 

 

 

Can be used with multiple independent variables

 

 

 

 

 
Expert Solution
steps

Step by step

Solved in 2 steps

SEE SOLUTIONCheck out a sample Q&A here
Blurred answer
Follow-up Questions
Read through expert solutions to related follow-up questions below.
Follow-up Question

I don't think the answser lined up.  Can you populate the table in the attached image?  Thanks

1) Estimating Relationships - There are many statistical tools used to estimate relationships between variables. These include covariance, correlation, ANOVA, simple linear regression, and multiple regression. In the table below, enter a Yes (or Y) or No (or N) in each box to indicate the best response. If a box does not apply, enter NA. Covariance Example: Works well with a categorical dependent variable. Example: Can be used to estimation direction of relation between variables Works well with one or more categorical variables Can be used to measure the magnitude of relationship between variables Works well with mostly continuous variables Estimated relationship depends on scale Can be used with multiple independent variables ΝΑ (no dependent variable) Correlation ΝΑ (no dependent variable) ANOVA N (should be continuous dependent variable) Simple Linear Regression N (logistic regression) Multiple Regression N (logistic regression)
Transcribed Image Text:1) Estimating Relationships - There are many statistical tools used to estimate relationships between variables. These include covariance, correlation, ANOVA, simple linear regression, and multiple regression. In the table below, enter a Yes (or Y) or No (or N) in each box to indicate the best response. If a box does not apply, enter NA. Covariance Example: Works well with a categorical dependent variable. Example: Can be used to estimation direction of relation between variables Works well with one or more categorical variables Can be used to measure the magnitude of relationship between variables Works well with mostly continuous variables Estimated relationship depends on scale Can be used with multiple independent variables ΝΑ (no dependent variable) Correlation ΝΑ (no dependent variable) ANOVA N (should be continuous dependent variable) Simple Linear Regression N (logistic regression) Multiple Regression N (logistic regression)
Solution
Bartleby Expert
SEE SOLUTION
Recommended textbooks for you
Algebra and Trigonometry (MindTap Course List)
Algebra and Trigonometry (MindTap Course List)
Algebra
ISBN:
9781305071742
Author:
James Stewart, Lothar Redlin, Saleem Watson
Publisher:
Cengage Learning
College Algebra
College Algebra
Algebra
ISBN:
9781305115545
Author:
James Stewart, Lothar Redlin, Saleem Watson
Publisher:
Cengage Learning
Functions and Change: A Modeling Approach to Coll…
Functions and Change: A Modeling Approach to Coll…
Algebra
ISBN:
9781337111348
Author:
Bruce Crauder, Benny Evans, Alan Noell
Publisher:
Cengage Learning
Big Ideas Math A Bridge To Success Algebra 1: Stu…
Big Ideas Math A Bridge To Success Algebra 1: Stu…
Algebra
ISBN:
9781680331141
Author:
HOUGHTON MIFFLIN HARCOURT
Publisher:
Houghton Mifflin Harcourt
Linear Algebra: A Modern Introduction
Linear Algebra: A Modern Introduction
Algebra
ISBN:
9781285463247
Author:
David Poole
Publisher:
Cengage Learning
Glencoe Algebra 1, Student Edition, 9780079039897…
Glencoe Algebra 1, Student Edition, 9780079039897…
Algebra
ISBN:
9780079039897
Author:
Carter
Publisher:
McGraw Hill
SEE MORE TEXTBOOKS