Which of the following is not a plot of residuals typically used in multiple regression analysis? Select one: None of these Residuals versus correlation coefficients Residuals versus X1 Residuals versus time Residuals versus X2.

Which of the following is not a plot of residuals typically used in multiple regression analysis? Select one: None of these Residuals versus correlation coefficients Residuals versus X1 Residuals versus time Residuals versus X2.

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018

18th Edition

ISBN:9780079039897

Author:Carter

Publisher:Carter

Chapter4: Equations Of Linear Functions

Section4.6: Regression And Median-fit Lines

Problem 4PPS

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Concept explainers

Correlation

Correlation defines a relationship between two independent variables. It tells the degree to which variables move in relation to each other. When two sets of data are related to each other, there is a correlation between them.

Linear Correlation

A correlation is used to determine the relationships between numerical and categorical variables. In other words, it is an indicator of how things are connected to one another. The correlation analysis is the study of how variables are related.

Regression Analysis

Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as predictors. Regression analysis is one of the methods to find the trends in data. The independent variable used in Regression analysis is named Predictor variable. It offers data of an associated dependent variable regarding a particular outcome.

Question

Which of the following is not a plot of residuals typically used in multiple regression analysis?

Select one:

None of these
Residuals versus correlation coefficients
Residuals versus X1
Residuals versus time
Residuals versus X2.

Definition Definition Statistical measure used to assess the strength and direction of relationships between two variables. Correlation coefficients range between -1 and 1. A coefficient value of 0 indicates that there is no relationship between the variables, whereas a -1 or 1 indicates that there is a perfect negative or positive correlation.

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