Noun:

బహుళ రిగ్రెషన్,

multiple regression's Usage Examples:

statistics, multicollinearity (also collinearity) is a phenomenon in which one predictor variable in a multiple regression model can be linearly predicted from.

A multiple regression e right hand side, each with its own slope coefficient Rencher, Alvin C.

motivation for including other right-side variables in a multiple regression; but while multiple regression gives unbiased results for the effect size, it does.

sometimes called DeFries–Fulker extremes analysis, is a type of multiple regression analysis designed for estimating the magnitude of genetic and environmental.

regression is a simplified and robust version (Wainer " Thissen, 1976) of multiple regression analysis where only the intercept term is estimated.

quality that affect demand and apply statistical methods, variants on multiple regression.

This section contains an example of multiple regression with two covariates (explanatory variables): w and x.

This includes models equivalent to any form of multiple regression analysis, factor analysis, canonical correlation analysis, discriminant.

involving multivariate data, for example simple linear regression and multiple regression, are not usually considered to be special cases of multivariate statistics.

Applied multiple regression/correlation analysis for the behavioral sciences (3.

In the more general multiple regression model, there are p {\displaystyle p} independent variables: y i .

Like the multiple regression equation transform, grid-based methods use a low-order interpolation.

" Standardization of variables prior to multiple regression analysis is sometimes used as an aid to interpretation.

Synonyms:

multiple correlation, multivariate analysis, multicollinearity,

Antonyms:

better, progress, gain, stay, typicality,