general linear model
In statistical modeling of data observations (), two types of variables are usually defined. One is the response variable or variate, usually denoted by , and the other is the explanatory variable or covariate . While there is only one response variable, there may be one or more than one explanatory variables. The response variable is considered random, where as the explanatory variable(s) may or may not be random.
Analysis of covariance, or ANCOVA, sits between a linear regression model and the ANOVA, where some of the explanatory variables are continuous and some are categorical.
|Title||general linear model|
|Date of creation||2013-03-22 14:31:23|
|Last modified on||2013-03-22 14:31:23|
|Last modified by||CWoo (3771)|
|Synonym||normal linear model|
|Defines||analysis of variance|
|Defines||analysis of covariance|