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## General linear model

> [!blank-container|right-medium] Relationship of Data, Information and Intelligence
> ![Pasted image 20220424085124.png](/img/user/screenshots/Pasted%20image%2020220424085124.png)
> Example of [simple linear regression](https://en.wikipedia.org/wiki/Simple_linear_regression "Simple linear regression"), which has one independent variable

The **general linear model** or **general multivariate regression model** is a compact way of simultaneously writing several [multiple linear regression](https://en.wikipedia.org/wiki/Multiple_linear_regression "Multiple linear regression") models. In that sense it is not a separate statistical [linear model](https://en.wikipedia.org/wiki/Linear_model "Linear model"). The various multiple linear regression models may be compactly written as $Y=XB + U$

The general linear model incorporates a number of different statistical models: ANOVA, ANCOVA, MANOVA, MANCOVA, ordinary linear regression, _t_-test and _F_-test. The general linear model is a generalization of multiple linear regression to the case of more than one dependent variable. If **Y**, **B**, and **U** were column vectors, the matrix equation above would represent multiple linear regression.

Hypothesis tests with the general linear model can be made in two ways: multivariate or as several independent univariate tests. In multivariate tests the columns of **Y** are tested together, whereas in univariate tests the columns of **Y** are tested independently, i.e., as multiple univariate tests with the same design matrix.

## Other Notes on Regression Model
> [!multi-column]
>
> ` | Statistical Analysis                                                                            |
> | ----------------------------------------------------------------------------------------------- |
> | Correlation does not imply causation |
> | Exploratory data analysis                       |
> | Descriptive Statistics                             |
> 
{ .block-language-dataview}`
>
> ` | Regression                                                              |
> | ----------------------------------------------------------------------- |
> | Logistic regression           |
> | Generalized linear model |
> 
{ .block-language-dataview}`
>
> ` | Model Validation                                                              |
> | ----------------------------------------------------------------------------- |
> | Goodness of fit                         |
> | Errors and residuals               |
> | Mean and predicted response |
> 
{ .block-language-dataview}`

> sample text extracted from [General linear model - Wikipedia](https://en.wikipedia.org/wiki/General_linear_model) and [Linear regression - Wikipedia](https://en.wikipedia.org/wiki/Linear_regression#Simple_and_multiple_linear_regression)
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