# explain.fisher: F Fisher Distribution Function Explained In LearningRlab: Statistical Learning Functions

## Description

Step by step demonstration of the fisher distribution calculus.

## Usage

 `1` ```explain.fisher(x,y) ```

## Arguments

 `x` Should be a vector `y` Should be a vector

## Details

To calculate the fisher distribution, the user should give two vectors of numbers. The result is a continuous probability distribution that arises frequently as the null distribution of a test statistic. We can saw fisher distribution formule in the fisher_ help document.

## Value

Numeric result and the process of this calculus explained.

## Note

A vector is created by c(), like c(1,2,3,4,5) creates a vector with the numbers: 1,2,3,4,5

## Author(s)

Jose Manuel Gomez Caceres, josemanuel.gomezc@edu.uah.es
Juan Jose Cuadrado, jjcg@uah.es
Universidad de Alcala de Henares

## Examples

 ```1 2 3 4 5 6 7``` ``` #data creation data <- c(10,4,5,7,3,4,1) data2 <- c(1,8,3,4,4,5,7) explain.fisher(data, data2) ```

LearningRlab documentation built on Feb. 9, 2021, 1:05 a.m.