# friedman: Friedman test and multiple comparison of treatments In agricolae: Statistical Procedures for Agricultural Research

 friedman R Documentation

## Friedman test and multiple comparison of treatments

### Description

The data consist of b-blocks mutually independent k-variate random variables Xij, i=1,..,b; j=1,..k. The random variable X is in block i and is associated with treatment j. It makes the multiple comparison of the Friedman test with or without ties. A first result is obtained by friedman.test of R.

### Usage

``````friedman(judge,trt,evaluation,alpha=0.05,group=TRUE,main=NULL,console=FALSE)
``````

### Arguments

 `judge` Identification of the judge in the evaluation `trt` Treatment `evaluation` Variable `alpha` Significant test `group` TRUE or FALSE `main` Title `console` logical, print output

### Details

The post hoc friedman test is using the criterium Fisher's least significant difference (LSD)

### Value

 `statistics` Statistics of the model `parameters` Design parameters `means` Statistical summary of the study variable `comparison` Comparison between treatments `groups` Formation of treatment groups

### Author(s)

Felipe de Mendiburu

### References

Practical Nonparametrics Statistics. W.J. Conover, 1999

`BIB.test`, `DAU.test`, `duncan.test`, `durbin.test`, `HSD.test`, `kruskal`, `LSD.test`, `Median.test`, `PBIB.test`, `REGW.test`, `scheffe.test`, `SNK.test`, `waerden.test`, `waller.test`, `plot.group`

### Examples

``````library(agricolae)
data(grass)
out<-with(grass,friedman(judge,trt, evaluation,alpha=0.05, group=TRUE,console=TRUE,
main="Data of the book of Conover"))
#startgraph
plot(out,variation="IQR")
#endgraph
``````

agricolae documentation built on Oct. 23, 2023, 1:06 a.m.