friedman | R Documentation |

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.

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

`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 |

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

`statistics` |
Statistics of the model |

`parameters` |
Design parameters |

`means` |
Statistical summary of the study variable |

`comparison` |
Comparison between treatments |

`groups` |
Formation of treatment groups |

Felipe de Mendiburu

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`

```
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
```

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