grass

Twelve homeowners are selected randomly to participate in an experiment with
 a plant nursery. Each homeowner is asked to select four fairly identical
 areas in his yard and to plant four different types of grasses, one in each area.

datasets

Original idea was presented in the thesis "A statistical analysis tool for agricultural research" to obtain the degree of Master on science, National Engineering University (UNI), Lima-Peru. Some experimental data for the examples come from the CIP and others research. Agricolae offers extensive functionality on experimental design especially for agricultural and plant breeding experiments, which can also be useful for other purposes. It supports planning of lattice, Alpha, Cyclic, Complete Block, Latin Square, Graeco-Latin Squares, augmented block, factorial, split and strip plot designs. There are also various analysis facilities for experimental data, e.g. treatment comparison procedures and several non-parametric tests comparison, biodiversity indexes and consensus cluster.

Felipe Mendiburu

agricolae

Statistical Procedures for Agricultural Research

grass function

A data frame with 48 observations on the following 3 variables.<dl>
 <dt><code>judge</code></dt>
<dd>a numeric vector</dd> <dt><code>trt</code></dt>
<dd>a factor with levels <code>t1</code> <code>t2</code> <code>t3</code> <code>t4</code></dd> <dt><code>evaluation</code></dt>
<dd>a numeric vector</dd> 
</dl>

Format

Data for Friedman test — grass

A data frame with 48 observations on the following 3 variables.<dl>
 <dt><code>judge</code></dt>
<dd>a numeric vector</dd>

 <dt><code>trt</code></dt>
<dd>a factor with levels <code>t1</code> <code>t2</code> <code>t3</code> <code>t4</code></dd>

 <dt><code>evaluation</code></dt>
<dd>a numeric vector</dd>

 
</dl>

grass: Data for Friedman test

Description

Usage

Arguments

Format

Details

References

Examples