corn

Data from a completely randomized design where four different methods of growing
 corn resulted in various yields per acre on various plots of ground where the 
 four methods were tried. Ordinarily, only one statistical analysis is used, 
 but here we will use the kuskal-wallis test so that a rough comparison may be made
 with the mediasn test.

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

corn function

A data frame with 34 observations on the following 3 variables.<dl>
 <dt><code>method</code></dt>
<dd>a numeric vector</dd> <dt><code>observation</code></dt>
<dd>a numeric vector</dd> <dt><code>rx</code></dt>
<dd>a numeric vector</dd> 
</dl>

Format

Data of corn — corn

A data frame with 34 observations on the following 3 variables.<dl>
 <dt><code>method</code></dt>
<dd>a numeric vector</dd>

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

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

 
</dl>

corn: Data of corn

Description

Usage

Arguments

Format

Details

References

Examples