cabbage

Cabbage yield in dependence of four doses of fertilizer.

datasets

Calculation of the parametric, nonparametric confidence intervals
for the difference or ratio of location parameters, nonparametric confidence interval
for the Behrens-Fisher problem and for the difference, ratio and odds-ratio of binomial
proportions for comparison of independent samples. Common wrapper functions to split
data sets and apply confidence intervals or tests to these subsets.
A by-statement allows calculation of CI separately for the levels of further factors.
CI are not adjusted for multiplicity.

Frank Schaarschmidt

pairwiseCI

Confidence Intervals for Two Sample Comparisons

Daniel Gerhard

cabbage function

A data frame with 20 observations on the following 2 variables.<dl class="dl-horizontal">
 <dt><code>Fert</code></dt><dd>a factor with levels <code>D1</code> <code>D2</code> <code>D3</code> <code>D4</code>, the different doses of fertilizer</dd>
 <dt><code>yield</code></dt><dd>a numeric vector, cabbage yield</dd>
 </dl>

Format

Yield of cabbage in one-factorial field trial — cabbage

A data frame with 20 observations on the following 2 variables.<dl class='dl-horizontal'>
 <dt><code>Fert</code></dt><dd>a factor with levels <code>D1</code> <code>D2</code> <code>D3</code> <code>D4</code>, the different doses of fertilizer</dd>
 <dt><code>yield</code></dt><dd>a numeric vector, cabbage yield</dd>
 </dl>

cabbage: Yield of cabbage in one-factorial field trial

Description

Usage

Arguments

Format

Examples