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<html><head><title>R: Classical N, P, K Factorial Experiment</title>
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<table width="100%" summary="page for npk {MASS}"><tr><td>npk {MASS}</td><td align="right">R Documentation</td></tr></table>
<h2>Classical N, P, K Factorial Experiment</h2>
<h3>Description</h3>
<p>
A classical N, P, K (nitrogen, phosphate, potassium) factorial
experiment on the growth of peas conducted on 6 blocks. Each half of a
fractional factorial design confounding the NPK interaction was used
on 3 of the plots.
</p>
<h3>Usage</h3>
<pre>
npk
</pre>
<h3>Format</h3>
<p>
The <code>npk</code> data frame has 24 rows and 5 columns:
<dl>
<dt><code>block</code></dt><dd>which block (label 1 to 6).
</dd>
<dt><code>N</code></dt><dd>indicator (0/1) for the application of nitrogen.
</dd>
<dt><code>P</code></dt><dd>indicator (0/1) for the application of phosphate.
</dd>
<dt><code>K</code></dt><dd>indicator (0/1) for the application of potassium.
</dd>
<dt><code>yield</code></dt><dd>Yield of peas, in pounds/plot (the plots were (1/70) acre).
</dd></dl>
<h3>Source</h3>
<p>
Imperial College, London, M.Sc. exercise sheet.
</p>
<h3>References</h3>
<p>
Venables, W. N. and Ripley, B. D. (2002)
<EM>Modern Applied Statistics with S.</EM> Fourth edition. Springer.
</p>
<h3>Examples</h3>
<pre>
options(contrasts = c("contr.sum", "contr.poly"))
npk.aov <- aov(yield ~ block + N*P*K, npk)
npk.aov
summary(npk.aov)
alias(npk.aov)
coef(npk.aov)
options(contrasts = c("contr.treatment", "contr.poly"))
npk.aov1 <- aov(yield ~ block + N + K, data = npk)
summary.lm(npk.aov1)
se.contrast(npk.aov1, list(N=="0", N=="1"), data = npk)
model.tables(npk.aov1, type = "means", se = TRUE)
</pre>
<hr><div align="center">[Package <em>MASS</em> version 7.2-44 <a href="00Index.html">Index]</a></div>
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