\HeaderA{npk}{Classical N, P, K Factorial Experiment}{npk}
\keyword{datasets}{npk}
\begin{Description}\relax
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.
\end{Description}
\begin{Usage}
\begin{verbatim}
npk
\end{verbatim}
\end{Usage}
\begin{Format}\relax
The \code{npk} data frame has 24 rows and 5 columns:
\describe{
\item[\code{block}] which block (label 1 to 6).

\item[\code{N}] indicator (0/1) for the application of nitrogen.

\item[\code{P}] indicator (0/1) for the application of phosphate.

\item[\code{K}] indicator (0/1) for the application of potassium.

\item[\code{yield}] Yield of peas, in pounds/plot (the plots were (1/70) acre).
}
\end{Format}
\begin{Source}\relax
Imperial College, London, M.Sc. exercise sheet.
\end{Source}
\begin{References}\relax
Venables, W. N. and Ripley, B. D. (2002)
\emph{Modern Applied Statistics with S.} Fourth edition.  Springer.
\end{References}
\begin{Examples}
\begin{ExampleCode}
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)
\end{ExampleCode}
\end{Examples}

