penicillin

Values are arranged in decreasing order of absolute magnitude.
Name of the contrast effect is given as the row name of each value.
Daniel(1959) uses the data to illustrate the use of half-normal plots.
In his words: "We need, of course, some rule of inference that will help us to 
be objective in judging whether or not the largest effects are real."

datasets

Provides the function qqtest which incorporates uncertainty in its
qqplot display(s) so that the user might have a better sense of the
evidence against the specified distributional hypothesis.  qqtest draws a
quantile quantile plot for visually assessing whether the data come from a
test distribution that has been defined in one of many ways.  The vertical
axis plots the data quantiles, the horizontal those of a test distribution.
The default behaviour generates 1000 samples from the test distribution and
overlays the plot with shaded pointwise interval estimates for the ordered
quantiles from the test distribution.  A small number of independently
generated exemplar quantile plots can also be overlaid.  Both the interval
estimates and the exemplars provide different comparative information to
assess the evidence provided by the qqplot for or against the hypothesis
that the data come from the test distribution (default is normal or
gaussian).  Finally, a visual test of significance (a lineup plot) can also
be displayed to test the null hypothesis that the data come from the test
distribution.

Wayne Oldford

qqtest

Self Calibrating Quantile-Quantile Plots for Visual Testing

penicillin function

A data frame with 31 rows and 1 variate:<dl class="dl-horizontal">
 <dt>value</dt><dd>value of contrast for that row</dd>
</dl>

Format

31 contrast sums from a 32 run 2^(5-0) factorial experiment on penicillin production. — penicillin

A data frame with 31 rows and 1 variate:<dl class='dl-horizontal'>
 <dt>value</dt><dd>value of contrast for that row</dd>
</dl>

penicillin: 31 contrast sums from a 32 run 2^(5-0) factorial experiment on penicillin production.

Description

Usage

Arguments

Format

Details