A small number of the datasets have been slightly altered, and their
associated documentation accordingly. The changes consist of adding some
useful extra variables to the three time series data sets
airpass.df, beer.df and
larain.df. These variables are t which is just
a time index to save the user creating it if they want to fit a lag
response model, and either month and year or
both. These are factor variables giving the year the observation
recorded, and if relevant the month. These extra variables can be used
for time series analysis or plots.
In addition we have made an attempt to use SI units rather than imperial units where sensible. Some examples of where it is sensible: converting inches to millimetres, pounds to kilograms, and acre-feet/gallons to litres (or megalitres). Some examples of where it is not sensible are carats (industry standard) and converting blood pressue to kiloPascals instead of millimetres of mecury (mm Hg), which again is the health profession standard. If these conversions have been made, then they have been done as extra variables added to the data set, rather than replacing the original measurements. The logic for this is to preseve the data sets as is to avoid lecture notes mismatches - at least for the time being.
A repository for the University of Auckland s20x R library. This library is used in our large undergrad classes STATS 201, STATS 208 and BIOSCI 209
We will attempt to add information about the changes in each new release (whether it makes it to CRAN or not) here, from version 3.1-21 onwards
Ben Stevenson added some code to summary2way so the attribute
information from TukeyHSD is preserved. That is so you see
this
> summary2way(fit, page = "interaction")
Tukey multiple comparisons of means
95% family-wise confidence level
Fit: aov(formula = fit)
$`store:crust`
instead of this
> summary2way(fit, page = "interaction")
$`store:crust`
A new function called modcheck has been added. This
allows the plotting of all four standard 20x model checking plots: a
pred-res or equality of variance plot, a normal Q-Q plot, a histogram of
the residuals, and a Cook’s distance plot, to be drawn on the same plot
at once. This function needed a much more flexible version of
normcheck, and needed modifications to
eovcheck and cooks20x. I have not put it on
CRAN yet because of the chance that it will fail for our current
students. We really need some unit testing in this package so
that this process can be sped up.