[R] Testing for normality in categorical data

[Bert Gunter]

Categorical data cannot be normal. What you are doing is statistical
nonsense, as your error messages suggest.  You need to consult a local
statistician for help.

Furthermore, statistical questions are generally OT on this list, which is
about R programming.

Bert Gunter

"The trouble with having an open mind is that people keep coming along and
sticking things into it."
-- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )


On Sat, Oct 5, 2019 at 6:19 AM Nancy Felix <nancyfelix25 using gmail.com> wrote:

> Hello
> I have data that are categorical both independent variable and dependent as
> well having levels more than 3. How can i check the normality of my data?
>
> I have tried the example given of Shapiro-Wilk for levels of factors
>
> data
> summary(chickwts)
>
> ## linear model and ANOVA
> fm <- lm(weight ~ feed, data = chickwts)
> anova(fm)
>
> ## QQ plot for residuals + Shapiro-Wilk test
> shapiro.test(residuals(fm))
>
> ## separate tests for all groups of observations
> ## (with some formatting)
> do.call("rbind", with(chickwts, tapply(weight, feed,
>    function(x) unlist(shapiro.test(x)[c("statistic", "p.value")]))))
>
> But ended up with Error message that x should be numeric and more comments
> see below.
> Hope to get some help on this
>
> Thanks,
> Nancy
>
> ## linear model and ANOVA
> > fm <- lm(retaliation ~ occupation, data = kazi)
> Warning messages:
> 1: In model.response(mf, "numeric") :
>   using type = "numeric" with a factor response will be ignored
> 2: In Ops.factor(y, z$residuals) : ‘-’ not meaningful for factors
> > anova(fm)
> Error in if (ssr < 1e-10 * mss) warning("ANOVA F-tests on an essentially
> perfect fit are unreliable") :
>   missing value where TRUE/FALSE needed
> In addition: Warning message:
> In Ops.factor(object$residuals, 2) : ‘^’ not meaningful for factors
> > ## QQ plot for residuals + Shapiro-Wilk test
> > shapiro.test(residuals(fm))
> Error in class(y) <- oldClass(x) :
>   adding class "factor" to an invalid object
> > ## separate tests for all groups of observations
> > ## (with some formatting)
> > do.call("rbind", with(kazi, tapply(retaliation, occupation,
> +                                        function(x)
> unlist(shapiro.test(x)[c("statistic", "p.value")]))))
>
>         [[alternative HTML version deleted]]
>
> ______________________________________________
> R-help using r-project.org mailing list -- To UNSUBSCRIBE and more, see
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>

	[[alternative HTML version deleted]]