"Thanjavur Bragadeesh" <bragadeesh02 at hotmail.com> writes:
> Hi,
>
> I am trying to run an analysis of variance using R.
> in my data table "x" is a continuous variable lengthof 200 and
"p" is a
> categorical variable also of length 200 and p is anyone of three categories
> 1,2 or ,3.
> if I run
> summary(aov(x~p,data=test))
> I get
> Response: x
> Df Sum Sq Mean Sq F value Pr(>F)
> p 1 3174.7 3174.7 42.749 5.175e-10 ***
> Residuals 198 14704.2 74.3
If you get 1 DF for a variable with three different values, then it is
not a categorical variable from R's point of view, but a quantitative
one. So you need x~factor(p) here like you have below. Or convert "p"
to a factor before the analysis.
> and if I run
> summary(aov(x~as.factor(p), data=test)) # I get
>
> Response: x
> Df Sum Sq Mean Sq F value Pr(>F)
> as.factor(p) 2 3175.7 1587.8 21.275 4.31e-09 ***
> Residuals 197 14703.2 74.6
>
>
> Can anyone kindly explain the difference. How will it affect -correct way
to
> run - if it is a two-way anova where I have a second categorical variable
> "sex" - male or female.
>
> Many Thanks
>
>
> Yours sincerely,
>
> Bragadeesh
>
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