[R] Need help understanding output from aov and from anova

[Suman Sundaresh]

Hi all,

I noticed something strange when I ran aov and anova.

vtot=c(7.29917, 7.29917, 7.29917)  #identical values
fac=as.factor(c(1,1,2))   #group 1 has first two elements, group 2 has
the 3rd element

When I run:
> anova(lm(vtot~fac))
Analysis of Variance Table

Response: vtot
          Df     Sum Sq    Mean Sq F value Pr(>F)
fac        1 1.6818e-30 1.6818e-30  0.3333 0.6667
Residuals  1 5.0455e-30 5.0455e-30


I get a p-value of 0.667. This seems strange to me. I would have
expected the p-value to be NaN.

Again, when I run:
> summary(aov(vtot~fac))
            Df     Sum Sq    Mean Sq F value Pr(>F)
fac          1 1.6818e-30 1.6818e-30  0.3333 0.6667
Residuals    1 5.0455e-30 5.0455e-30

Again same p-value.


Now, if I set fac to c(1,2,2) which is essentially just switching the groups.
fac=as.factor(c(1,2,2))

And run,
> anova(lm(vtot~fac))
Analysis of Variance Table

Response: vtot
          Df     Sum Sq    Mean Sq    F value    Pr(>F)
fac        1 6.7274e-30 6.7274e-30 1.3340e+32 < 2.2e-16 ***
Residuals  1  5.043e-62  5.043e-62
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1


The p-value is really significant which again looks very strange.

Please could someone shed some light on what I may be missing here?

Thanks very much.
Suman.