*Kickstarting*
R - ANOVAs
## ANOVAs

For more complex hypotheses, we'll have to go to ANOVAs. As a pretty artifical
example, we'll combine the test performed in the t-test example with another
test in a simple ANOVA using `aov()`

, asking if `case`

and `education`

__and__ their interaction have any association
with `age`

.

> anova(aov(age~case*education,infert))
Analysis of Variance Table
Response: age
Df Sum Sq Mean Sq F value Pr(>F)
case 1 0.1 0.1 0.0034 0.9536
education 2 753.3 376.7 15.0456 6.938e-07
case:education 2 0.2 0.1 0.0031 0.9969
Residuals 242 6058.4 25.0

We're getting pretty much the same answers, except that the variance has been
partitioned appropriately for looking at the more complex question.
`anova()`

produces the ANOVA table from the output of
`aov()`

.

For a much more detailed treatment of ANOVAs and other methods, get the
VR package or Notes on the use of R..."
in the Contributed documentation page.
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