If you wanted to fit a linear regression model with R, you could do so with
the lm function. Calling anova on the output of the regression would give
you a regression anova table.

model <- lm(delivered_seeing ~ zeenith_seeing, data = delsee)
anova(model)

You would need non-zero residuals for that to be useful of course.

Otherwise, you need to stack your *_seeing columns into one column with
another column saying which kind of seeing it was and then:

model.aov <- aov(seeing ~ factor(kind), data = delsee2)

You could do the stacking in a number of ways. My favorite is to use the
gather function in the tidyr package.

aov is just a wrapper around lm, so just take the same approach as before
to get the ANOVA table. Hope that helps.

On Thu, Apr 21, 2016, 15:10 Uwe Brauer <oub@mat.ucm.es> wrote:

> Hello
>
> Using Kubuntu I just installed R and the following code works nicely
>
> #+tblname: delsee
> | airmass | zenith_seeing | delivered_seeing |
> |---------+---------------+------------------|
> |     1.3 |          0.95 |        1.1119612 |
> |     1.3 |           1.0 |        1.1704854 |
> |     1.3 |           1.1 |        1.2875340 |
> |     1.3 |           1.2 |        1.4045825 |
> #+TBLFM: $3=$2*($1**0.6)
>
>
> #+begin_src R :results output :var delsee=delsee
> summary(delsee)
> #+end_src
>
>
> Does somebody know whether I could do an ANOVA, comparing these columns
> (which does not make much sense, but this is not the point.
>
> Any help is strongly appreciated.
>
> thanks
>
> Uwe Brauer
>
>
>