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 <o...@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 > > >
