Comparison of means in R I have the following boxplots of a quantitative trai by medication group. I would like to compare Med0 against all the other groups. Which statistical test in R would be appropriate in this case?Med0 are basically healthy individuals and med1-4 cases in different medications. All groups contain independent samples.
Thanks
 A: Would recommend using a T-Test for comparison of means for each individual comparison against the Med0 group:
$$ T_k = \frac{\bar{X}_2 - \bar{X}_1}{\sqrt{\frac{s_1^2}{n_1}+\frac{s_2^2}{n_2}}}$$
Where
$$\qquad k = \min( n_1 - 1, n_2 - 1)$$
$$\qquad s^2 = \frac{\sum (X_{i} - \bar{X})^2}{n-1}$$
This can be done in R with the following command:
t.test(Med0,Med1) 

A: Variances do not look equal, this can violate the t-test assumptions. See below from SPSS documentation:

Assumption #6: There needs to be homogeneity of variances. You can
  test this assumption in SPSS Statistics using Levene’s test for
  homogeneity of variances. In our enhanced independent t-test guide, we
  (a) show you how to perform Levene’s test for homogeneity of variances
  in SPSS Statistics, (b) explain some of the things you will need to
  consider when interpreting your data, and (c) present possible ways to
  continue with your analysis if your data fails to meet this assumption
  https://statistics.laerd.com/spss-tutorials/independent-t-test-using-spss-statistics.php

In R you can test homogeneity of variances via 
library(car)
leveneTest

I recommend you use pairwise.wilcox.test for nonparametic approach of testing equality of central values for multiple groups.
