As we discussed in our last five-minutes of science, a new perspective in Plant Cell (Reassess the t Test) by plant researchers from UCDavis and UMN addresses the growing complexity of studies examining how plants interact with their environment. In many cases such studies employ arrays of pairwise t-tests, but the authors show how linear models such as ANOVA, provide more statistical power to assess these interactions. Though ease-of-use in Excel strongly favours the t-test, the free statistical package R can grant us all the ability to use ANOVA. These are also the types of questions we are addressing in the Python group (now more an “R” group); anyone interested is welcome to join!

Full disclosure: There is a reason R is not more popular than Excel; the learning curve is steep. Also, for those unaware, I am biased against the t-test (probably more than I realize), though I admit there is a place for it.