Another vector for disruption is with statistics. Scientists use statistics to analyze the results of their experiments all the time. Unfortunately, most scient

Another vector for disruption is with statistics. Scientists use statistics to analyze the results of their experiments all the time. Unfortunately, most scientists are not statisticians. They spend a lot of time on statistics that they want to spend doing things they're good at. They make lots of mistakes, for example using the wrong statistical test or deciding what test to use after the experiment, etc. With today's computer speeds there is no reason to do the statistics the way they're doing it. You don't need to make strong and unjustified assumptions about your data because then you can use a simple T-test. Today with simulation you can do pretty much any statistical test you want. You can do Bayesian inference. However, most of these scientists are not capable of programming that themselves in R. What is needed is a simple GUI interface where they can state their assumptions and enter their data. Then the program calculates their posteriors and does any hypothesis test they want. The statistics scientists use today are optimized for pen and paper. The assumptions no longer hold. Who cares if the computation takes 500 milliseconds on a computer instead of 3 milliseconds?