1 min read

data analysis principles

I was looking through some of my old notes and came across this list of “data analysis principles”.

  • answer the question
  • understand where the data came from
  • make a graph
  • does the result make sense?
  • if it seems too good to be true, it probably is
  • form a diagnostic checklist: think of ways things could go wrong and how they might be revealed
  • follow up on all aberrations
  • every estimate needs an SE
  • consider taking logs
  • consider taking differences
  • use common axis scales
  • avoid normality assumptions
  • remember Simpson’s paradox

I also found this list of “key statistics concepts”.

  • separate the population and the sample, the parameter and the estimate
  • imagine doing it again: estimates have distributions
  • suppose there were no effect; are the observed data unusual?
  • scatterplots