One of the concerns raised during one of the recent QS meetups in NYC was how to analyze and interpret data. The research ideas, data collection and experimental design phases of the QS projects seem to be covered very well, but when it comes to analyzing our small QS datasets, there were not much showcases. So I thought I could help a bit, since statistics and applied research are my “bread and butter”, and decided to start a series of posts on my blog, providing hands-on examples and step-by-step instructions on how to conduct simple statistical tests and analyses. In my first post, I discuss significance testing of differences:
I would love to hear your opinion on this post, and what kind of analyses/tests I should cover next. Thanks a lot in advance!
Analytics just became personal! Can you express your everyday life in numbers? Can you improve your life by turning it into a series of games and experiments? Follow my personal “Measured Me” experiment to find out: http://www.measuredme.com