I help a friend of mine to understand material in an econometrics course. This is also a good exercise for me since soon I will start as a TA. The challenge is that she does not have sufficient knowledge in statistics and also not strong in mathematics. For example, starting explaining hypothesis testing and confidence intervals, I realize that she is not comfortable with the fact that OLS estimate is a random variable and has a distribution. Furthermore, I have to go back and explain first what a random variable is, what is pdf and pmf etc. But then this person gets frustrated and starts to think that she is "stupid". I frankly believe that training her for passing the exam is a fully doable task, but I need to bring in more "applied" stuff into the learning process. That is, not only explaining the theory (statistics and econometrics) and running regressions on the data, but show some nice (maybe funny) examples, illustrations etc. So far I've found some nice applets on the WLLN and CLT and good lecture notes for introductory statistics by MIT. But still too few entertainment.

I want also to clarify that I am not trying to make her an econometrician, but to give basic intuition into the subjects such that she understands what she is doing, not just blindly running regressions.

I would appreciate any suggestions and resource references. Feel free to give your advises.

  • $\begingroup$ I suspect that the question might be closed as primarily opinion-based, but here is a nice visual introduction to probability and statistics: students.brown.edu/seeing-theory $\endgroup$
    – T.E.G.
    Mar 5 '18 at 16:19
  • $\begingroup$ @T.E.G. wow it looks really good, thank you for sharing! $\endgroup$
    – tosik
    Mar 5 '18 at 16:22

I recommend doing lots of stuff by simulation (if she has some coding knowledge).

The other two resources I would suggest are Peter Kennedy's A Guide to Econometrics and Andrew Vicker's What Is a p-value Anyway? for more basic stats questions.

Another good teaching resource is Gelman and Nolan's Teaching Statistics.


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