Thoughts about Presentations on Inference
Yesterday, I finished my semester project for my randomized algorithms course. I started the project almost a month in advance since I knew there was going to be a significant amount of research and reading to do. The original plan was to create a mathematica module for processing Exponential Random Graph simulations. The concept is this:
You have some observed social network, collected from data or in the field. You want to know things about the relationships of people in the network, like, how likely are people to form connections randomly or do they form connections based on other sociological things. For example, if Alice is connected to both Bob and Eve, is there likely going to be a relationship between Bob and Eve? In other words, do they complete the triangle? Standard random graph models can’t test for this but we can use exponential random graphs. The output of the algorithm is a set of values that indicate how strong various network structures are.
My presentation went alright. In the mathematical sciences (engineering, math, etc) proofs are the only method you can use to show something is true. In the applied sciences (communications, sociology, statistics) the only method you can use to prove something is statistical inference. So, explaining inference to engineers is difficult since they don’t encounter it (I think they should!). Explaining math to social scientists is challenging since they’re not familiar with proof techniques (what is the contrapositive again?)
I haven’t finished the paper yet (almost done) and I will post the results here shortly. In the mean time, I’ve compiled some of my thoughts about approaching this topic in the future. This is what I want to study (using computer science theory in other fields) so I am noting this for posterity.
- Use more visualizations to explain inference. Mathematicians love proofs and it is ok to use math on your slides. However, when talking about statistical inference, you’re looking at how something observed fits something hypothesized. The best way to do this, I suspect, is to plaster a N(0,1) curve on the slides and point to where things fit.
- For social networks stuff, use examples! I used a couple examples in my slides and people found it helpful and interesting. There are so many great visualization tools for social networks, so I should use them more.
- Take a course on econometrics. I’m doing this next year. Econometrics is using statistical inference to reach economic conclusions. There has to be some good techniques they use.
- Write the slides AFTER you write the paper. In this case, I was so worried about the presentation, I did it before I wrote the paper and ended up rushing the paper. Next time, I’ll flip it and spend time worrying more about visualizations and teaching people than plastering equations on slides.