It’s about time

I speak at Jared’s NYR conference every year (see here for some past talks). It’s always fun. Here’s the title/abstract for the talk I’ll be giving this year.

It’s About Time

Statistical processes occur in time, but this is often not accounted for in the methods we use and the models we fit. Examples include imbalance in causal inference, generalization from A/B tests even when there is balance, sequential analysis, adjustment for pre-treatment measurements, poll aggregation, spatial and network models, chess ratings, sports analytics, and the replication crisis in science. The point of this talk is to motivate you to include time as a factor in your statistical analyses. This may change how you think about many applied problems!

P.S. The talk happened! and the video is here.

5 thoughts on “It’s about time

  1. The double-entendre time title I always want to use, but never have! This talk sounds great, I hope they will post it as usual. And that someone will help me solve my time problems in models — I have some tree rings, ripening winegrapes and more where ignoring time isn’t a good option. I am especially interested in sequential process models where both time and temperature matter and there’s an inherent delay between processes for development to happen. Actually, I need a talk: It’s about time, and temperature.

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