Blog posts on statistics
2024
- What is an “economic model?” (Aug 13)
- Decomposing matrices of pairwise minima (May 5)
- Learning about a changing state (Jan 8)
2023
- Learning from correlated signals (Nov 24)
- Inverting matrices of pairwise minima (Aug 20)
- Correlation and concordance (Aug 3)
- The option value of waiting (Jul 16)
- Learning in continuous time (Jul 8)
- Paying for precision (Jul 4)
- Binary signals and posterior variances (Jul 2)
- Selection bias and fixed effects (Jan 25)
- Learning and persuasion (Jan 8)
- Learning from opinions (Jan 6)
2022
- Correlation and concatenation (Nov 17)
- The friendship paradox (Nov 16)
- Estimating treatment effects with OLS (Nov 12)
- Paying for the truth (Sep 1)
- Persuading with anecdotes (Mar 18)
- Ideological bias and trust in information sources (Mar 9)
- Pre-screening evidence (Mar 2)
- Communicating science (Feb 23)
- Hypothesis tests and Bayesian reasoning (Jan 6)
2021
- Learning from noisy signals (Oct 23)
- Snowball sampling bias in program evaluation (Sep 4)
- Improving human predictions (Aug 17)
- Coefficients of correlated regressors (Jul 7)
- Dyadic dependence (Feb 10)
- Ordinary and total least squares (Jan 11)
2020
- Estimating sensitive parameters (Oct 21)
- Lessons from Dave Maré (Aug 16)
- Understanding selection bias (Jul 3)
- Degree-preserving randomisation (Feb 17)
- Centrality rankings with noisy edge sets (Feb 14)