Statistics Practice

Instructions

1. Write the model before deriving an estimator or test.
2. Keep p-values and posterior probabilities distinct.

Ordered items

1. Bias, variance, MSE, and consistencyStatistics · 7 min
2. Maximum likelihood estimation from a densityStatistics · 12 min
3. Bayesian posterior density and normalizationStatistics · 15 min
4. Method of moments and Bayesian updatingStatistics · 10 min
5. One-sided test, critical value, and p-valueStatistics · 12 min
6. Confidence interval with known varianceStatistics · 7 min
7. Test decisions and errorsStatistics · 7 min
8. Chi-square test for a contingency tableStatistics · 18 min
9. Simple regression from momentsStatistics · 7 min
10. Linear transformations and quadratic expectationsStatistics · 15 min
11. Type I error, Type II error, and powerStatistics · 5 min

Completion

Derive and interpret one estimator, interval, hypothesis test, and posterior update from first principles.