Some Basic Theory for Statistical Inference

E.J.G. Pitman

1. Basic principles of the theory of inference, the likelihood principle, sufficient statistics 2. Distance between probability measures 3. Sensitively of a family of probability measures with respect to a parameter 4. Sensitivity rating, conditional sensitivity, the discrimination rate statistic 5. Efficacy, sensitivity, the cramer-rao inequality 6. Many parameters, the sensitivity matrix 7. Asymptotic power of a test, asymptotic relative efficiency 8. Maximum likelihood estimation 9. The sample distribution function