MATH-312
Statistical Inference
Maximum likelihood principle, Bayesian estimation, properties of estimators, sufficiency, likelihood ratio tests, chi-square distribution, t distribution, F distribution, power, nonparametrics, bootstrap, and Markov Chain Monte Carlo.
Prerequisites:
- [MATH-256] Introduction to Probability and Statistics -- with a grade of at least C.
- [MATH-311] Probability Theory -- with a grade of at least C.
Teaching history:
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2020 Spring-- G. Sokolov.
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2018 Spring-- G. Sokolov.
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2016 Spring-- A. Schwab-McCoy.
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2014 Spring-- G. Malla.