- Understand the concept of statistical models and apply the principles of sufficient statistics and related theorems.
- Find point estimators (moment estimator and maximum likelihood estimator) and evaluate their properties (unbiasedness, efficiency, sufficiency, and consistency).
- Calculate and interpret Fisher information.
- Investigate the quality of an estimator in the finite and asymptotic case.
- Perform interval estimation and conduct hypothesis testing and understand its implications (likelihood ratio test).
- Evaluate hypothesis tests (controlling type I/II errors, most powerful tests, p-values).
- Derive confidence intervals using different methods and evaluate their properties.
- Interpret and communicate statistical results effectively.
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Fundamental concepts of probability, statistical inference, hypothesis testing, key theorems and techniques in sufficient statistics, point estimation, and interval estimation, application of statistical methods in real-world scenarios.
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