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{\Large \bf ST402 --- Principles and Methods of\\[2ex]
 Statistical Practice (Part II) }


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\section*{Course outline}

\begin{enumerate}
\item 
\underline{Introduction}: what is statistics, terminology and notation,
statistics from normal samples
(0.5 weeks)
\item  
\underline{Maximum likelihood estimation}: likelihood, sufficiency and
data compression,
maximum likelihood estimators (MLE), numerical computation of MLEs, EM
algorithms, Fisher information, Cram\'er-Rao inequality,
asymptotic properties of MLEs, bootstrap standard errors.
(2.5 weeks)
\item  
\underline{Hypotheses testing}:
basic setting, the Neyman-Pearson Lemma, uniformly most powerful tests,
likelihood ratio tests.
(1.5 weeks)
\item
\underline{Interval estimation}: what is an interval estimator, 
methods of pivotal functions, inverting tests, Bootstrap confidence
intervals. (0.5 weeks)
\end{enumerate}

\section*{References}
\begin{itemize}
\item
Azzalini, A. (1996). {\sl Statistical Inference Based on the Likelihood}.
Chapman \& Hall, London.
\item
Bickel, P.J. and Doksum, K.A. (2001). {\sl Mathematical Statistics} Vol.1
(2nd edition). Prentice Hall, New Jersey.
\item
Casella, G. and Berger, R.L. (2002). {\sl Statistical Inference} (2nd edition).
Duxbury.
\item
Knight, K. (2000). {\sl Mathematical Statistics}.
Chapman \& Hall, Boca Raton.
\item
Pawitan, Y. (2001). {\sl In All Likelihood}.
Clarendon Press, Oxford.
\end{itemize}
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