20430030 - STATISTICS

Acquire a good knowledge of basic statistical-mathematical methodologies for inference and statistical modeling problems. Also develop a practical knowledge of some specific statistical packages for the practical application of the theoretical tools acquired.
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Programme

- Random variables and their distribution, moment generating function, mean variance and
covariance.
- Random sampling model and statistical model.
- Statistics: concept, examples, sufficient statistics.
- Point estimators: definition and desired properties, moments, maximum likelihood and Bayes + computational methods. Methods for improving an estimator (for example Cramer-Rao)
- Confidence intervals
- Hypothesis testing
- Non-parametric methods: goodness-of-fit, contingency table, Kolmogorov-Smirnov and ranking
tests.
- Analysis of variance (ANOVA) and F.
- Regression

Core Documentation

Introduzione alla Statistica, S.M. Ross, Apogeo - Maggioli Editore.
testo aggiuntivo: Luca Leuzzi, Enzo Marinari, Giorgio Parisi
CALCOLO DELLE PROBABILITÀ: un trattatello per principianti volenterosi
Statistical Inference, Casella e Berger, 2nd Edition, Duxbury Advanced Series.

Reference Bibliography

Introduzione alla Statistica, S.M. Ross, Apogeo - Maggioli Editore. testo aggiuntivo: Luca Leuzzi, Enzo Marinari, Giorgio Parisi CALCOLO DELLE PROBABILITÀ: un trattatello per principianti volenterosi Statistical Inference, Casella e Berger, 2nd Edition, Duxbury Advanced Series.

Attendance

Optional

Type of evaluation

The written part will consist of 4 exercises, each one divided into 2 or 3 points. The questions will be of theoretical and practical nature. The oral part will be about commenting the written part and answering more questions, especially of theoretical nature.