mathematics and statistics

Objectives

– Review (or see) the concepts of mathematical statistics and probabilistic tools that are essential for the Specialized Master’s courses.

– Practice on exercises.

– Get a brief overview of some upcoming courses.

Course outline

– Statistical models and point estimation (different estimators, bias, squared error, asymptotic properties, maximum likelihood, Bayesian framework).

– Optimal estimation (completeness, free and complete statistics, Fisher information, optimality).

– Confidence intervals (confidence interval and region, pivotal function, different methods for constructing a confidence interval, credibility interval in the Bayesian framework).

– Statistical tests (parametric tests, risk, level, power, efficiency, some non-parametric tests).

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Prerequisites

L3 or first-year engineering school courses in probability and measurement theory.