37679 - Statistics LM

Learning outcomes

At the end of the course the student has acquired knowledge of the mains tools of statistical inference, with particular reference to the concept of likelihood. In particular, he/she is able to:

- apply the proper methodologies for estimation and hypothesis testing;

- deal with joint, conditional and marginal distributions.

Course contents

Probability concepts: joint and marginal distributions, conditional distributions and independence, expected values, covariance and correlation
Statistical inference. The likelihood function.
Estimation theory. The point and interval estimation. Properties of estimators. Moments and maximum likelihood estimation method. Asymptotic properties of the maximum likelihood estimators.
The likelihood ratio test. Elements of Bayesian inference

Readings/Bibliography

Casella, G. and Berger, R.L. (2002). Statistical Inference, Wadsworth.
Teacher's notes.

Teaching methods

Classroom lessons.

Assessment methods

Written exam. The exam paper consists of questions concerning  the theoretical parts of the course and exercises aiming at evaluating if the students are able to solve probability and statistical inference problems. During the exam the use of textbooks, notes and computers tools are not allowed.

Teaching tools

Teacher's notes available at the web-site http://www2.stat.unibo.it/cagnone.

Office hours

See the website of Silvia Cagnone