75368 - Statistics

Course Unit Page

Academic Year 2018/2019

Learning outcomes

At the end of the course the student is introduced to the basic concepts of probability, with particular reference to their role in statistics. In particular, the student is able to compute the probability of complex events using fundamental probability axioms and theorems, analyze standard examples of random variables and compute their moments.

Course contents

The main discrete and continuous probabilistic distributions. Essential concepts of statistical inference. Point estimation and confidence intervals. Statistical tests about normal (Gaussian) parameters. Tests about frequencies. One-factor and multiple ANOVA. Nonparametric tests of goodness-of-fit, independence, two-sample comparison.

Readings/Bibliography

A.M.Mood, F.A.Graybill, D.C.Boes, Introduction to the Theory of Statistics, 3rd Edition Paperback – International Edition.
G.Casella, R.L.Berger, Statistical inference.
L.Wasserman, All of Statistics: A Concise Course in Statistical Inference. Springer Texts in Statistics.

Teaching methods

Lessons will include a theoretical part and some applications and exercises.

Assessment methods

Written test about all of the topics faced during the course, composed by three esercises. The first exercise is related to probability, and ranges between 10 and 12 points. The other exercises are related to statistical inference, and are valued 9-10 points each. Integrative oral conversation (optional). Candidates have the possibility to reject a positive result only once.

Teaching tools

Some detailed learning sheets will be available to the students. A preliminary version of them is already available on the web platform AMS Campus. All these sheets are written in English.

Office hours

See the website of Maurizio Brizzi