2021-22 2020-21 2019-20 2018-19 2017-18 2016-17 2015-16

The course aim at introducing the fundamentals of descriptive statistics, probability and parametric inferential statistics.

## Expected results

Students will be able to carry out basic explorative analyses and inferences on datasets, they will know the main probability distributions and will be able to understand statistical analyses conducted by others; moreover, they will know simple methods for the problem of binary classification, and will be able to evaluate their performances. The students will also acquire the fundamental competences for studying more sophisticated techniques for data analysis and data modeling.

## News

Date Info
01/06/2022 Date change for the written test of Statistics and data analytics
The written test of Statistics and data analytics of June has been postponed to June, 17th at 14:30 in the sigma gamma classroom of the Computer science department.
06/04/2022 Modality change for the 7/4 lecture of «Statistics and data analysis»
The 7/4 lecture of the «Statistics and data analysis» will take place only remotely.
28/02/2022 Office hours on March, 10th
The office hours of March, 10th are canceled.
28/02/2022 Office hours for the spring semester
Office hours for the spring semester will be on Thursday from 17:00 in the teacher's office, starting from 03/03. To avoid crowds during the pandemic period, students are required to schedule an appointment.

## Language

Lectures are in italian.

## Course schedule

Lectures take place (until further notice) using a hybrid modality: in presence at the educational sector of "Città studi", and online through authentication to a zoom link published on the moodle page of the course. The schedule is as follows:

Day Hour Place
Tuesday 10:30 - 12:30 G11
Thursday 13:30 - 16:30 G11

Any change to the schedule will be announced in class and published in paragraph News of this page.

## Office hours

Thursday, 17:00. It is possible contact the teacher by e-mail, taking care to read in advance the guide prepared by Prof. Sebastiano Vigna and clearly specifying in the message the course name and the academic year. In particular, students are encouraged to always use their academic address (i.e. based on the domain studenti.unimi.it) signing with name and student ID number and recalling that the response time may vary depending on the teacher commitments.

### Course material

The parts on descriptive statistics are taken from the first three chapters of the textbook Ross, Introductory statistics, Academic press, 2010, ISBN 9780123743886 (marked by PS in the lectures calendar). These chapters (from the italian edition) can be downloaded through authentication using the previously described credentials.

The remaining part course is mainly based on the following textbook: Ross, S., Introduction to Probability and Statistics for Engineers and Scientists, Academic press, 2014, ISBN 978-0-12-394811-3 (marked by RPS in the lectures calendar).

Some lecutre notes for topics not covered by the textbooks are available through a github repository, as well as in a form directly executable in a Web browser.

## Syllabus

The course explains the topics listed in the lecture calendar.

### Prereqs

Students shall have passed the exam of «Calculus»; besides that, the course requires knowledge of the main topics of computer programming, and having passed the exam of «Discrete mathematics» is strongly suggested.

## Exam modalities

The exam consists of a written and an oral test, both relating to the topics covered in the course. The written test takes place in a computer-based room and it lasts two hours and a half. It is based on open-ended questions and on the analysis of a dataset through the adequate application of the statistical techniques described during the classes. The evaluation, with a mark of pass/fail, takes into account the level of mastery of the topics and the correct use of mathematical formalism.

The oral test, which is accessed after passing the written test, is based on the discussion of the written test answers and on questions concerning topics covered in the course. Its evaluation, expressed on a scale between 0 and 30, takes into account the level of mastery of the topics, the clarity, the language skills, and the correct use of technical jargon.

## Exam sessions

Session Date
June 13/06/2022 17/06/2022
July 04/07/2022
September 19/09/2022
January N/A
February N/A
February N/A