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Statistics and Data Analysis

A.Y. 2020/2021
6
Max ECTS
60
Overall hours
SSD
INF/01
Language
Italian
Learning objectives
The course aim at introducing the fundamentals of descriptive statistics, probability and parametric inferential statistics.
Expected learning outcomes
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.

Lesson period: First semester

Lessons timetable

Assessment methods: Esame
Assessment result: voto verbalizzato in trentesimi

Exams calendar

Single course

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Course syllabus and organization

Single session

Lesson period
First semester
Lectures and exercises in a virtual classroom based on the Zoom platform. Links are available on the Ariel site (see Reference materials)
Course syllabus
This course provides an introduction to the fundamental concepts of Probability and Inferential Statistics and points to their most relevant applications in Computer Science. The main topics are 1. Probability 2. Introduction to Statistics and Data Analysis.
Prerequisites for admission
Continuum mathematics
Teaching methods
Lectures on theoretical foundations and classroom-based problem-solving activities.
Teaching Resources
Assessment methods and Criteria
Written examination assessing the ability to solve exercises concerning main topics of probability and statistics treated during the course. The level of difficulty of the problems is comparable to that of the problems discussed during the lectures.
INF/01 - INFORMATICS - University credits: 6
Practicals: 36 hours
Lessons: 24 hours
Professor: Gianini Gabriele