Statistics and Data Analysis
A.Y. 2019/2020
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: Third four month period
Assessment methods: Esame
Assessment result: voto verbalizzato in trentesimi
Single course
This course cannot be attended as a single course. Please check our list of single courses to find the ones available for enrolment.
Course syllabus and organization
Single session
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. Main topics are: 1. Introduction to Statistics and Data Analysis 2. Probability
Prerequisites for admission
Continuum mathematics
Teaching methods
Lectures on theoretical foundations and class-based problem solving activities
Teaching Resources
Sito web: http://ggianinicpsm.ariel.ctu.unimi.it/
Assessment methods and Criteria
Written examination assessing the ability to solve exercises concerning main topics of probability and statistics treated along the course. The difficulty of problems is paired to those that have been discussed and solved in lectures. The examination is t
INF/01 - INFORMATICS - University credits: 6
Lessons: 48 hours
Professor:
Gianini Gabriele
Shifts:
-
Professor:
Gianini Gabriele