Statistics and Data Analysis
A.Y. 2020/2021
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: Second semester
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
Responsible
Lesson period
Second semester
Lectures will be given either in asynchronous or synchronous mode via Zoom video conference system. In both modalities, lectures will be recorded and made available on the Ariel web site of the course
There will be no variations in the course program and examinations, except for the final written, which will take place on Zoom.
There will be no variations in the course program and examinations, except for the final written, which will take place on Zoom.
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
3. Random Variables and Probability Distributions
4. Mathematical Expectation
5. Discrete Probability Distributions
6. Continuous Probability Distributions
7. Functions of Random Variables
8. Fundamental Sampling Distributions and Data Descriptions
9. One- and Two-Sample Estimation Problems
10. Introduction to Hypotheses Testing
Main topics are:
1. Introduction to Statistics and Data Analysis
2. Probability
3. Random Variables and Probability Distributions
4. Mathematical Expectation
5. Discrete Probability Distributions
6. Continuous Probability Distributions
7. Functions of Random Variables
8. Fundamental Sampling Distributions and Data Descriptions
9. One- and Two-Sample Estimation Problems
10. Introduction to Hypotheses Testing
Prerequisites for admission
Students shall have passed the exam of "Matematica del continuo"; besides that, having passed the exam of "Matematica del discreto" is strongly suggested.
Teaching methods
Lectures on theoretical foundations and class-based problem solving activities
Teaching Resources
Course web site hosted by Ariel (https://ariel.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 to be completed in two hours time. The student is allowed to use statistical tables and the compendium of main formulas available for download from the course web site, together with a hand-held calculator. Other books and notes are not allowed.
INF/01 - INFORMATICS - University credits: 6
Practicals: 36 hours
Lessons: 24 hours
Lessons: 24 hours
Professors:
Boccignone Giuseppe, Cuculo Vittorio
Professor(s)