Sampling Techniques for Big Data
A.Y. 2019/2020
Learning objectives
The aim of the course is to introduce the most typical sampling methods to select a sub sample from a Big dataset. In addition, the theory of optimal design will be developed to enable students to select the most informative observations. The course will develop theoretical and computational aspects concerning its implementation.
Expected learning outcomes
At the end of the course students will be able to select a sample of informative observations from a Big Dataset, using software R.
Lesson period: Open sessions
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 currently not available
SECS-S/01 - STATISTICS - University credits: 6
Lessons: 40 hours