Upon successful completion of the course, the student will be able to
use fundamental concepts, and the connection between them, in statistics and probability theory.
solve simple combinatorial problems
establish probability models for everyday probability problems and explain why these models can be used
use the most common probability models and their properties, as well as the central limit theorem and hypothesis testing, to analyse random data samples.
Course contents
Basic statistics, probability theory, probability models, moment-generating functions, random variables, expectation, variance, conditional expectation, simultaneous distribution, central limit theorem, stochastic processes in discrete and continuous time, point estimation and confidence intervals including maximum likelihood and moment method, hypothesis testing. Applications.
Teaching methods
Lectures, group work and compulsory group presentation. The course has an expected workload of about 267 hours.
Examination requirements
Compulsory submissions must be approved, see Canvas for more information.
Assessment methods and criteria
Graded 5-hour written examination.
Evaluation
The person responsible for the course decides, in cooperation with student representative, the form of student evaluation and whether the course is to have a midway or end of course evaluation in accordance with the quality system for education, chapter 4.1.