Curricula

Objectives

The student understands the concept of probability as a measure of uncertainty. They have a view how this measure can be applied to the random real-world phenomena and statistical analysis.

Content

Random phenomena and the concept of probability. The conditional probability and independency, Bayes’ rule. The random variable, binomial-, Poisson- and normal distribution, the central limit theorem. A review of statistical analysis. Application examples.

Time and location

Course is implemented between 31.8 - 23.10.

Learning materials and recommended literature

Materials in the e-learning environment.

Teaching methods

- lectures
- independent study

Exam dates and retake possibilities

Date and method of the exam will be announced in the course opening.

Alternative completion methods

The admission procedures are described in the degree rule and the study guide. The teacher of the course will give you more information on possible specific course practices.

Student workload

One credit (1 Cr) corresponds to an average of 27 hours of work.

- lectures 39 h
- independent study 42 h
Total 81 h

Content scheduling

Will be agreed on the first contact lesson of the course.

Further information for students

Arviointi kokeen ja kotitehtävien mukaan.
Ei läsnäolovelvoitetta.

Evaluation scale

Pass/Fail

Evaluation criteria, satisfactory (1-2)

Pass: The student shows in the exam that they understand the concept of probability and is able to apply it to random real-life phenomena and statistical analysis.

The assessment is based on exam and exercises.

Evaluation criteria, pass/failed

Pass: The student shows in the exam that they understand the concept of probability and is able to apply it to random real-life phenomena and statistical analysis. The assessment is based on exam and exercises.

Prerequisites

Basic skills of algebra and analysis, integral