Elements of Probability Theory Course code
MLM6197.DT
old course code
Course title in Estonian
Tõenäosusteooria elemendid
Course title in English
Elements of Probability Theory
ECTS credits
6.0
Assessment form
Examination
lecturer of 2023/2024 Autumn semester
Tõnu Tõnso (language of instruction:Estonian)
lecturer of 2023/2024 Spring semester
Not opened for teaching. Click the study programme link below to see the nominal division schedule.
Course aims
The aim of the course is to introduce the basic concepts and methods of probability theory, learn to solve the problems, where the probability approach is required.
Brief description of the course
The basic concepts of probability theory. Computing classic probability. Relative frequency. Statistical probability. Geometric probability. Probability sum and product rule. Using combinatorics. Conditional probability, total probability formula and Bayes’ formula. Bernoulli’s formula. The most probable number of events in case of repeated experiments. The main principles of data processing. General population and representative sample. Variational series. Frequency table and distribution table. Data representation. Mean value. Median. Mode. Using different statistical averages. Variance and its uses. Distribution of the random variable. Probability density function. Mean value and standard deviation of the random variable. Normal distribution. Normal distribution as an approximation of binomial distribution. Moivre-Laplace formula. Correlation. Pearson correlation coefficient. Spearman's rank correlation coefficient.
Learning outcomes in the course
Upon completing the course the student:
- is able to use the notions from the course and apply the formulas;
- is able to solve problems of probability theory;
- is able to compute mean value and standard deviation, use normal distribution, find Perason and Spearman’s correlation coefficients.
Teacher
lektor Tõnu Tõnso
Study programmes containing that course 