Learning outcomes
After the course the student can:
- perform simple calculations of university-level mathematics on the course topics on pen and paper.
- explain some main principles of statistical testing and estimation.
- apply basic statistical testing and estimation in specific cases, selecting the methods according to the requirements set by data.
- use the R environment as a simple calculator and a visualization tool for basic presentation of functions and data.
- use the R environment to perform basic statistical testing and estimation, simulate data from simple probabilistic models and calculate and analyze estimates from data.
Contents
- Calculus
- Linear algebra
- Probability
- Basic probability and statistical models
- Estimators, maximum likelihood
- Hypothesis testing (t-test, U-test, Fisher’s exact test, permutation testing)
- Required components and the resulting number of credit units are assigned in accordance with the personal study plan
Modes of study
- Degree Programme Students
- Other Students
- Open University Students
- Doctoral Students
- Exchange Students
Evaluation
Numeric 1-5.Belongs to following study modules
2018–2019
