Probability and Statistics
Included:
- Elements of combinatorics.
- Probability of random events.
- Independence of random events.
- Random vectors: marginal and conditional distributions.
- Functions of random variables.
- Numerical properties of random variables: mathematical expectation, variance of a random variable, correlation coefficient between two random variables.
- Central border theorem.
- Elements of statistics: population and sample, parameters and statistics.
- Basic data processing and descriptive statistics.
- Sample statistics distributions: normal, t-distribution, Chi-square and F-distribution.
- Evaluation of landmark parameters: method of moments, method of maximum suitability, confidence intervals.
- Parameter tests.
- Nonparametric tests.
- Linear regression, estimation by the least squares method.m events.
- Properties of probabilities.
- Discrete probability space.
- Conditional probability.