Statistics

1. Random event, experiment, definition of probability. Conditional probability, independent events and its probability.
2. Random variable. Discrete random variable, probability function, distribution function of a discrete random variable. Numerical characteristics. Discrete uniform distribution, Poisson distribution, binomial distribution, hypergeometric distribution.
3. Continuous random variable. Probability density function, distribution function of a continuous random variable, numerical characteristics. Uniform distribution, exponential distribution, normal distribution.
4. Population. Data sample, frequency distributions.
5. Random sample and empirical characteristics.
6. Point and interval estimates of parameters, method of moments and maximum likelihood method.
7. Correlation and regression analysis, covariant and correlation matrix.
8. Approximation by the method of least squares.
9. Tests of hypotheses.
10. F-test of the equality of two variances.
11. Unpaired and paired two-sample t-tests.
12. Pearson's test, Kolmogorov–Smirnov test, two-sample Kolmogorov–Smirnov test.
13. Dixon's Q test, Grubbs' test for outliers.
14. Reserve.