Syllabus
Probability random trial, random event, probability(classical, geometrical), recapitulation of elements of combinatorics independence of random events, conditional probability, complete probability theorem, the theorem of Bayes random variables and distribution of probability, expected value, variance, other characteristics discrete and continuos distributions (alternative, binomial, hypergeometric, geometric, Poisson, uniform, exponential), probability density, distribution function random vectors, joint and marginal probability density and distribution function independence of random variables, covariance, corellation operation with random variables, Law of the great numbers, central limit theorem, normal distribution, distribution chi-square, Student, Fischer
Statistics random sample, parameter estimate, testing hypotheses principle, statistical discrepancy basic types of statistic tests (t-test, one-sample, two-sample, corellation coefficient) linear regression, method of least squares analysis of variance contingency table, some other tests (McNemar), Pearson's chi-square test non-parametric methods (sign test, Wilcoxon test, Spearmann coefficient) descriptive statistics, data processing
Annotation
Random trial, random event, probability, distribution of probablity, probability density, distribution function. Operations with random variables, Law of great numbers, central limit theorem.
Distribution: normal, chi-square, Student. Testing hypotheses, statistical tests, data processing