Syllabus of lecture
Combinatorics. Random events and their operations.
Probabilities of random events - classical, geometrical, statistical. Conditional probability. Composite probability.
Bernoulli sequence of independent random trials. Bayes formula.
Discrete and continuous random variable. Probability mass and density function. Probability distribution funciton.
Characteristics of random variables.
Basic types of probability distributions of discrete and continuous random variables.
Random vectors, their probabilities distribution and characteristics.
Processing of the statistical sample.
Random selection, point and interval estimates.
Testing of hypothesis - parametrical and nonparametrical tests.
Linear regression. Least square method.
Combinatorics. Random events and their operations.
Probabilities of random events - classical, geometrical, statistical. Conditional probability. Composite probability.
Bernoulli sequence of independent random trials. Bayes formula.
Discrete and continuous random variable. Probability mass and density function. Probability distribution funciton.
Characteristics of random variables.
Basic types of probability distributions of discrete and continuous random variables.
Random vectors, their probabilities distribution and characteristics.
Processing of the statistical sample.
Random selection, point and interval estimates.
Testing of hypothesis - parametrical and nonparametrical tests.
Linear regression. Least square method.