Fundamentals of statistics 1300-OPST2CW

The lecture has the task to know with the following subject matters:
• elements of probability definitions: classical, geometrical, axiomaltical, statistical,
• random variables discrete and continuous and their parameters. Distributions of random variables: binomial, Poisson, normal, chi-square, Student`s distributions,
• n-dimensional random variables,
• basic statistics notions, methods of sample collections,
• one dimensional statistical series and their elaboration, distributive series, diagram, histogram, distribution parameters,
• point estimation, confidence intervals for average value and variance,
• verification of statistical hypothesises, tests of significances,
• two-dimensional populations, regression lines, coefficient of linear correlations (least squares method), curvilinear correlation.

The exercises will be devoted for solving of the problems based on the theory presented on lectures,
• are synchronized with lectures,
• teach to solve of exercises, calculations,
• teach to solve some examples illustrative the lecture theory,
• teach to interpret of the obtained results,
• indicate numerical programs for the statistical problems.

Type of course

obligatory courses

Prerequisites (description)

Student should have a basic knowledge connected with: • differential calculus for one-variable function, • integral calculus, definite Riemann integral, improper integral.

Learning outcomes

After completion of lecture a student:
• calculates statistical parameters, creates distributive series, interprets their graphically,
• calculates confidence intervals for average value and variance,
• verifies statistical hypothesis connected with parameters and distributions (chi-square test, Kolmogov`s test),
• determines equations of regression lines and coefficients of linear correlations,
• determines curvilinear regressions,
• contrives to interpret results obtained by using statistical computer programs.

Assessment criteria

Credit requirements:
• knowledge of the materials presented on lectures,
• applications of knowledge to solve practical examples.

Written test with applications of received knowledge to solve practical problems (numerical examples), there is possible to use lecture notes.