Course Details

Probability and mathematical statistics

Academic Year 2022/23

DA62 course is part of 21 study plans

D-K-E-SI (N) Summer Semester 1st year

D-K-E-SI (N) Summer Semester 1st year

D-K-E-SI (N) Summer Semester 1st year

D-K-E-SI (N) Summer Semester 1st year

D-K-E-SI (N) Summer Semester 1st year

D-K-C-SI (N) Summer Semester 1st year

D-K-C-SI (N) Summer Semester 1st year

D-K-C-SI (N) Summer Semester 1st year

D-K-C-SI (N) Summer Semester 1st year

D-K-C-SI (N) Summer Semester 1st year

D-P-E-SI (N) Summer Semester 1st year

D-P-E-SI (N) Summer Semester 1st year

D-P-E-SI (N) Summer Semester 1st year

D-P-E-SI (N) Summer Semester 1st year

D-P-E-SI (N) Summer Semester 1st year

D-P-C-SI (N) Summer Semester 1st year

D-P-C-SI (N) Summer Semester 1st year

D-P-C-SI (N) Summer Semester 1st year

D-P-C-SI (N) Summer Semester 1st year

D-P-C-SI (N) Summer Semester 1st year

unknown (history data) unknown (history data) 1st year

Continuous and discrete random variables (vectors), probability function, density function, probability, cumulative distribution, independent random variables, characteristics of distribution, transformation of random variables, conditional distribution, conditional mean, special distributions.
Random sampling, statistic, point estimate of distribution parameters and their functions, desirable properties of an estimator, estimator of correlation matrix, confidence interval for distribution parameter, fundamentals for testing hypotheses, tests of hypotheses for distribution parameters - one-sample analysis, two-sample analysis, goodness-of-fit test.

Course Guarantor

RNDr. Helena Koutková, CSc.

Institute

Institute of Mathematics and Descriptive Geometry

Objective

The correct grasp of the basic concepts and art of interpreting statistical outcomes.

Syllabus

1. - 8. Continuous and discrete random variables (vectors), probability function, density function, probability, cumulative distribution, independent random variables, characteristics of distribution, transformation of random variables, conditional distribution, conditional mean, special distributions.
9. - 13. Random sampling, statistic, point estimate of distribution parameters and their functions, desirable properties of an estimator, estimator of correlation matrix, confidence interval for distribution parameter, fundamentals for testing hypotheses, tests of hypotheses for distribution parameters - one-sample analysis, two-sample analysis, goodness-of-fit test.

Prerequisites

Basics of linear algebra, differentiation, integration.

Language of instruction

Czech

Credits

4 credits

Semester

summer

Forms and criteria of assessment

course-unit credit

Specification of controlled instruction, the form of instruction, and the form of compensation of the absences

Extent and forms are specified by guarantor’s regulation updated for every academic year.

Offered to foreign students

Not to offer

Course on BUT site

https://www.vut.cz/en/students/courses/detail/255974

Lecture

13 weeks, 3 hours/week, elective

Syllabus

1. - 8. Continuous and discrete random variables (vectors), probability function, density function, probability, cumulative distribution, independent random variables, characteristics of distribution, transformation of random variables, conditional distribution, conditional mean, special distributions.
9. - 13. Random sampling, statistic, point estimate of distribution parameters and their functions, desirable properties of an estimator, estimator of correlation matrix, confidence interval for distribution parameter, fundamentals for testing hypotheses, tests of hypotheses for distribution parameters - one-sample analysis, two-sample analysis, goodness-of-fit test.