Mathematical Statistics I
Code  Completion  Credits  Range  Language 

D01MS1_EN  ZK  2P  English 
 Course guarantor:
 Daniela Jarušková
 Lecturer:
 Daniela Jarušková
 Tutor:
 Supervisor:
 Department of Mathematics
 Synopsis:

Random sample. Idea of statistical inference. Random variables and their distribution. Normal distribution. Central limit theorem. Multiple distribution. Independence. Correlation. Theory of estimation. – point and interval estimate. Hypotheses testing. Test statistic and statistical decision. Pvalue. Simple linear regression – parameters estimation, hypotheses testing, prediction intervals, regression diagnostic. Simulation independent realizations of random variables.
 Requirements:
 Syllabus of lectures:

1. Basic ideas of statistical inference.
2. Basic notions of probability calculus.
3. Discrete and continuous random variables and its distribution.
4. Multivariate distrbutions and estimation of their parameters.
5. Hypotheses testing (onesample and two sample problems), oneway analysis of variance. Goodness of fit tests.
6. Linear regression.
7. Generation of several types of random variables. Method of inverse transformation.
8. Application to assessing structure reliability
 Syllabus of tutorials:
 Study Objective:

Basic knowledge of mathematical statistics.
 Study materials:

Jay Devore: Probability and Statistics for Engineering and the Sciences
 Note:
 Timetable for winter semester 2024/2025:
 Timetable is not available yet
 Timetable for summer semester 2024/2025:
 Timetable is not available yet
 The course is a part of the following study plans: