Mathematical Statistics I
Code  Completion  Credits  Range  Language 

D01MS1  ZK  2P  Czech 
 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:

Basic calculus.
 Syllabus of lectures:

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
 Syllabus of tutorials:
 Study Objective:

The goal is to get a basic knowledge of inferential statistics for postgraduate students who did not encounter the subject in their studies or who have some rudiment knowledge only.
 Study materials:

Jay Devore: Probability and Statistics for Engineering and the Sciences
 Note:
 Timetable for winter semester 2024/2025:

06:00–08:0008:00–10:0010:00–12:0012:00–14:0014:00–16:0016:00–18:0018:00–20:0020:00–22:0022:00–24:00
Mon Tue Wed Thu Fri  Timetable for summer semester 2024/2025:
 Timetable is not available yet
 The course is a part of the following study plans: