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. P-value. Simple linear regression – parameters estimation, hypotheses testing, prediction intervals, regression diagnostic. Simulation independent realizations of random variables.
- Requirements:
- Syllabus of lectures:
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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 (one-sample and two sample problems), one-way 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:
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Basic knowledge of mathematical statistics.
- Study materials:
-
Jay Devore: Probability and Statistics for Engineering and the Sciences
- Note:
- Time-table for winter semester 2024/2025:
- Time-table is not available yet
- Time-table for summer semester 2024/2025:
- Time-table is not available yet
- The course is a part of the following study plans: