13M081MAST - Mathematical Statistics
Course specification | ||||
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Course title | Mathematical Statistics | |||
Acronym | 13M081MAST | |||
Study programme | Electrical Engineering and Computing | |||
Module | ||||
Type of study | master academic studies | |||
Lecturer (for classes) | ||||
Lecturer/Associate (for practice) | ||||
Lecturer/Associate (for OTC) | ||||
ESPB | 6.0 | Status | elective | |
Condition | Probability and statistics (3 or 6 credits), Mathematics 1 and Mathematics 2 | |||
The goal | Acquisition of knowledge about methods of mathematical statistics and their applications in problems of estimation,detection, classification and hypotheses testing in the framework of classical and Bayesian theory. | |||
The outcome | A student will be able to use methods of mathematical statistics in areas of parameters estimation, testing hypotheses using classical and Bayesian paradigm, based on samples from a distribution or a random process. | |||
Contents | ||||
Contents of lectures | Short review of probability theory. Likelihood function. Parameters estimation. Testing hypotheses. Monte Carlo methods. Conditional distributions and conditional expectation. Bayesian theory and its applications. Linear regression. Logistic and other kinds of regression in classification problems. High dimensional statistics. Robust methods with statistical depth functions. | |||
Contents of exercises | Study research work on a given topic | |||
Literature | ||||
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Number of hours per week during the semester/trimester/year | ||||
Lectures | Exercises | OTC | Study and Research | Other classes |
3 | 1 | |||
Methods of teaching | Classical lecturing supplemented with software demonstration. Presentations in groups or individually. | |||
Knowledge score (maximum points 100) | ||||
Pre obligations | Points | Final exam | Points | |
Activites during lectures | Test paper | 40 | ||
Practical lessons | 20 | Oral examination | ||
Projects | ||||
Colloquia | ||||
Seminars | 40 |