PřF:M5120 Linear Models in Statistics I - Course Information
M5120 Linear Models in Statistics I
Faculty of ScienceAutumn 2013
- Extent and Intensity
- 2/1/0. 3 credit(s) (příf plus uk k 1 zk 2 plus 1 > 4). Type of Completion: zk (examination).
- Teacher(s)
- RNDr. Marie Forbelská, Ph.D. (lecturer)
Mgr. Ondřej Pokora, Ph.D. (seminar tutor) - Guaranteed by
- prof. RNDr. Ivanka Horová, CSc.
Department of Mathematics and Statistics – Departments – Faculty of Science
Supplier department: Department of Mathematics and Statistics – Departments – Faculty of Science - Timetable
- Mon 8:00–9:50 M1,01017
- Timetable of Seminar Groups:
M5120/02: Fri 11:00–11:50 MP1,01014, O. Pokora
M5120/03: Fri 10:00–10:50 MP1,01014, O. Pokora - Prerequisites
- KREDITY_MIN(30) && ( M4122 Probability and Statistics II || M6130 Computational statistics )
Základy teorie pravděpodobnosti a matematické statistiky, teorie odhadu a testování statistických hypotéz. Práce s počítačem: uživatelská znalost programového prostředí R. - Course Enrolment Limitations
- The course is also offered to the students of the fields other than those the course is directly associated with.
- fields of study / plans the course is directly associated with
- Mathematics - Economics (programme PřF, M-AM)
- Mathematics (programme PřF, N-MA, specialization Applied Mathematics)
- Course objectives
- At the end of the course the student should be able to understand and use basic methods of statistical regression analysis, which are explained by a matrix approach. Programming environment R is used in the exercises for the basic statistical analysis.
- Syllabus
- Basic knowledge of matrix algebra: positive definite matrix, idempotent matrix, generalized inverse of matrix
- Normal distribution: n-dimensional normal distribution and its properties, distribution of quadratic forms
- Regression: regular linear regression model, least squares method and estimators of model's parameters, properties of the estimators, testing hypotheses about the parameters and confidence intervals for parameters, basic of regression diagnostics
- Correlation: correlation coefficient, multiple correlation coefficient, partial correlation coefficient, their sampling opposites and tests for them
- Literature
- ANDĚL, Jiří. Matematická statistika. Vyd. 2. Praha: SNTL - nakladatelství technické literatury, Alfa, vydavatelstvo technickej a ekonomickej literatury, 1985, 346 s. URL info
- RAO, C. Radhakrishna. Lineární metody statistické indukce a jejich aplikace. Translated by Josef Machek. 1. vyd. Praha: Academia, 1978, 666 s. URL info
- Teaching methods
- Lectures: theoretical explanation with practical examples Exercises: solving problems for understanding of basic concepts and theorems, contains also more complex problems.
- Assessment methods
- Conditions: active participation in seminars, individual homeworks, 1 test on computer. Evaluation: written (weight 50 %) and oral (weight 50 %) final examination, at least 50 % of points is needed to pass.
- Language of instruction
- Czech
- Further Comments
- Study Materials
The course is taught annually. - Listed among pre-requisites of other courses
- Enrolment Statistics (Autumn 2013, recent)
- Permalink: https://is.muni.cz/course/sci/autumn2013/M5120