M7986 Statistical inferences I

Faculty of Science
Autumn 2016
Extent and Intensity
2/2. 4 credit(s) (fasci plus compl plus > 4). Type of Completion: zk (examination).
Teacher(s)
doc. PaedDr. RNDr. Stanislav Katina, Ph.D. (lecturer)
Mgr. Veronika Horská (seminar tutor)
Guaranteed by
doc. PaedDr. RNDr. Stanislav Katina, Ph.D.
Department of Mathematics and Statistics – Departments – Faculty of Science
Contact Person: doc. PaedDr. RNDr. Stanislav Katina, Ph.D.
Supplier department: Department of Mathematics and Statistics – Departments – Faculty of Science
Timetable
Mon 19. 9. to Sun 18. 12. Wed 10:00–11:50 M2,01021
  • Timetable of Seminar Groups:
M7986/01: Mon 19. 9. to Sun 18. 12. Tue 16:00–17:50 MP1,01014, V. Horská
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
Course objectives
The main goal of the course is to become familiar with some basic principles of testing statistical hypotheses base on Wald principle, likelihood and score principle connecting the statistical theory with MC simulations, implementation in R, geometry, and statistical graphics for continuous data; to understand and explain basic principles of parametric statistical inference for continuous data; to implement these techniques into R language; to be able to apply them to real data.
Syllabus
  • probabilistic and statistical model,
  • likelihood function and its maximisation,
  • basic principles of testing statistical hypotheses,
  • types of test statistics,
  • principles of MC simulations for testing statistical hypotheses,
  • design in one-, two-, and multi-sample experiments,
  • design in linear regression models for continuous data
Literature
    recommended literature
  • COX, D. R. Principles of statistical inference. 1st ed. Cambridge: Cambridge University Press. xv, 219. ISBN 0521685672. 2006. info
  • CASELLA, George and Roger L. BERGER. Statistical inference. 2nd ed. Pacific Grove, Calif.: Duxbury. xxviii, 66. ISBN 0534243126. 2002. info
Teaching methods
Lectures, practicals.
Assessment methods
Homework, oral exam.
Language of instruction
Czech
Follow-Up Courses
Further Comments
Study Materials
The course is taught annually.
Listed among pre-requisites of other courses
The course is also listed under the following terms Autumn 2013, Autumn 2014, Autumn 2015, autumn 2017, Autumn 2018, Autumn 2019, Autumn 2020, autumn 2021, Autumn 2022, Autumn 2023, Autumn 2024.
  • Enrolment Statistics (Autumn 2016, recent)
  • Permalink: https://is.muni.cz/course/sci/autumn2016/M7986