MA012 Statistics II

Faculty of Informatics
Autumn 2014
Extent and Intensity
2/2. 4 credit(s) (plus extra credits for completion). Recommended Type of Completion: zk (examination). Other types of completion: k (colloquium), z (credit).
Teacher(s)
RNDr. Marie Budíková, Dr. (lecturer)
Mgr. Eva Janoušková, Ph.D. (seminar tutor)
Mgr. Petra Ráboňová, Ph.D. (seminar tutor)
Guaranteed by
prof. RNDr. Ivanka Horová, CSc.
Faculty of Informatics
Supplier department: Faculty of Science
Timetable
Thu 12:00–13:50 A217
  • Timetable of Seminar Groups:
MA012/T01: Mon 15. 9. to Fri 19. 12. Mon 13:00–14:35 Učebna S4 (35a), Thu 18. 9. to Fri 19. 12. Thu 9:40–11:15 Učebna S6 (20), E. Janoušková, Nepřihlašuje se. Určeno pro studenty se zdravotním postižením.
MA012/01: Wed 8:00–9:50 B204, P. Ráboňová
MA012/02: Wed 10:00–11:50 B204, P. Ráboňová
Prerequisites
Statistics II assume knowledges of fundamental statistical concepts in range Statistics I.
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
there are 22 fields of study the course is directly associated with, display
Course objectives
Random samples, point and interval estimators of parametrs and parametrical functions, statistical hypotheses testing, correlation and regression analysis. The main goals of this course are: to introduce the principles of statistical induction; to explain the fundamentals of selected statistical tests including computer implementation; the definition of preconditions of these tests; to learn to interpret the test results.
Syllabus
  • Basic ideas of inferential statistics. Samples and sample characteristics.
  • Properties of the point estimators.
  • Properties of the normal and asymptotically normal samples.
  • Interval estimators.
  • Statistical hypotheses testing.
  • Analysis of correlation.
  • Multidimensional linear regression.
  • Statistical computation pacquets.
Literature
    required literature
  • BUDÍKOVÁ, Marie, Štěpán MIKOLÁŠ and Tomáš LERCH. Základní statistické metody. Vydání první. Brno: Masarykova univerzita, 2005. 180 pp. ISBN 80-210-3886. info
    not specified
  • BUDÍKOVÁ, Marie, Štěpán MIKOLÁŠ and Pavel OSECKÝ. Teorie pravděpodobnosti a matematická statistika. Sbírka příkladů. (Probability Theory and Mathematical Statistics. Collection of Tasks.). 2.,přepracované vyd. Brno: Masarykova univerzita Brno, 1998. 127 pp. ISBN 80-210-1832-1. info
  • ANDĚL, Jiří. Statistické metody. 1. vyd. Praha: Matfyzpress, 1993. 246 s. info
  • OSECKÝ, Pavel. Statistické vzorce a věty. 1. vyd. Brno: Masarykova univerzita, 1998. [29] list. ISBN 8021017589. info
Teaching methods
Lectures, Exercises
Assessment methods
The weekly class schedule consists of 2 hour lecture and 2 hours of class exercises. A necessary condition for the successful completion of the course is pass a test on the computer. The examination is written, consisting of test part and exercises part.
Language of instruction
Czech
Further Comments
Study Materials
The course is taught annually.
The course is also listed under the following terms Autumn 2002, Autumn 2003, Autumn 2004, Autumn 2005, Autumn 2006, Autumn 2007, Autumn 2008, Autumn 2009, Autumn 2010, Autumn 2011, Autumn 2012, Autumn 2013, Autumn 2015, Autumn 2016, Autumn 2017, Autumn 2018, Autumn 2019, Autumn 2020, Autumn 2021, Autumn 2022, Autumn 2023.
  • Enrolment Statistics (Autumn 2014, recent)
  • Permalink: https://is.muni.cz/course/fi/autumn2014/MA012