MV011 Statistics I

Faculty of Informatics
Spring 2007
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. Ivo Moll, CSc. (lecturer)
Mgr. Tomáš Lerch (seminar tutor)
Mgr. Jaroslava Sidorová (seminar tutor)
Mgr. Jiří Tesař (seminar tutor)
Guaranteed by
prof. RNDr. Ivanka Horová, CSc.
Faculty of Informatics
Timetable
Tue 8:00–9:50 A107
  • Timetable of Seminar Groups:
MV011/01: Tue 10:00–11:50 B003, I. Moll
MV011/02: Wed 8:00–9:50 B003, J. Sidorová
MV011/03: Tue 18:00–19:50 B003, T. Lerch
MV011/04: Mon 18:00–19:50 B003, J. Tesař
Prerequisites (in Czech)
! M011 Statistics I
Předpokládá se znalost diferenciálního a integrálního počtu jedné a více proměnných a znalost lineární algebry.
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 17 fields of study the course is directly associated with, display
Course objectives
Data files, empirical characteristics and graphs, numerical characteristics.
Probability space, property of probability, conditional probability, stochastic independence of events.
Random variables and vectors, functional and numerical characteristics.
Weak law of large number and central limit theorem.
Syllabus
  • Data files, empirical characteristics and graphs, numerical characteristics.
  • Probability space, property of probability, conditional probability, Bayes' theorem, stochastic independence of events.
  • Construction of classical probability and of probability distributions using probability function and density.
  • Random variables and vectors. Probability distribution and distribution function.
  • Discrete and continuous random variables and vectors. Typical distribution laws. Simultaneous and marginal distributions.
  • Stochastic independence of random variables and vectors. The sequence of independent trials.
  • Quantiles, expectation, variance, covariance, correlation coeficient and their properties.
  • Weak law of large number and central limit theorem.
Literature
  • BUDÍKOVÁ, Marie, Štěpán MIKOLÁŠ and Pavel OSECKÝ. Popisná statistika (Descriptive Statistics). 3., doplněné vyd. Brno: Masarykova univerzita, 1998, 52 pp. ISBN 80-210-1831-3. info
  • BUDÍKOVÁ, Marie, Štěpán MIKOLÁŠ and Pavel OSECKÝ. Teorie pravděpodobnosti a matematická statistika : sbírka příkladů. 2. vyd. Brno: Masarykova univerzita v Brně, 1998, viii, 116. ISBN 8021018321. info
  • OSECKÝ, Pavel. Statistické vzorce a věty. 1. vyd. Brno: Masarykova univerzita, 1998, [29] list. ISBN 8021017589. info
  • ANDĚL, Jiří. Statistické metody. 1. vyd. Praha: Matfyzpress, 1993, 246 s. info
Assessment methods (in Czech)
Výuka probíhá každý týden v rozsahu 2 hodiny přednášek, 2 hodiny cvičení. Nutnou podmínkou absolvování předmětu je vypracování seminárního úkolu. V průběhu semestru bude písemná kontrolní prověrka. Zkouška je písemná, obsahuje část testovou a část s příklady.
Language of instruction
Czech
Follow-Up Courses
Further Comments
The course is taught annually.
The course is also listed under the following terms Spring 2003, Spring 2004, Spring 2005, Spring 2006, Spring 2008, Spring 2009, Spring 2010, Spring 2011, Spring 2012, Spring 2013, Spring 2014, Spring 2015, Spring 2016, Spring 2017, Spring 2018, Spring 2019, Spring 2020.
  • Enrolment Statistics (Spring 2007, recent)
  • Permalink: https://is.muni.cz/course/fi/spring2007/MV011