MB104 Mathematics IV

Faculty of Informatics
Spring 2012
Extent and Intensity
2/2. 4 credit(s) (plus extra credits for completion). Type of Completion: zk (examination).
Teacher(s)
Mgr. Martin Panák, Ph.D. (lecturer)
prof. RNDr. Jan Slovák, DrSc. (lecturer)
Mgr. Marek Filakovský, Ph.D. (seminar tutor)
Mgr. David Kruml, Ph.D. (seminar tutor)
Mgr. Jan Meitner (seminar tutor)
Mgr. Jaroslav Šeděnka, Ph.D. (seminar tutor)
doc. Mgr. Josef Šilhan, Ph.D. (seminar tutor)
RNDr. Jan Vondra, Ph.D. (seminar tutor)
Mgr. Milan Werl, Ph.D. (seminar tutor)
Guaranteed by
prof. RNDr. Jan Slovák, DrSc.
Faculty of Informatics
Supplier department: Faculty of Science
Timetable
Mon 18:00–19:50 D1, Tue 8:00–9:50 D1
  • Timetable of Seminar Groups:
MB104/01: Wed 8:00–9:50 G124, M. Panák
MB104/02: Wed 10:00–11:50 G124, M. Panák
MB104/03: Thu 12:00–13:50 G125, D. Kruml
MB104/04: Thu 14:00–15:50 G125, D. Kruml
MB104/05: Thu 16:00–17:50 G125, D. Kruml
MB104/06: Wed 12:00–13:50 G124, J. Šilhan
MB104/07: Wed 14:00–15:50 G124, J. Šilhan
MB104/08: Fri 8:00–9:50 G125, J. Šeděnka
MB104/09: Fri 10:00–11:50 G125, J. Šeděnka
MB104/10: Fri 12:00–13:50 G125, J. Meitner
MB104/11: Fri 14:00–15:50 G125, J. Meitner
MB104/12: Wed 8:00–9:50 G125, M. Filakovský
MB104/13: Wed 10:00–11:50 G125, M. Filakovský
Prerequisites
Recommended: Calculus and linear algebra.
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 last part of the block Mathematics I-IV, for the brief content of the whole block see Mathematics I MB101. The main objectives can be summarized as follows: to understand basic concepts and tools of Algebra; to understand basic concepts and tools of Probability and Statistics.
Syllabus
  • Abstract mathematical structures: groups, algebras, lattices, rings, fields, divisibility, prime numbers decompositions, Euler theorem. Introduction to probability theory and statistics: Probality functins and their properties, conditional probability, Bayes formula, random quantities, mean value, median, quantil, variance, sequences of random quantities, law of large numbers, examples of discrete and continuous distributions, selected applications.
Literature
  • ROSICKÝ, J. Algebra, grupy a okruhy. 3rd ed. Brno: Masarykova univerzita, 2000, 140 pp. ISBN 80-210-2303-1. info
  • BUDÍKOVÁ, Marie, Štěpán MIKOLÁŠ and Pavel OSECKÝ. Popisná statistika. Třetí doplněné vydání. Brno: Masarykova univerzita, 1998, 48 stran. ISBN 8021018313. info
  • BUDÍKOVÁ, Marie, Štěpán MIKOLÁŠ and Pavel OSECKÝ. Teorie pravděpodobnosti a matematická statistika : sbírka příkladů [Budíková, 1996]. 1. vyd. Brno: Masarykova univerzita, 1996, 131 s. ISBN 80-210-1329-X. info
  • ZVÁRA, Karel and Josef ŠTĚPÁN. Pravděpodobnost a matematická statistika. Vyd. 3. Praha: Matfyzpress, 2002, 230 s. ISBN 80-85863-93-6. info
Bookmarks
https://is.muni.cz/ln/tag/FI:MB104!
Teaching methods
There are theoretical lectures, practical demonstration of the computational aspects, and standard tutorial accompanied by homework assessment.
Assessment methods
Two hours of lectures, two hours of presentations of typical problem solutions. Homeworks supported by tutorials. Written test exam.
Language of instruction
Czech
Further comments (probably available only in Czech)
Study Materials
The course is taught annually.
The course is also listed under the following terms Spring 2004, Spring 2005, Spring 2006, Spring 2007, Spring 2008, Spring 2009, Spring 2010, Spring 2011, Spring 2013, Spring 2014, Spring 2015, Spring 2016, Spring 2017, Spring 2018, Spring 2019, Spring 2020.
  • Enrolment Statistics (Spring 2012, recent)
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