PLIN006 Elementary mathematisc and statistics for Humanities, Pt. II

Faculty of Arts
Spring 2018
Extent and Intensity
2/0/0. 4 credit(s). Type of Completion: zk (examination).
Teacher(s)
RNDr. Vojtěch Kovář, Ph.D. (lecturer)
Guaranteed by
doc. PhDr. Zdeňka Hladká, Dr.
Department of Czech Language - Faculty of Arts
Contact Person: Jaroslava Vybíralová
Supplier department: Department of Czech Language - Faculty of Arts
Timetable
Wed 14:10–15:45 K33
Prerequisites
The subject will be using notions and procedures introduced in PLIN004 Elementary mathematisc and statistics for Humanities, Pt. I. However, its completion is not mandatory if the student is able to study them themselves.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
The capacity limit for the course is 50 student(s).
Current registration and enrolment status: enrolled: 4/50, only registered: 0/50, only registered with preference (fields directly associated with the programme): 0/50
fields of study / plans the course is directly associated with
Course objectives
Students will get acquainted with more substantial information from the field of mathematics and statistics that can be used during their studies. This seminar follows the course called “Essentials of mathematics and statistics for humanities, Pt. I” and is focused especially on probability and statistics, random entities, graphs and graph algorithms.
Learning outcomes
After completing the course, the student will be able to:
- work with graphs, explain selected graph algorithms - use basic statistical methods, including hypotheses testing - explain the relationship between statistics and probability - explain the principle of selected statistical methods in the field of computational linguistics
Syllabus
  • Main areas: 1) Graphs: graph, sub-graphs, isomorphism, degrees of peaks, continual components of graphs, net. 2) Graph algorithms: distances in graphs, searching for the shortest route, acylic graphs trees and their properties. 3) Combinatorics and selections of elements: independent selections, combinatorial numbers, permutations and factorial. Combinatorial probability: throwing the dice and shuffling cards, finite space of probability. 4) Descriptive statistics: statistic file, average, medians, diffusion, correlation. 5) Space for probability, qualities of probability, conditioned probability, Bayes’ formula, stochastic independence of phenomena. 6) Random entities, random vectors and their distributional functions. 7) Selected applications of statistics in computational linguistics
Literature
    recommended literature
  • ANDĚL, Jiří. Statistické metody. 2. přeprac. vyd. Praha: Matfyzpress, 1998. 274 s. ISBN 80-85863-27-8. info
  • http://www.fi.muni.cz/~hlineny/Vyuka/GT/Grafy-text07.pdf
Teaching methods
One-hour lecture and subsequent one-hour tutorial.
Assessment methods
Mid-term test (25 %) and final written exam (75 %).
Language of instruction
Czech
Further Comments
Study Materials
The course is taught annually.
The course is also listed under the following terms Spring 2011, Spring 2012, Spring 2013, Spring 2014, Spring 2015, Spring 2016, Spring 2017, Spring 2019, Spring 2020.
  • Enrolment Statistics (Spring 2018, recent)
  • Permalink: https://is.muni.cz/course/phil/spring2018/PLIN006