FF:PLIN006 Element. mathemat. and stat.II - Course Information
PLIN006 Elementary mathematisc and statistics for Humanities, Pt. IIFaculty of Arts
- Extent and Intensity
- 2/0/0. 4 credit(s). Type of Completion: zk (examination).
- 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
- Thu 15:50–17:25 B2.24
- 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: 0/50, 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
- Czech Language and Literature (programme FF, B-MA)
- Czech Language with Orientation on Computational Linguistics (programme FF, B-FI)
- 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
- 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
- recommended literature
- ANDĚL, Jiří. Statistické metody. 2. přeprac. vyd. Praha: Matfyzpress, 1998. 274 s. ISBN 80-85863-27-8. info
- Teaching methods
- One-hour lecture and subsequent one-hour tutorial.
- Assessment methods
- Mid-term test (25 %) and final written exam (75 %).
- Language of instruction
- Further Comments
- Study Materials
The course is taught annually.