SubjectsSubjects(version: 861)
Course, academic year 2019/2020
  
Statistical methods in linguistic research I - ALINV353B
Title: Statistické metody v lingvistickém výzkumu I
Guaranteed by: Institute of Linguistics (21-ULING)
Faculty: Faculty of Arts
Actual: from 2018
Semester: summer
Points: 0
E-Credits: 3
Examination process: summer s.:
Hours per week, examination: summer s.:1/1 Ex [hours/week]
Capacity: unknown / unknown (unknown)
Min. number of students: unlimited
State of the course: taught
Language: Czech
Teaching methods: full-time
Level:  
Is provided by: APH200013
Explanation: Další informace lze najít po kliknutí na kód předmětu, který výuku zajišťuje.
Note: course can be enrolled in outside the study plan
enabled for web enrollment
Guarantor: Ing. Tomáš Bořil, Ph.D.
Annotation -
Last update: Ing. Tomáš Bořil, Ph.D. (02.05.2018)
The course introduces philology students into the realm of statistics and their exploitation in fundamental
procedures of the descriptive and inductive analyses. The design of the course provides demonstrations of terms, relations and concepts on
speech material processing, which is familiar to students. The core of the coursework rests in the analysis of phonetic
studies, which present given statistical procedures, whether in a correct or incorrect manner.
Literature - Czech
Last update: Ing. Tomáš Bořil, Ph.D. (02.05.2018)

Volín, J. (2007): Statistické metody ve fonetickém výzkumu. Praha: Epocha.
Meloun, M. - Militký, J. (2001): Kompendium statistického zpracování dat. Praha: Academia. (vybrané části)
Robson, C. (1973): Experiment, design and statistics in psychology. Harmondsworth: Penguin Books Ltd.
Urdan, T. C. (2001): Statistics in plain English. London: Lawrence Erlbaum Associates.
Lamser, V. - Růžička, L. (1970): Základy statistiky pro sociology. Praha: Svoboda.

Syllabus -
Last update: Ing. Tomáš Bořil, Ph.D. (13.12.2018)

1. Introduction into statistical treatment of data.
2. Population and sample, types of variables, types of errors.
3. Descriptive data analysis; point and confidence interval estimation, plots.
4. Statistical distributions.
5. Normalization of phonetic data.
6. Hypotheses and p-value.
7. Chi-squared test.
8. Test of distributions.
9. Mean value tests.
10. Non-parametric tests.
11. Introduction do data processing in R.

 
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