LgBB04 Formal and experimental semantics II

Faculty of Arts
Spring 2022
Extent and Intensity
0/2/0. 5 credit(s). Type of Completion: z (credit).
Teacher(s)
doc. PhDr. Mojmír Dočekal, Ph.D. (lecturer)
Mgr. Lucia Vlášková (lecturer)
Guaranteed by
doc. PhDr. Mojmír Dočekal, Ph.D.
Department of Linguistics and Baltic Languages – Faculty of Arts
Supplier department: Department of Linguistics and Baltic Languages – Faculty of Arts
Timetable
Tue 14:00–15:40 G02
Prerequisites
successful completion of LgBA12: Formal and experimental semantics I
passive English on the level of understanding the textbooks
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 aim of the course is to teach students to actively link together the formal-theoretic and experimental-data-oriented parts of natural language meaning description and to gather and manage data for their own linguistic experiment and formal analysis. The course is an advanced continuation of LgBA12: Formal and experimental semantics I.
Learning outcomes
At the end of the semester, the student will be able to gather linguistic data from the corpus or from the respondents of a questionnaire/experiment and manage it in the programming language R, so that an exploratory data analysis can be performed and the data can be analysed by a formal statistical model. The student will then be able to properly communicate and visualise the achieved results.
Syllabus
  • active natural language data gathering methods: designing a questionnaire/experiment in IBEX farm/L-rex, working with corpus
  • data science in the programming language R in RStudio: basic operations in R, add-on packages, data import and export, data processing with the dplyr package
  • basic frequentist statistical methods (exploratory data analysis): mean, median, standard error, boxplot, whisker-plot
  • basics of formal statistical modelling (basic concepts of linear regression, t-test)
  • basics of data communication and visualisation: graphs in the ggplot2 package, report compilation, description of methodology and experimental results
Literature
    required literature
  • PENG, Roger. Exploratory data analysis with R. Lulu. com, 2012.
  • WICKHAM, Hadley and Garrett GROLEMUND. R for data science : import, tidy, transform, visualize, and model data. First edition. Sebastopol, CA: O'Reilly, 2016, xxv, 492. ISBN 9781491910399. info
  • LEVŠINA, Natal‘ja Gennad‘jevn. How to do linguistics with R : data exploration and statistical analysis. Amsterdam: John Benjamins Publishing Company, 2015, x, 443. ISBN 9789027212245. info
    recommended literature
  • BAAYEN, Rolf Harald. Analyzing linguistic data : a practical introduction to statistics using R. 1st print. Cambridge: Cambridge University Press, 2008, xiii, 353. ISBN 9780521882590. info
Teaching methods
lectures, seminars, self-study of the literature, homework during the semester
Assessment methods
class discussion, homework assignments, small projects
Language of instruction
Czech
Further Comments
Study Materials
The course is taught annually.
The course is also listed under the following terms Spring 2020, Spring 2021, Spring 2023, Spring 2024, Spring 2025.
  • Enrolment Statistics (Spring 2022, recent)
  • Permalink: https://is.muni.cz/course/phil/spring2022/LgBB04