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Master Program Linguistics

Quantitative Methods

Quantitative Methods (06SM271-516)

General description This course introduces the basic concepts of statistical analysis as used in modern linguistics, covering data description and visualization as well as basic techniques of machine learning and modelling. The course also introduces the basic concepts of frequentist vs Bayesian approaches and the use of simulations and baseline models.
ECTS 6
Learning outcome

Students are familiar with the basic concepts and methods of statistical analyses of linguistic data and are able to perform such analyses themselves
Language of instruction English
Prerequisites

Notice: the following knowledge of high school mathematics is required and has to be solid:

  • Concept of spaces / number systems (e.g., natural, rational and real numbers);
  • Basic Functions: Linear, polynomial, exponential, logarithmic function;
  • Differential Calculus: Extreme values, derivatives, integrals;
  • Linear Algebra: Vectors, vector spaces, linear transformations, matrices, dot (scalar) product;
  • Probability Theory: Random variables, probability distributions (uniform, binomial, normal, exponential), joint and marginal distributions.
Assessment

Portfolio (80% written exam and 20% written exercises). All elements of this portfolio must be completed. If an element is not completed, the module is considered as «failed».
Repeatability Repeatable once, book again
Duration / Offered in 1 semester / every fall semester
Courses within this module:
  • Quantitative Methods - Lecture (06VU271-516a)
  • Quantitative Methods - Tutorial (06TT271-516a)