Ling 201: Research methods and statistics in linguistics (S2006, S2008, F2008)

This course introduced fundamentals of quantitative/statistical methodology in linguistics. We began by looking at a few basic notions such as variables and hypotheses. We then discussed the logic of quantitative studies using the null-hypothesis falsification approach and familiarized ourselves with how to set up factorial experiments and how data from experiments and corpora should be set up for subsequent statistical evaluation. Then, we were concerned with a variety of descriptive graphs and statistics for frequency data, averages, dispersions, and correlations. The largest part was concerned with a variety of statistical tests: distribution fitting tests, tests for independence, and tests for differences for frequencies, means, dispersions, and correlations. We ended with a small primer for the kind of multifactorial methods that are the subject of Ling 202. We used the open source software tool R .
(This course is partially based on my textbook Statistik für Sprachwissenschaftler (Statistics for linguists). Göttingen: Vandenhoeck und Ruprecht.)

Ling 202: Advanced research methods and statistics in linguistics
(to be developed in more detail and then taught the first time)

Multifactorial and multivariate statistical methods for analyzing observational and experimental data in linguistics: ANOVA; ANCOVA; regression techniques, generalized linear models for count and proportion data; hierarchical configural frequency analysis, cluster analysis; graphical methods for data exploration.

Ling 110/210: Computational linguistics (W2007)

This course was a (highly selective) introduction to the discipline known as Computational Linguistics. It featured (i) a brief general introduction to some main areas of research within this field(ii) an introduction to a programming language, R, with which we worked on linguistic data, and (iii) hands-on work in a computer lab on a variety of case studies from domains such as computational lexicography as well as word sense and synonym disambiguation, information retrieval, automatic text processing, and a few other things such as orthographic similarities of words and spell-checking, computational methods for authorship attribution, and others. Given the practical orientation of the course, this course was ideally suited for students who were thinking of practical applications and liked to acquire some first computational programming experience. Reading assignments were largely parts of Manning and Schütze's (2000¹) Foundations of Statistical Natural Language Processing as well as Jurafsky and Martin's (2000¹) Speech and Language Processing, supplemented with a variety of introductory chapters and research articles.

Ling 218: Corpus linguistics (S2007)

This course was an introduction to advanced corpus-linguistic research methods, which are applied to large data bases of language used in natural communicative settings to supplement more traditional ways of linguistic analysis in all linguistic sub-disciplines. It was broadly based on my textbook Quantitative corpus linguistics with R: a practical introduction to be published by Routledge, supplemented with a variety of research articles. The course had a bipartite structure. On the one hand, we read and discussed a variety of papers on different corpus-linguistic applications ranging from morphophonology, morphology, syntax, the syntax-lexis interface, and semantics to text linguistics / the study of literature. On the other hand, the course taught a programming language (i) to use two of the the three main corpus-linguistics methods to retrieve linguistically relevant data, and (ii) to perform elementary statistical analyses of these data. To that end, we looked at several different corpora and corpus formats. Thus, the course aimed at enabling you (i) to understand and replicate corpus-linguistic work, (ii) to pursue your own corpus-linguistic studies on a wide variety of data, and (iii) to acquire basic skills in programming and regular expressions, which are extremely useful both within and outside academia. See also here for the CorpLing with R Google group, which I moderate and which will host the companion website of my book.

Ling 219: Corpus construction
(to be developed in more detail and then taught the first time)

Design and construction of electronic corpora to represent spoken or written forms of language. Data collection from electronically available texts/transcripts, linguistic fieldwork, archives. Issues of sampling, balancedness, representativity, scale; formatting, markup, annotation, coding, tools; archival preservation, orthography, politics, ethics.

Ling 137/237: Introduction to first language acquisition (F2007, F2008)

This course was a selective introduction to the interdisciplinary enterprise of research on first language acquisition. It covered several different though interrelated topics: an introduction to 'the problem of language acquisition', overviews of different theoretical and methodological approaches towards first language acquisition, and introductions to aspects and processes of first language acquisition in different linguistic subdisciplines: phonology/morphology, semantics/lexicon, syntax.

Ling 252-A/B: Cognitive Linguistics (F2006/W2007)

This course dealt with the set of related approaches known as Cognitive Linguistics. It provided a brief general introduction to the assumptions governing or underlying most of the field, followed by a variety of case studies focusing on central notions of, and areas of research within, Cognitive Linguistics; these notions and areas of research include metaphor/metonymy, polysemy, Cognitive Grammar, (argument structure) constructions etc.