Ling 104: Statistical methods in linguistics (20152017: F; 2022: W) 

This course was a handson introduction to fundamentals of quantitative/statistical methodology in linguistics. It was based on the third edition (2021) of my textbook Statistics for linguistics with R: […], which also forms the basis for Ling 105. We began by looking at a few basic notions such as variables and hypotheses. We then discussed the logic of quantitative studies using the nullhypothesis falsification approach 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 elementary aspects of correlation/regression. We ended with a small primer for the kind of multifactorial regression and treebased methods that are the subject of Ling 105. We used the open source software tool R . 
Ling 105: Predictive modeling in linguistics (2022: S)


This course was a selective introduction to predictive modeling applications in linguistics. We started with a onesession intro of predictive modeling with an emphasis on regression modeling, which surveyed model formulation, model selection, multifactoriality, and validation. Then, we worked our way through a variety of regression modeling applications: linear regression, binary logistic regression, multinomial, and ordinal regression models. Then, one session was concerned with model diagnostics and model validation. Finally, there were two sessions on treebased approaches: classification and regression trees as well as random forests. Like its prerequisite course Ling 104, this course used the open source programming language R , and was based on the third edition (2021) of my book Statistics for Linguistics with R: […], which comes with sample data, exercises, answer keys, etc., plus additional materials.

Ling 110/210: Computational linguistics (2007: W; 2010: S)


This course was a (highly selective) introduction to a 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 the programming language R based on my book Quantitative Corpus Linguistics with R: […], with which we worked on linguistic data, and (iii) handson 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 spellchecking, 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 wanted to acquire some first computational programming experience (prior experience with R was not necessary, but a largerthanaverage computer savviness was recommended). Reading assignments included parts of Manning and Schütze's (2000) Foundations of Statistical Natural Language Processing as well as Jurafsky and Martin's (2000) Speech and Language Processing, supplemented with a variety of introductory chapters and research articles.

Ling 113: Introduction to semantics (2008: W; 2011: F)


This course was an introduction to the linguistic subdiscipline of semantics. After a very brief general introduction to the course and some main semantic concepts, we looked at definitional approaches to word meaning, lexical relations, and cognitive/psycholinguistic approaches to meaning. We then covered sentence meaning, utterances, and propositions as well as logical relations between sentences. Finally, we considered selected aspects of the acquisition of word meaning by children and explored a few central notions of pragmatics (or utterance meaning).

Ling 120: Corpus linguistics (2008, 2014, 2018, 2019, 2021: S; 2010, 2023: W)


This course was an introduction to computerized 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 subdisciplines. In the first part of this particular class, we began with a theoretical introduction: what is a corpus / what are corpora, what kinds of corpora are there and how are they created/compiled, and why would one use corpora in the first place? In the second part, we familiarized ourselves with the open source programming language and environment R . In the third part, we read a variety of published corpuslinguistic studies as well as replicate, modify, or extend them. The topics covered include syntax (patterns and alternations), lexis/semantics (key words in different cultures and near synonymy), psycholinguistics (disfluencies), and others. Note: This course was based on the second edition (2016) of my textbook Quantitative corpus linguistics with R: […]. New York: Routledge, Taylor & Francis Group, which you will need to have: it will teach you most fundamentals of R programming for text analysis (and can therefore be useful way beyond this course) and contains all readings for the first half of the course as well as additional answer keys and exercises for parts of the second half.

Ling 127 / Psy 127: Psychology of language (2006: F)


This course was an introduction to psycholinguistics concerned with various aspects of language comprehension, production, and acquisition. It was broadly based on Carroll's (2004) Psychology of Language, but also incorporated a variety of additional information/materials.

Ling 137(/237): Introduction to first language acquisition (2007, 2008: F; 2010, 2018: W)


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 194: Group studies in linguistics (2006: W)


This course was an introduction to corpus linguistics, involving simple computerized research methods to large data bases of language used in natural communicative settings.
