Courses

The listing of a course description here does not guarantee a course’s being offered in a particular semester. Please refer to the published schedule of classes on the MyBU Student Portal for confirmation a class is actually being taught and for specific course meeting dates and times.

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  • GRS LX 732: Intermediate Semantics: The Grammatical Construction of Meaning
    Systematic development of a semantic theory of natural language, using the tools of model-theoretic semantics. In-depth study of the relation between meaning and grammar, and the relation between meaning and context. This course cannot be taken for credit in addition to the course entitled "Semantics II" that was previously numbered CAS LX 503.
  • GRS LX 733: Experimental Pragmatics
    Covers recent developments in the theory of pragmatics and related empirical findings obtained through a variety of experimental methods. Topics include scalar implicature and its relation to vagueness and imprecision, hyperbole, metaphor, irony, politeness, and the pragmatics of reference to objects in visual scenes. Effective Fall 2019, this course fulfills a single unit in each of the following BU Hub areas: Quantitative Reasoning II, Digital/Multimedia Expression, Creativity/Innovation.
    • Quantitative Reasoning II
    • Digital/Multimedia Expression
    • Creativity/Innovation
  • GRS LX 736: Advanced Topics in Semantics & Pragmatics
    Topic will vary. May be taken more than once for credit with different topics. Topic for Spring 2020: Degree semantics. The semantics of expressions of degree, including vague, gradable expressions like "tall", positive and comparative forms ("taller", "tallest"), and degree-denoting expressions like "six feet". Examination of multiple theoretical perspectives, and investigation of crosslinguistic variation through literature and new data collection.
  • GRS LX 738: Discourse Analysis: Theoretical and Methodological Approaches
    Review of current research literature on discourse analysis; students practice and apply current methods and techniques of discourse analysis.
  • GRS LX 753: Acquisition of Phonology
    Surveys current knowledge about how children acquire phonology during the first years of life. Topics include biological foundations; perceptual and vocal development; word learning; phonological universals; implicit and explicit learning mechanisms; formalist and functionalist models; and individual variation. This course cannot be taken for credit in addition to the course entitled "Phonological Development" that was previously numbered CAS LX 541.
  • GRS LX 754: Acquisition of Syntax
    Exploration of the character and course of acquisition of syntactic knowledge in both first and second language contexts. Covers methodological principles for conducting studies and analyzing data, and topics such as development of verb movement, binding theory, and tense. This course cannot be taken for credit in addition to the course with the same title that was previously numbered CAS LX 540.
  • GRS LX 790: Intermediate Topics in Linguistics
    Topics and pre-requisites vary by semester and section. May be repeated for credit as topics change. Topic for Spring 2022: Advanced Topics in Quantitative Methods. Provides students who already have a strong foundation in statistical analysis as well as basic skills in R with an overview of a range of advanced techniques and topics, including: Praat functions in R, Generalized Additive Models, multinomial regression, principal components analysis, frequentist vs. Bayesian statistics, cluster analysis, Poisson regression, discriminant analysis, power analysis, stepwise model selection, multilevel interactions, and dynamic visualization. Also explores strategies for streamlining workflow, increasing efficiency and reducing time from data import to communication of results.
  • GRS LX 795: Quantitative Methods in Linguistics
    Introduces students to quantitative approaches to linguistic data, including visualization, hypothesis testing, and data modeling. Students gain proficiency in R, an open-source statistical environment, and learn the logic behind statistical techniques, as well as practical skills for using them.
  • GRS LX 796: Computational Linguistics
    Introduction to computational techniques to explore linguistic models and test empirical claims. Serves as an introduction to concepts, algorithms, data structures, and tool libraries. Topics include tagging and classification, parsing models, meaning representation, corpus creation, information extraction. [Students who have already taken CAS LX 394/GRS LX 694 are not eligible to take this course.] Effective Spring 2020, this course fulfills a single unit in each of the following BU Hub areas: Quantitative Reasoning II, Research and Information Literacy.
    • Quantitative Reasoning II
    • Research and Information Literacy
  • GRS LX 801: Seminar in Linguistic Research
    Advanced graduate students working on their qualifying research papers or thesis present and discuss work in progress. The course is organized thematically based on students' research areas. Readings each week are determined on the basis of the research discussed. 2 cr. per semester.
  • GRS LX 802: Seminar in Linguistic Research
    Advanced graduate students working on their qualifying research papers or thesis present and discuss work in progress. The course is organized thematically based on students' research areas. Readings each week are determined on the basis of the research discussed. 2 cr. per semester.
  • GRS LX 865: Advanced Topics in Linguistics: Language Acquisition
    An in-depth exploration of current issues in language acquisition in relation to recent developments in linguistic theory, making use of computer-based tools and techniques in hands-on lab work. The focus is on experimental methodology and statistics, analysis of transcripts to uncover generalizations and test theoretical predictions, and use of other psycholinguistic tools. Topics to be covered will be drawn, in part, from the recent programs of the annual Boston University Conference on Language Development.
  • GRS MA 614: Statistical Methods 2
    Second course in statistics, embodying basic statistical methods used in educational and social science research. Reviews all basic concepts covered in a first statistics course and presents, in detail, more advanced topics such as analysis of variance, covariance, experimental design, correlation, regression, and selected nonparametric techniques. A problem-solving course; students carry out analysis of data taken from educational and other social science sources.
  • GRS MA 615: Data Science in R
    Introduction to R, the computer language written by and for statisticians. Emphasis on data exploration, statistical analysis, problem solving, reproducibility, and multimedia delivery. Intended for MSSP and other graduate students. Effective Fall 2020, this course fulfills a single unit in the following BU Hub area: Critical Thinking.
    • Critical Thinking
  • GRS MA 665: Introduction to Modeling and Data Analysis in Neuroscience
    An introduction to the basic techniques of quantifying neural data and developing mathematical models of neural activity. Major focus on computational methods using computer software and graphical methods for model analysis.
  • GRS MA 666: Advanced Modeling and Data Analysis in Neuroscience
    Advanced techniques to characterize neural voltage data and analyze mathematical models of neural activity. Major focus on computational methods using computer software and graphical methods for model analysis.
  • GRS MA 675: Statistics Practicum 1
    First of a two-semester sequence aimed at integrating the quantitative training and other skills required for doing statistics in practice. Emphasis on statistical consulting throughout, complemented by modules on speaking, writing, statistical software and programming, and data analysis.
  • GRS MA 676: Statistics Practicum 2
    Second of a two-semester sequence aimed at integrating the quantitative training and other skills required for doing statistics in practice. Emphasis on statistical consulting throughout, complemented by modules on speaking, writing, statistical software and programming, and data analysis.
  • GRS MA 677: Conceptual Foundations of Statistics
    Introduction to statistical methods relevant to research in the computational sciences. Core topics include probability theory, estimation theory, hypothesis testing, linear models, GLMs, and experimental design. Emphasis on developing a firm conceptual understanding of the statistical paradigm through data analyses.
  • GRS MA 678: Applied Statistical Modeling
    Application of multivariate data analytic techniques. Topics include ANOVA, multiple regression, logistic regression, generalized linear models, generalized linear mixed effect models, and Bayesian hierarchical models, experiment design, multiple comparison, and variable selection.

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