**Course Objectives:** | Students will acquire basic knowledge of quantitative and
statistical approaches for gathering, analyzing, and visualizing
data from human language. Quantitative analysis is common in
linguistics, yet statistics courses typically do not cover the
data types or specialized techniques frequently used by
linguists. This course introduces basic statistical methods
and principles while assuming no mathematical background, and
students learn to apply these through hands-on implementation
in a software programming environment. Through homework
assignments with real data sets and in a final project, students
will develop the skills to apply quantitative methods in a
variety of subfields, including phonetics and phonology, syntax
and semantics, historical linguistics, sociolinguistics, and
psycholinguistics. The course will prepare students to carry
out thesis or dissertation research and to evaluate other
scholarsâ€™ quantitative approaches in linguistics. |

**Topical Outline:** | I. Introduction to Quantitative Methods
A. Quantitative approaches in linguistics: a brief survey
B. Why test a hypothesis?
C. Introduction to the statistical analysis environment
(software)
D. Graphic data exploration
E. Data types (continuous, categorical, nominal)
II. Descriptive analysis
A. Capturing central tendencies
B. Probability distributions; measures of dispersion
C. Normalizing data: how and why
D. How much is enough data?
III. Basic statistical methods (data from phonetics/phonology)
A. Testing for the mean; testing the difference between data
sets
B. Comparing continuous and categorical variables
C. Analysis of variance
D. Confidence intervals
IV. Analytical statistics (data from sociolinguistics and
syntax)
A. Linear regression
B. Mixed-effects models
C. Logistic regression
D. Interactions
E. Evaluating model fit
V. Clustering and classification (data from historical
linguistics)
A. Cladistics
B. Classification trees
C. Multidimensional scaling |