Quantitative Methods for Linguistic Data: An Introduction to Statistics using R

Dr. Kevin Tang, Summer 2024, Course Catalog

Course Description

Audience: Students who would like to do any English Linguistic courses with a quantitative component in the future. It can also be beneficial to those who are more literature-based but would like to do more digital humanities.

Description: It is as necessary to be numerate as it is to be literate, but students in the field of humanities are often not as numerate as they are literate. They will need to evaluate evidence that are based on probability-based models or statistical results in many of the courses that they take in university, as they consider the efficacy of vaccination and the severity of the pandemic, as they begin to vote in local and national elections, as they search for employment on the job market after graduating, and so on. With an increasingly digital world filled with big data, a command of statistical reasoning is more important than ever. In this course, we will learn numeracy through linguistics, specifically through phonetics and phonology by learning to analyse the sounds of languages quantitatively. How do we analyse the sounds of languages quantitatively? This course, Analysing the sounds of languages, covers the basics of quantitative methods using real data taken from the field of phonetics and phonology. We will provide a gentle introduction to the statistical program R (www.r-project.org) – a program that is used by data scientists in the tech. industry and academic researchers. The course will consist of a combination of lectures, and plenty of hands-on exercises. We introduce research questions, such as “Do Southerners in the US really talk more slowly?” or “Why do we expect scholarly words to be longer than familiar words?” as a framework for introducing the numerical concepts required to answer research questions such as these. In this course, statistical methods are introduced with a research question and a solid understanding of the data, which is why we use real data and questions that are relevant to anyone who commands a spoken language. A good amount of space is also devoted to illustrating how to formulate and answer a research question, and hypothesis development and testing.