Syllabus: Analyzing linguistic data

Course Information

Instructor Contact Information

    • Katrin Erk

    • office hours: Monday 1-2pm, Tuesday 1-2pm, 3:30-4:30pm

    • office: CLA 4.734

    • email: katrin dot erk at mail dot utexas dot edu

TA Contact Information

    • Su Wang

    • office hours: Thursday 4-6pm

    • office: cubicle E5 in the linguistics department, CLA 4th floor, just outside Katrin Erk's office

    • email: shrekwang at utexas dot edu


Upper-division standing.

Syllabus and Text

This page serves as the syllabus for this course.


P. R. Hinton (2004): Statistics Explained: A Guide for Social Science Students. Psychology Press; 3rd edition.

R.H. Baayen (2008): Analyzing Linguistic Data: A Practical Introduction to Statistics Using R. Cambridge University Press.

Additional readings will be made available for download from the course website.


This course carries the Quantitative Reasoning flag. Quantitative Reasoning courses are designed to equip you with skills that are necessary for understanding the types of quantitative arguments you will regularly encounter in your adult and professional life. You should therefore expect a substantial portion of your grade to come from your use of quantitative skills to analyze real-world problems.

This course carries the Independent Inquiry flag. Independent Inquiry courses are designed to engage you in the process of inquiry over the course of a semester, providing you with the opportunity for independent investigation of a question, problem, or project related to your major. You should therefore expect a substantial portion of your grade to come from the independent investigation and presentation of your own work.

Exams and Assignments

Assignments will be updated on the assignments page. There will be 4 assignments. A tentative schedule for the entire semester is posted on the schedule page. Readings and exercises may change up one week in advance of their due dates.

This is an Independent Inquiry course in which students do a course project that uses statistical analyses on linguistic data. Requirements for the course project are: a short initial project description, an intermediate project report, a final project report, and a short in-class presentation. More details on the project requirements, as well as suggestions for project topics, are listed on the assignments page.

This course does not have a midterm or final exam.

Attendance is not required. However, given that we will do a lot of hands-on exercises in class, and homework and projects address the material covered in class, good attendance is essential for doing well in this class.

Philosophy and Goals

The aim of this course is to provide an introduction to statistics that is hands-on, making extensive use of the R statistics package in class, and that is driven by questions and data sets from linguistics, such as: Do women produce more words than men do? Does it matter whether you say "I gave Mary the book" or "I gave the book to Mary"? Can you tell, from the way a wine is described, whether it is expensive or cheap? The course draws heavily on the "breakfast experiments" of Language Log, a linguistics blog that sometimes has small statistical analyses for whatever language-related questions come up. This course will introduce fundamental concepts that will enable students to formulate quantitatively-oriented questions and answer them with appropriate visualization, modeling, and testing.

Content Overview

This course provides hands-on introduction to statistics for language, using the R programming language. We will study the following topics:

    • Descriptive statistics, and data exploration through visualization

    • Testing hypotheses: when is a result "significant", rather than a random blip in the data?

    • Regression modeling: both linear regression and logistic regression

A detailed schedule for the course, with topics for each lecture, is available at the schedule page, which forms part of the syllabus.

Course Requirements and Grading Policy

    • Assignments: 60% (4 assigments, 15% each)

    • Course project:

      • Initial project description: 5%

      • Intermediate project report: 10%

      • In-class presentation: 5%

      • Final report: 20%

By default, course projects should be done by teams of 2 students; however, projects done by 1 or 3 students are possible with prior approval of the instructor.

Final grades will use plus/minus grades.

Extension Policy

If you turn in your assignment late, expect points to be deducted. Extensions will be considered on a case-by-case basis. If you anticipate that you will need an extension for some assignment, let me know in advance.

By default, 5 points (out of 100) will be deducted for lateness, plus an additional 1 point for every 24-hour period beyond 2 that the assignment is late. For example, an assignment due at 2pm on Tuesday will have 5 points deducted if it is turned in late but before 2pm on Thursday. It will have 6 points deducted if it is turned in by 2pm Friday, etc.

Even if you are late for some assignment, you should definitely turn it in, and you will get some credit for your work, even though some points may be deducted. But it is crucial for your learning progress that you do all the coursework.

Academic Dishonesty Policy

You are encouraged to discuss assignments with classmates. But all written work must be your own. Students caught cheating will automatically fail the course. If in doubt, ask the instructor.

Notice about students with disabilities

The University of Texas at Austin provides upon request appropriate academic accommodations for qualified students with disabilities. Please contact the Division of Diversity and Community Engagement, Services for Students with Disabilities, 512-471-6259,

Notice about missed work due to religious holy days

By UT Austin policy, you must notify me of your pending absence at least fourteen days prior to the date of observance of a religious holy day. If you must miss a class, an examination, a work assignment, or a project in order to observe a religious holy day, you will be given an opportunity to complete the missed work within a reasonable time after the absence.

Emergency Evacuation Policy

    • Occupants of buildings on The University of Texas at Austin campus are required to evacuate buildings when a fire alarm is activated. Alarm activation or announcement requires exiting and assembling outside.

    • Familiarize yourself with all exit doors of each classroom and building you may occupy. Remember that the nearest exit door may not be the one you used when ent ering the building.

    • Students requiring assistance in evacuation shall inform their instructor in writing during the first week of class.

    • In the event of an evacuation, follow the instruction of faculty or class instructors.

    • Do not re-enter a building unless given instructions by the following: Austin Fire Department, The University of Texas at Austin Police Department, or Fire Prevention Services office.

    • Link to information regarding emergency evacuation routes and emergency procedures can be found at:

Behavior Concerns Advice Line (BCAL)

If you are worried about someone who is acting differently, you may use the Behavior Concerns Advice Line to discuss by phone your concerns about another individual's behavior. This service is provided through a partnership among the Office of the Dean of Students, the Counseling and Mental Health Center (CMHC), the Employee Assistance Program (EAP), and The University of Texas Police Department (UTPD). Call 512-232-5050 or visit