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LINGUIST 2DD3 Stats For Language Research

Academic Year: Winter 2018

Term: Winter

Day/Evening: D

Instructor: Dr. Victor Kuperman


Office: Togo Salmon Hall 510

Phone: 905-525-9140 x 20384


Office Hours: Fri 2:30-3:30

Course Objectives:


This is an introductory course to statistical methods custom-tailored to the needs of language researchers. No prior background in statistics or mathematics (beyond basic algebra) is required, but the course may move quickly through a number of analytical techniques.

By the end of the course, students should be able to identify analytical methods appropriate for a given numeric problem and perform basic statistical analyses of the data. They will develop basic programming and data processing skills in a statistical software environment. They should value data-driven scientific approaches to questions that are at the core of humanities as a discipline. They will develop research and analytical skills directly transferrable to, and in high demand in, a variety of a academic and professional settings.

Textbooks, Materials & Fees:

              - There are two textbooks for this course. Butler, Christopher S. (1985). Statistics in Linguistics. Oxford, Basil Blackwell.  While this is an old book, it is an excellent introduction to basic concepts. You can download it free from the course webpage on Avenue.

              - A second book will be used to introduce R. Verzani, John. (2014). Using R for introductory statistics. Boca Raton: Chapman & Hall. Edition 2. Available as an e-book from McMaster library and as a hard copy at the bookstore.

              - Other readings will be made available through links on Avenue. Note that some of those links will only work from campus computers. E-journals can sometimes be accessed from off-campus locations using your McMaster ID and password.

              - The assigned readings must be read before class.

Method of Assessment:


This is a hands-on course administered in a computer lab that consists of a combination of lectures and tutorials. Students learn by attending, and participating in lectures and lab sessions, and by completing the assigned readings and assignments.


              In-class work                                  10%

              Short HW assignments                 20%

              Long HW assignments                  15%

              Midterm test                                  25%

              Final exam                                      30%

n-Class Work

              - We will usually have in-class assignments, which you will upload to Avenue at the end of the class.

              - Save your work in R as a text file. On Avenue, go to In-Class Assignments and upload your file to the link of today’s date.

              - These assignments will be graded on a pass/fail basis.

              - This work cannot be made up at a later time: the link will disappear an hour after the class is over.


Short Homework Assignments

              - There will be a weekly assignment (under “Homework Assignments”) for most weeks.

              - The short assignment will be available on Avenue on Mondays after class.

              - You will submit your weekly short homework assignment on Avenue by the beginning of the Monday class the week after. This work cannot be made up at a later time.


Long Homework Assignments

              - There will be 2 to 3 long homework assignments that build on the knowledge gained over several classes.

              - Due dates are to be announced.


Midterm Test

              - The midterm will take place during class (date TBA).

              - If you miss a test, you must contact the instructor by email within 24 hours. You will either write a makeup test or have the weight of the test transferred to the other test, depending on the circumstances.


Final Exam

              - There will be a cumulative final exam during the exam period. It will be administered in the computer lab. The date is TBA.

Policy on Missed Work, Extensions, and Late Penalties:

Due Date Policies

Assignments submitted within 48 hours of the due date are subject to a 25% penalty. Assignments submitted 2 to 7 days after the due date are subject to a 50% penalty. Assignments are not accepted more than 7 days after the due date.


Exceptions to due dates and exam dates can be made only with medical documentation.  Submit your medical documentation to the office of the Dean of your Faculty using the appropriate forms. Please note that the instructor will NOT adjudicate whether the absence was justified or not. Note that the University's policy on medical notes is subject to change at any time in the event of a health emergency on campus.


Other Course PoliciesThe midterm and the final exam are open-book exams: the use of all class materials is permitted. Either oral or electronic communication with other individuals is strictly prohibited and will be penalized.

Please Note the Following Policies and Statements:

Academic Integrity

You are expected to exhibit honesty and use ethical behaviour in all aspects of the learning process. Academic credentials you earn are rooted in principles of honesty and academic integrity. It is your responsibility to understand what constitutes academic dishonesty.

Academic dishonesty is to knowingly act or fail to act in a way that results or could result in unearned academic credit or advantage. This behaviour can result in serious consequences, e.g. the grade of zero on an assignment, loss of credit with a notation on the transcript (notation reads: "Grade of F assigned for academic dishonesty"), and/or suspension or expulsion from the university. For information on the various types of academic dishonesty please refer to the Academic Integrity Policy, located at

The following illustrates only three forms of academic dishonesty:

  • plagiarism, e.g. the submission of work that is not one’s own or for which other credit has been obtained.
  • improper collaboration in group work.
  • copying or using unauthorized aids in tests and examinations.

Authenticity / Plagiarism Detection

Some courses may use a web-based service ( to reveal authenticity and ownership of student submitted work. For courses using such software, students will be expected to submit their work electronically either directly to or via Avenue to Learn (A2L) plagiarism detection (a service supported by so it can be checked for academic dishonesty.

Students who do not wish to submit their work through A2L and/or must still submit an electronic and/or hardcopy to the instructor. No penalty will be assigned to a student who does not submit work to or A2L. All submitted work is subject to normal verification that standards of academic integrity have been upheld (e.g., on-line search, other software, etc.). To see the Policy, please go to

Courses with an On-Line Element

Some courses use on-line elements (e.g. e-mail, Avenue to Learn (A2L), LearnLink, web pages, capa, Moodle, ThinkingCap, etc.). Students should be aware that, when they access the electronic components of a course using these elements, private information such as first and last names, user names for the McMaster e-mail accounts, and program affiliation may become apparent to all other students in the same course. The available information is dependent on the technology used. Continuation in a course that uses on-line elements will be deemed consent to this disclosure. If you have any questions or concerns about such disclosure please discuss this with the course instructor.

Online Proctoring

Some courses may use online proctoring software for tests and exams. This software may require students to turn on their video camera, present identification, monitor and record their computer activities, and/or lockdown their browser during tests or exams. This software may be required to be installed before the exam begins.

Conduct Expectations

As a McMaster student, you have the right to experience, and the responsibility to demonstrate, respectful and dignified interactions within all of our living, learning and working communities. These expectations are described in the Code of Student Rights & Responsibilities (the "Code"). All students share the responsibility of maintaining a positive environment for the academic and personal growth of all McMaster community members, whether in person or online.

It is essential that students be mindful of their interactions online, as the Code remains in effect in virtual learning environments. The Code applies to any interactions that adversely affect, disrupt, or interfere with reasonable participation in University activities. Student disruptions or behaviours that interfere with university functions on online platforms (e.g. use of Avenue 2 Learn, WebEx or Zoom for delivery), will be taken very seriously and will be investigated. Outcomes may include restriction or removal of the involved students' access to these platforms.

Academic Accommodation of Students with Disabilities

Students with disabilities who require academic accommodation must contact Student Accessibility Services (SAS) at 905-525-9140 ext. 28652 or e-mail to make arrangements with a Program Coordinator. For further information, consult McMaster University’s Academic Accommodation of Students with Disabilities policy.

Email correspondence policy

It is the policy of the Faculty of Humanities that all email communication sent from students to instructors (including TAs), and from students to staff, must originate from each student’s own McMaster University email account. This policy protects confidentiality and confirms the identity of the student.  Instructors will delete emails that do not originate from a McMaster email account.

Modification of course outlines

The University reserves the right to change dates and/or deadlines etc. for any or all courses in the case of an emergency situation or labour disruption or civil unrest/disobedience, etc. If a modification becomes necessary, reasonable notice and communication with the students will be given with an explanation and the opportunity to comment on changes. Any significant changes should be made in consultation with the Department Chair.

Request for Relief for Missed Academic Term Work
McMaster Student Absence Form (MSAF)

In the event of an absence for medical or other reasons, students should review and follow the Academic Regulation in the Undergraduate Calendar "Requests for Relief for Missed Academic Term Work".

Academic Accommodation for Religious, Indigenous and Spiritual Observances (RISO)

Students requiring academic accommodation based on religious, indigenous or spiritual observances should follow the procedures set out in the RISO policy. Students should submit their request to their Faculty Office normally within 10 working days of the beginning of term in which they anticipate a need for accommodation or to the Registrar's Office prior to their examinations. Students should also contact their instructors as soon as possible to make alternative arrangements for classes, assignments, and tests.

Copyright and Recording

Students are advised that lectures, demonstrations, performances, and any other course material provided by an instructor include copyright protected works. The Copyright Act and copyright law protect every original literary, dramatic, musical and artistic work, including lectures by University instructors.

The recording of lectures, tutorials, or other methods of instruction may occur during a course. Recording may be done by either the instructor for the purpose of authorized distribution, or by a student for the purpose of personal study. Students should be aware that their voice and/or image may be recorded by others during the class. Please speak with the instructor if this is a concern for you.

Extreme Circumstances

The University reserves the right to change the dates and deadlines for any or all courses in extreme circumstances (e.g., severe weather, labour disruptions, etc.). Changes will be communicated through regular McMaster communication channels, such as McMaster Daily News, A2L and/or McMaster email.

Topics and Readings:





Read before class




B1 (read for Wed class)


Univariate data

Central tendency, dispersion


B2, B3

V1, V2.1, V2.2


Sampling distributions, sample statistics and population parameters (confidence intervals, standard errors)


B4, B5

V5, V7


Hypothesis Testing


B6, V8



Bivariate and multivariate statistics & correlation


V3, V4


Goodness of fit, Chi square

HW1 assigned

B9, V9


Reading week

HW1 due







Parametric tests I

HW2 assigned



Parametric tests II

HW2 due



Non parametric tests

HW3 assigned




HW3 due

B10, V11




B11, V10