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The Chinese University of Hong Kong
Department of Linguistics and Modern Languages
First Term, 2013-14
Course Title: LING3403 Quantitative Methods for Linguistics
Lecture: Tu 2:30PM – 4:15PM
Tutorial: Tu 4:30PM – 5:15PM
Teaching Venue: LSK_404L (Lee Shau Kee Building, 404 language lab)
Instructor: Dr Fang Liu; f.liu@cuhk.edu.hk; 3943-3779 (lab); G36, Leung Kau Kui Building;
http://www.cuhk.edu.hk/lin/new/people/fangliu/; Office hours: Fridays 10AM – 12PM, or by appointments
TA: Miss Haoyan Ge; hyge@cuhk.edu.hk; 3943-7053 (office); G16, Leung Kau Kui Building;
http://ihome.cuhk.edu.hk/~s1155007071/; Office hours: Tuesdays 10AM – 12PM, or by appointments
Description:
This course introduces common statistical concepts and analyses used in psycholinguistic research. It covers
both descriptive and inferential statistics. Students will understand the basic knowledge through lectures and
gain practical experience in conducting data analyses in tutorials. Students interested in doing quantitative
research for their undergraduate theses should take this course.
This course assumes NO prior knowledge in statistics. Students will learn how to summarize, visualize, and
analyze linguistic data using R, an open-source statistical software environment.
Content, highlighting fundamental concepts
Topics
Contents/fundamental concepts
Research design
Fundamentals of research design
Introduction to R
What is R and why use it? Setting up R & RStudio for use;
Calculations, functions, and variable classes; File handling;
Packages and writing functions
Descriptive statistics and graphics
Frequency tables, histograms, distributions, central tendency,
variability, standard deviation
Inferential statistics
Z scores, the normal curve, proportions, normality, sample vs.
population, probability
Hypothesis testing
Core logic of hypothesis testing, significance levels, one and two
tailed tests, estimation, standard errors, confidence intervals
Statistical power
Decision errors, effect size, statistical power
t tests
The t distribution, single
dependent/independent means
Analysis of variance
The F distribution, basic logic of ANOVA, factorial ANOVA,
post hoc tests
Correlation
Scatter diagrams, correlation direction and size, correlation
coefficient, assessing causality
Chi-Square tests
Chi-Square tests for categorical data
sample
t
tests,
t
tests
for
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Learning outcomes:
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Formulate research questions and design research projects
Use R to conduct statistical analyses
Characterize data using descriptive statistics and graphical methods
Understand the conceptual underpinnings of common statistical tests, and apply them appropriately
Summarize, visualize, and analyze data using a variety of statistical methods
Critically evaluate quantitative analyses in linguistics
Learning activities:
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Lectures (1.45 hrs per week)
Tutorials (0.45 hrs per week)
Assignments and readings (on average 2-3 hrs per week)
Assessment scheme
Task nature
Description
Weight
Participation
Participation in problem-solving activities in tutorial sessions. Each
unexcused absence in lectures or tutorials will incur a 1% deduction of the
total mark. Students with zero participation in tutorials will be deducted
10% of the total mark.
10%
Assignments
There will be 10 homework assignments, which will be handed out in class
in Weeks 2-4 and 6-12, and due by class time one week later. Please submit
hard copies of these assignments. No late assignments accepted.
60%
Final Project
A project that conducts an in-depth analysis of a dataset of your choice.
30%
Total: 100%
Learning resources for students:
Software:
All students will be required to use R, a “language and environment for statistical computing”, which can be
downloaded for free from http://www.R-project.org/. RStudio (http://www.rstudio.com/) is recommended to
be used as an integrated development environment (IDE) for R.
Required textbooks:
Aron, A., Aron, E. N., & Coups, E. J. (2013). Statistics for psychology (6th ed.). Pearson.
Web Chapters (1 through 4) downloaded from http://www.pearsonhighered.com/aron.
Dalgaard, P. (2008). Introductory Statistics with R. Springer.
Suggested readings:
Baayen, H. (2008). Analyzing Linguistic Data: A Practical Introduction to Statistics. Cambridge University
Press.
Gries, S. (2013). Statistics for Linguistics with R. De Gruyter Mouton.
Johnson, K. (2008). Quantitative Methods in Linguistics. Blackwell.
Websites:
RSeek: Web search for R help: http://www.rseek.org/
Joe Fruehwald’s R Study Group page: http://www.ling.upenn.edu/~joseff/rstudy/
Resources to help you learn and use R: http://www.ats.ucla.edu/stat/r/
Handbook of Biological Statistics: http://udel.edu/_mcdonald/statintro.html
Karl Wuensch’s Statistical Help Page: http://core.ecu.edu/psyc/wuenschk/StatHelp/StatHelp.htm
The Little Handbook of Statistical Practice: http://www.jerrydallal.com/LHSP/LHSP.HTM
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Feedback for evaluation
Students are encouraged to give feedback or comments on course contents and teaching materials throughout
the course, in addition to the midterm and final course evaluation.
Course schedule
Class/ week
Week 1
Date
September 3
Week 2
September 10
Week 3
September 17
Week 4
September 24
Week 5
Week 6
October 1
October 8
Week 7
October 15
Week 8
October 22
Week 9
October 29
Week 10
November 5
Week 11
November 12
Week 12
November 19
Week 13
November 26
December 10, Tuesday
Topics and Readings
Course outline and research design
Aron, Aron, & Coups (2013): Web Chapter 1
Introduction to R
Dalgaard (2008): Chapters 1-2
Descriptive statistics and graphics
Aron, Aron, & Coups (2013): Chapters 1-2
Dalgaard (2008): Chapter 4
Inferential statistics
Aron, Aron, & Coups (2013): Chapter 3
Dalgaard (2008): Chapter 3
National Day
Hypothesis testing
Aron, Aron, & Coups (2013): Chapters 4-5
Statistical power
Aron, Aron, & Coups (2013): Chapter 6
Dalgaard (2008): Chapter 9
t tests
Aron, Aron, & Coups (2013): Chapters 7-8
Dalgaard (2008): Chapter 5
Analysis of variance I
Aron, Aron, & Coups (2013): Chapter 9
Dalgaard (2008): Chapter 7
Analysis of variance II
Aron, Aron, & Coups (2013): Chapter 10
Dalgaard (2008): Chapter 7
Correlation
Aron, Aron, & Coups (2013): Chapter 11
Dalgaard (2008): Chapter 6
Chi-Square tests
Aron, Aron, & Coups (2013): Chapter 13
Dalgaard (2008): Chapter 8
Applying statistical methods in your own research project
Aron, Aron, & Coups (2013): Web Chapter 2
Final project due date
Academic honesty and plagiarism
Attention is drawn to University policy and regulations on honesty in academic work, and to the disciplinary
guidelines and procedures applicable to breaches of such policy and regulations. Details may be found at
http://www.cuhk.edu.hk/policy/academichonesty/.
With each assignment, students will be required to submit a signed declaration that they are aware of these
policies, regulations, guidelines and procedures. For group projects, all students of the same group should be
asked to sign on the declaration.
For assignments in the form of a computer-generated document that is principally text-based and submitted
via VeriGuide, the statement, in the form of a receipt, will be issued by the system upon students' uploading
of the soft copy of the assignment. Assignments without the receipt will not be graded by teachers. Only the
final version of the assignment should be submitted via VeriGuide.
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