BA English Language and Japanese

Year of entry: 2023

Course unit details:
Quantitative Methods in Language Sciences

Course unit fact file
Unit code LELA32011
Credit rating 20
Unit level Level 3
Teaching period(s) Semester 1
Available as a free choice unit? Yes

Overview

This course aims to familiarize students with the basic concepts of statistics through hands-on practice. Topics covered in the course include distributions of data, basic principles of probability, describing and visualizing quantitative data, and interpreting quantitative data through hypothesis testing.

Aims

The principal aims of the course unit are as follows:

  • To familiarize students with basic statistical concepts and terms necessary to understand quantitative research
  • To help students understand the rules of describing, visualizing, and interpreting data
  • To help students develop computer skills needed to work with quantitative data
  • To foster critical thinking skills necessary for conducting quantitative research in the future

Syllabus

Some representative topics covered:

  • Variable types
  • Descriptive statistics
  • Visualising Data
  • Probability and Inference
  • Correlation and regression
  • Multiple regression
  • Comparing means
  • Experimental design and generalisation

Teaching and learning methods

Weekly 1 hour lecture (online)

Weekly 2 hour computer data-analysis tutorial

E-learning: The Blackboard environment will provide: lecture recordings, lecture slides, tutorials on using R, reading assignments (beyond the main textbook), revision quizzes, additional exercises. We will also use the Blackboard discussion forum.

Knowledge and understanding

By the end of this course students will be able to:

  • Understand fundamentals of quantitative analysis
  • Be familiar with basic statistical methods
  • Describe, summarize, and visualize data
  • Conduct basic statistical tests by hand and using computer statistical software

Intellectual skills

By the end of this course students will be able to:

  • Identify appropriate descriptive and data visualization methods for different types of data
  • Assess validity and soundness of conclusions drawn from basic statistical tests

Practical skills

By the end of this course students will be able to:

  • Form sound statistical hypotheses based on research questions
  • Use computer programs to visualize and summarize data and conduct basic statistical tests.
  • Write simple computer code (using the R package)

Transferable skills and personal qualities

By the end of this course students will be able to:

  • Use a variety of quantitative techniques to explore quantitative data
  • Draw conclusions from quantitative data through both descriptive and inferential statistics
  • Become comfortable working with quantitative data
  • Develop time management skills by working to deadline

Employability skills

Analytical skills
By the end of the semester, students are expected to be able to use computer software programs to describe, visualize data, and conduct some basic statistical tests. These skills will be beneficial to students regardless of whether they intend to pursue academic or non-academic careers.
Research
For students interested in pursuing postgraduate degrees in linguistics, many subfields of linguists are becoming more and more data-driven, so the quantitative skills acquired in this class will provide a good foundation, making it easier for students to start their own research.
Other
For students intending to pursue non-academic careers, quantitative skills will be a valuable asset as many employers increasingly look for job candidates that have both domain-specific knowledge (e.g., linguistic knowledge) and general quantitative skills.

Assessment methods

Assessment Task

Formative or Summative

Weighting

Blackboard Quizzes

Formative

0%

Coursework (Analysis Report)

Summative

75%

Mid-term Exam

Summative

25%

 

Feedback methods

Blackboard quizzes: individual scores Formative
Coursework mark and individual feedback Formative and summative
Exam mark Summative

 

Recommended reading

Winter, B. (2019). Statistics for linguists: An introduction using R. Routledge

Field, A. and Hole, G., 2002. How to design and report experiments. Sage.

Crawley, Michael J. (2005). Statistics: An Introduction Using R.

Johnson, Keith (2008). Quantitative Methods in Linguistics.

Study hours

Scheduled activity hours
Assessment written exam 1.5
Lectures 11
Tutorials 22
Independent study hours
Independent study 165.5

Teaching staff

Staff member Role
Andrea Nini Unit coordinator
Patrycja Strycharczuk Unit coordinator

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