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# BA Linguistics / Course details

Year of entry: 2020

## Course unit details:Quantitative Methods in Language Sciences

Unit code LELA20232 20 Level 2 Semester 2 Linguistics & English Language 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

### Learning outcomes

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

### Syllabus

Provisional outline

Week 1: Why use quantitative methods?

Week 2: Descriptive statistics

Week 3: Visualising data

Week 4: Probability and inference

Week 5: Comparing two means

Week 6: Comparing multiple means

Week 7: Correlation and regression

Week 8: Multiple regression

Week 9: Categorical data

Week 10: Experimental design and generalisation

Week 11: Choosing the right statistical test. Revision.

### Teaching and learning methods

•   Weekly 1.5 hour lecture
• Weekly 1.5 hour computer data-analysis tutorial
• E-learning: The Blackboard environment will provide: lecture slides, tutorials on using R, reading assignments (beyond the main textbook), revision quizzes, materials for exam preparation, additional exercises. We will also use the Blackboard discussion thread.

### Knowledge and understanding

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

• Know the characteristics of basic data distributions
• Understand different levels of measurement (e.g., nominal, ordinal, interval, ratio)
• Know different descriptive statistics used to summarize data
• Know different kinds of plots for data visualization
• Understand the assumptions behind basic statistical tests
• Conduct basic statistical tests using statistical package R

### 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.
Other
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. 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 Length Weighting within unit(if summative) 2 take-home quizzes formative N/A Dossier based on 3 home assignments (summative) summative Coursework equivalent to a 2,500 words assignment 50% Final exam summative 1.5 h 50%

### Feedback methods

 Feedback method Formative or summative Blackboard quizzes will provide individual scores formative General feedback on homework assignments will be given in lectures. Students will have the opportunity to modify their assignment for the final dossier, based on this feedback.Final dossier will be graded formative and summative Additional one-to-one feedback will be provided as required during consultation hour or by appointment formative

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

### Study hours

Scheduled activity hours
Assessment written exam 1.5
Lectures 16.5
Seminars 16.5
Independent study hours
Independent study 165.5

### Teaching staff

Staff member Role
Patrycja Strycharczuk Unit coordinator