Postgraduate Course: Statistics and Experimental Design (10 Credits) (LASC11168)
Course Outline
| School | School of Philosophy, Psychology and Language Sciences |
College | College of Arts, Humanities and Social Sciences |
| Credit level (Normal year taken) | SCQF Level 11 (Postgraduate) |
Availability | Available to all students |
| SCQF Credits | 10 |
ECTS Credits | 5 |
| Summary | This course introduces key principles of experimental design and statistical methods as applied to linguistic research. It considers how to use data to test research hypotheses and explains how to conduct the appropriate statistical analysis with a widely-used statistical package, R. |
| Course description |
This course provides an introduction to experimental design and statistical methods for linguistics and psycholinguistics, assuming a minimal amount of prior knowledge and experience. We will explore a range of standard statistical methods and discuss how to apply them and under what circumstances they are appropriate, as well as the practicalities of performing these analyses using R as a statistical package.
The course will proceed from the simplest statistical tests via t-tests, correlation and regression through to an introduction to linear models, as well as considering non-parametric methods and the limitations of null hypothesis testing. We will also consider how to design experiments in such a way as to address typical theoretical questions in a range of linguistic subfields.
The course will be taught via lectures supported by lab materials, which will give students the opportunity to familiarise themselves with the practicalities of statistical analysis at their own pace and with readily-available support. Students completing the course will be able to formulate, justify and critique designs for experiments to test linguistic hypotheses, and be able to conduct suitable statistical analyses using R.
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Information for Visiting Students
| Pre-requisites | None |
| High Demand Course? |
Yes |
Course Delivery Information
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| Academic year 2021/22, Available to all students (SV1)
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Quota: None |
| Course Start |
Semester 1 |
Timetable |
Timetable |
| Learning and Teaching activities (Further Info) |
Total Hours:
100
(
Lecture Hours 27,
Programme Level Learning and Teaching Hours 2,
Directed Learning and Independent Learning Hours
71 )
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| Assessment (Further Info) |
Written Exam
0 %,
Coursework
100 %,
Practical Exam
0 %
|
| Additional Information (Assessment) |
Take Home Exam 100% |
| Feedback |
Lab exercises will be provided that anticipate the format of the exam; model answers will be published. |
| No Exam Information |
Learning Outcomes
On completion of this course, the student will be able to:
- understand the difference between descriptive and inferential statistics, and the motivations for calculating and reporting each kind of statistic
- critically evaluate experimental designs and statistical analyses
- perform a range of statistical analyses with a widely-used statistical software package
- present the results of statistical analyses in accordance with the standards of the experimental linguistics literature
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Reading List
| Field, A., Miles, J., and Field, Z. (2012). Discovering Statistics Using R. London: SAGE Publications. |
Additional Information
| Graduate Attributes and Skills |
Not entered |
| Keywords | behaviour,analysis,methodology,descriptive statistics,inferential statistics,R |
Contacts
| Course organiser | Dr Christopher Cummins
Tel: (0131 6)50 6858
Email: ccummins@exseed.ed.ac.uk |
Course secretary | Miss Toni Noble
Tel: (0131 6)51 3188
Email: Toni.noble@ed.ac.uk |
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