Postgraduate Course: Statistics and Quantitative Methods (LASC11172)
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 is an introduction to study design, statistics and quantitative data analysis as commonly employed in linguistics, using the R software. |
| Course description |
The course will cover the basics of statistics and quantitative data analysis, and how to design studies that effectively address the intended research questions. Students will learn the principles of data visualisation and statistical modelling and develop the practical skills necessary to perform such analyses. The course will draw examples from different branches of linguistics and will provide students with hands-on experience in open science practices.
The course will teach students how to carry out Bayesian statistical inference using a wide variety of statistical models, and how to interpret results from traditional Null Hypothesis Significance Testing (i.e. p-values and confidence intervals).
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Entry Requirements (not applicable to Visiting Students)
| Pre-requisites |
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Co-requisites | |
| Prohibited Combinations | |
Other requirements | None |
Information for Visiting Students
| Pre-requisites | None |
Course Delivery Information
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| Academic year 2022/23, Available to all students (SV1)
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Quota: None |
| Course Start |
Semester 2 |
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 %
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| Additional Information (Assessment) |
Coursework 100% |
| Feedback |
Not entered |
| No Exam Information |
Learning Outcomes
On completion of this course, the student will be able to:
- demonstrate an understanding of the difference between descriptive and inferential statistics
- critically evaluate study designs and statistical analyses
- perform a range of statistical analyses with a widely-used statistical software package
- present the results of statistical analyses in a clear and comprehensible way
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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 Stefano Coretta
Tel:
Email: |
Course secretary | Mrs Elinor Lange
Tel: (0131 6)51 3188
Email: |
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