Undergraduate Course: Statistics and Quantitative Methods (Semester 2) (LASC10119)
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 10 (Year 3 Undergraduate) |
Availability | Available to all students |
| SCQF Credits | 20 |
ECTS Credits | 10 |
| 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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Information for Visiting Students
| Pre-requisites | Visiting students should have completed at least 3 Linguistics/Language Sciences courses at grade B or above . We will only consider University/College level courses. |
Course Delivery Information
|
| 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:
200
(
Lecture Hours 18,
Seminar/Tutorial Hours 9,
Programme Level Learning and Teaching Hours 4,
Directed Learning and Independent Learning Hours
169 )
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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
- Perform a range of statistical analyses with a widely-used statistical software package
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Additional Information
| Graduate Attributes and Skills |
Not entered |
| Keywords | Not entered |
Contacts
| Course organiser | Dr Stefano Coretta
Tel:
Email: s.coretta@ed.ac.uk |
Course secretary | Mr Liam Hedley
Tel: (0131 6)50 9870
Email: liam.hedley@ed.ac.uk |
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