Postgraduate Course: Inferential Statistics in Applied Psychology (CLPS11073)
Course Outline
| School | School of Health in Social Science |
College | College of Arts, Humanities and Social Sciences |
| Credit level (Normal year taken) | SCQF Level 11 (Postgraduate) |
Availability | Not available to visiting students |
| SCQF Credits | 20 |
ECTS Credits | 10 |
| Summary | This course aims to provide students with both a theoretical and practical understanding of inferential statistics and their use in psychology. It is aimed primarily at postgraduate students who have completed an undergraduate degree in Psychology or a cognate subject, and who have a basic understanding of statistical principles and assumptions, including the ability to conduct descriptive statistics. The course will cover a range of statistical methods and content, such as t-tests, correlation, regression, and mediation. After taking this course, students should be able to make choices regarding the appropriate use of statistical tests dependent on research questions, independently run statistical analysis, and interpret and effectively report analysis results.
This course is one of the core options for students on the MSc in Mental Health in Children & Young People. |
| Course description |
Statistical testing and inference are important and necessary elements of graduate learning in psychology. The ability to understand how to meaningfully test hypotheses and interpret the results, are required components for any student undertaking an empirical dissertation project. This course is meant to provide students with both theoretical and applied competencies related to the use of inferential statistics. Students will attend weekly lectures, as well as practical lab sessions where they will have the opportunity to engage in hands-on-training related to the concepts covered in the lecture that week. Achievement of learning outcomes will be assessed via a statistical report, which will require students to demonstrate a combination of theoretical and applied knowledge.
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Entry Requirements (not applicable to Visiting Students)
| Pre-requisites |
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Co-requisites | |
| Prohibited Combinations | |
Other requirements | Programme entrance qualifications apply |
Course Delivery Information
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| Academic year 2024/25, Not available to visiting students (SS1)
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Quota: None |
| Course Start |
Semester 2 |
Timetable |
Timetable |
| Learning and Teaching activities (Further Info) |
Total Hours:
200
(
Lecture Hours 20,
Supervised Practical/Workshop/Studio Hours 10,
Programme Level Learning and Teaching Hours 4,
Directed Learning and Independent Learning Hours
166 )
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| Assessment (Further Info) |
Written Exam
0 %,
Coursework
100 %,
Practical Exam
0 %
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| Additional Information (Assessment) |
Assessment 100%
The final assessment will assess student¿s knowledge of theoretical and applied knowledge of inferential statistics. Students will be required to work hands on with dummy data and address different research questions. This will test their analysis, interpretation and write up skills. |
| Feedback |
Tutorial exercises will be tailored more towards practicing the skills that will be assessed in the final graded summative assessment. |
| No Exam Information |
Learning Outcomes
On completion of this course, the student will be able to:
- Demonstrate theoretical knowledge and critical understanding of inferential statistics.
- Demonstrate understanding of assumptions and limitations of inferential statistics.
- Demonstrate the ability to conduct inferential statistics and model building appropriate to research questions.
- Demonstrate the ability to make critical inferences regarding statistical testing.
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Additional Information
| Graduate Attributes and Skills |
* Critical thinking, ability to analyse, and evaluate research via better understanding of statistical testing and inferences.
* Ability to critically select appropriate statistical tests in applied research.
* Ability to parse and critically interpret statistical information in published research.
* Critical understanding of interpreting practical meaning from statistics.
* Applied knowledge of statistical testing and inference.
* Autonomy skills via independent learning.
* Improvement of analytical skills.
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| Keywords | Statistical Analysis,Inferential Statistics |
Contacts
| Course organiser | Dr Monica Truelove-Hill
Tel:
Email: m.truelovehill@ed.ac.uk |
Course secretary | Ms Katie Killeen
Tel: (01316) 513969
Email: kkilleen@ed.ac.uk |
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