Undergraduate Course: Research Methods & Statistics 3 (PSYL10127)
|School||School of Philosophy, Psychology and Language Sciences
||College||College of Humanities and Social Science
|Credit level (Normal year taken)||SCQF Level 10 (Year 3 Undergraduate)
||Availability||Available to all students
|Summary||This course will cover qualitative methodology and a number of quantitative topics and their relation to the generalized linear model. In the first 5 weeks, a variety of methodologies for collecting and analysing qualitative data will be presented, but we will focus especially on discursive and interpretative phenomenological analyses. The second 5 weeks of the course will focus on topics of scale construction and data reduction. Emphasis will be placed on how and when these different models should be applied to psychological data and how to run such models using R.
This course is split into two halves covering qualitative methodologies and quantitative methods for data reduction and scale development. In the qualitative section of the course, consideration will be given to differing approaches to psychological research, with a focus on qualitative study design and data, discursive analysis, and interpretative phenomenological analysis. In the quantitative aspect of the course, students will be introduced to a range of data reduction methods including cluster analysis, principal components analysis and factor analysis. We will discuss the use of these methods, factor analysis in particular, for scale development and discuss related issues of reliability and validity. The course is taught via a mix of large group lectures, smaller group labs, problem sets and homework. Students will be encouraged to participate in group discussions in all aspects of the course, but are especially encouraged to make use of office hours. The regular homework exercises will provide a means of tracking student development and be a source of regular formative feedback.
Information for Visiting Students
|Pre-requisites||This course teaches using the R statistical package. If you have no experience with R, please contact the course organizer to arrange access to tutorial materials to be completed before the start of the course.
|High Demand Course?
Course Delivery Information
|Academic year 2018/19, Available to all students (SV1)
|Learning and Teaching activities (Further Info)
Lecture Hours 20,
Supervised Practical/Workshop/Studio Hours 10,
Programme Level Learning and Teaching Hours 2,
Directed Learning and Independent Learning Hours
|Assessment (Further Info)
|Additional Information (Assessment)
Reports: 40% (2x 20%)
||Weekly marked homework exercises delivered via LEARN.
Weekly office hours with lecturers.
Weekly problem sets with answers.
Online Q&A sessions.
||Hours & Minutes
|Main Exam Diet S2 (April/May)||Research Methods & Statistics 3||2:00|
On completion of this course, the student will be able to:
- Understand concepts in scale construction and assessment.
- Understand concepts of data reduction methods including interpretation, model assumptions and methods to assess them.
- Be able to run the above statistical tests in R and evaluate applications of these methods in published research.
- Understand the rationale underlying qualitative methodologies and know about various means of collecting and analyzing qualitative data.
- Be able to conduct qualitative analyses and evaluate applications of these methods in published research.
|Graduate Attributes and Skills
|Course organiser||Dr Sue Widdicombe
Tel: (0131 6)50 3411
|Course secretary||Ms Alexandra MacAndrew
Tel: (0131 6)51 3733