Please note: there may be some adjustments to the teaching arrangements published in the course catalogue for 2020-21. Given current circumstances related to the Covid-19 pandemic it is anticipated that some usual arrangements for teaching on campus will be modified to ensure the safety and wellbeing of students and staff on campus; further adjustments may also be necessary, or beneficial, during the course of the academic year as national requirements relating to management of the pandemic are revised.

Formal Models and Quantitative Methods for Psychology (PGT) PSYCH5025

  • Academic Session: 2022-23
  • School: School of Psychology and Neuroscience
  • Credits: 10
  • Level: Level 5 (SCQF level 11)
  • Typically Offered: Semester 2
  • Available to Visiting Students: No
  • Available to Erasmus Students: No

Short Description

The course typically introduces students to the R/RStudio modelling environments through hands-on sessions providing a mixture of lectures, class exercises and presentations/workshops.

Timetable

10 hours x lecture

Requirements of Entry

Typically a 2:1 honours degree in Psychology or related discipline.

Excluded Courses

None

Assessment

An original computer program/application that performs a specific task relevant to the modelling techniques described in the course.

Course Aims

To introduce students to formal models in the psychological sciences. This entails the application of parametric estimation and inference, prediction and testing of models, and quantitative methods in general.

Intended Learning Outcomes of Course

By the end of this course students will be able to:

■ use specialised tools for quantitative methods (e.g. packages in R)

■ critically evaluate challenges of formal modelling, and parametric testing (e.g. sampling, simulation)

■ engage in cutting-edge applications of data analyses (e.g. statistical learning)

■ develop interactive apps (e.g. shiny apps in R/RStudio)

■ present and communicate functionality of IT solutions  

Minimum Requirement for Award of Credits

Students must submit at least 75% by weight of the components (including examinations) of the course's summative assessment.