Module PSYC3901: The Use and Misuse of Statistics in Psychological Research

Department: Psychology

PSYC3901: The Use and Misuse of Statistics in Psychological Research

Prerequisites

• 60 credits from Level 2 psychology including either PSYC2232 Advanced Research Methods and Statistics OR PSYC2261 Advanced Psychological Research for Non-Single Honours

Corequisites

• None

Excluded Combination of Modules

• None

Aims

• To teach students a set of advanced statistical methods that are used across psychology, neuroscience and the behavioural sciences including the ability to confidently identify appropriate statistical techniques and analyse data using relevant software across a range of different types of research
• To enable students to contextualise the use of statistical methods in the broader research context, including a consideration of questionable research practices such as p-hacking and HARKing (hypothesising after the results are known) and open science practices such as preregistration and replication.

Content

• Statistical methods for modelling using programming tools (e.g., R), and could include for instance classical statistics, linear models, logistic regression, and general linear models.
• This module also examines questionable research practices (e.g., p-hacking; HARKing) and open science practices (e.g., preregistration; replication).
• Topics can vary from year to year but are likely to include meta-analysis; mediation; moderation; Bayesian methods; questionable research practices; HARKing; preregistration; open science; the replication crisis.

Learning Outcomes

• On completion of this module, students will acquire knowledge and understanding of: A range of advanced statistical tests used in psychology, neuroscience, and the behavioural sciences.
• The assumptions and limitations of the statistical techniques covered.
• Questionable research practices and approaches to reduce them (e.g., pre-registration).

• Have the ability to review and analyse critically evidence derived from different sources, evaluate different research methods, and identify questionable research practices.
• Have the ability to conduct a range of advanced statistical tests.

• Good IT skills related to data manipulation and data presentation.
• Ability to work independently in scholarship and research within broad guidelines.
• Critical thinking.

Modes of Teaching, Learning and Assessment and how these contribute to the learning outcomes of the module

• Student understanding and practical ability to use the statistical tools will be facilitated by workshops supplemented with online material.
• The workshops will take place in a computer laboratory, where students will get experience in using the statistical tools.
• Students' acquisition of detailed knowledge will be facilitated by lectures, within-lecture interactive elements such as small group work and discussions, audio-visual materials, and detailed reading lists.
• These modes of teaching provide students with detailed knowledge of the key theories and the skills needed to evaluate different theoretical positions in light of current evidence.
• Summative assessment is done through a statistical report, exercises, as well as an essay in the style of a blog post.
• Formative Assessment will be through in-class presentation.

Teaching Methods and Learning Hours

Summative Assessment

Formative Assessment:

In Class Presentation.

■ Attendance at all activities marked with this symbol will be monitored. Students who fail to attend these activities, or to complete the summative or formative assessment specified above, will be subject to the procedures defined in the University's General Regulation V, and may be required to leave the University