Advanced Quantitative Methods module (PY52007)

This module will provide you with an understanding of statistical analyses used in psychological research. It aims to teach you the use of appropriate advanced statistical methods.

Using a problem-oriented approach, you will learn the following topics:

• hypothesis testing
• correlation
• regression
• ANOVA
• multilevel models
• structural equation modelling
• mediation and moderation

You will also learn to conduct power analysis, alongside learning the open science principles that are embedded throughout the module.

What you will learn

In this module you will:

• consider what analyses are appropriate for your research design
• learn how these analyses work
• learn how to run analyses
• learn how to interpret analyses and report the results
• focus on the common logic of statistical analyses by looking at the general linear model, showing how all the analyses we do are different cases of this

By the end of this module, you will be able to:

• design studies efficiently and effectively
• understand the range of statistical procedures and their appropriate use
• report, visualise, and evaluate findings using advanced statistical method

Assignments / assessment

weekly quizzes (30%)

• a total of nine quizzes
• starts in week 3
• given on Wednesday at noon
• due on Fridays at noon
• each quiz may only be attempted once

short answer assignment (30%)

• answer common statistical questions, e.g.:
  • What is a test statistic?
  • Why do we need to check for assumptions in data testing?
• given in week 3
• due in week 6

final assignment 2,000 words (40%)

• formulate a hypothesis based on a dataset
• conduct your own analysis to test that hypothesis
• write up the results in a report
• due in week 11

This module does not have a final exam.

Teaching methods / timetable

Teaching and learning material are provided via:

• weekly pre-recorded content
  • available each Friday before the next practical session
• weekly practical sessions
  • Fridays (1pm-3pm)
  • sessions will recap material covered in pre-recorded sessions for 30-45 minutes before covering theory and practical examples in G*Power and JASP
  • practical sessions will not be recorded

We will be using JASP in this module. JASP is an open-source statistics interface supported by the University of Amsterdam. You can download JASP here. Please bring a laptop to the on-campus sessions if you can. There will also be University computers available. 

It is also recommended that you download a copy of G*Power. G*Power is a tool to compute statistical power analyses. You can download G*Power here.