Welcome to Psychology as a Science. You can find all the course materials, such as lecture slides, lecture handouts, and practical worksheets listed on this page.
Lecture 1: Introduction
Handout for Lecture 1 of PAAS, School of Psychology @ UniSussex
Lecture 2: Philosophy of Science
We try to answer the question: 'What is this thing called "science"?'
Lecture 3: Approaches to Research
Here we cover some approaches to you take to answering research questions. We’ll cover qualitative and quantitative methods and briefly discuss methods like computer simulation and formal methods
Quantitative research, measurement, and variables
Lecture 4: Quantitative research
In an almost 60 slide-long lecturepalooza, we take you on a road trip through quantitative research design, measurement, and variables. That’s value for money, that!
Lecture 5: Open Science
In this lecture we’ll talk about "open science", the replication crisis, preregistration, and the lab report.
Lecture 6: Samples, Populations, and Distributions
In this lecture we’ll learn about samples and populations and how samples and populations can be described with distributions.
Descriptive statistics and the sampling distribution
Lecture 7: Towards statistical models
In this lecture we will discuss basic descriptive statistcs, viewing them not just as ways of summarising variables but also as simple models of the world. Then, we will "go a little meta" by talking about how these statistics are themselves variables with their own distributions and descriptive stats.
Distributions, functions, transformations
Lecture 8: Distributions, functions, transformations
In this lecture we will start thinking about variables in terms of distributions. We will see how we can perform simple arithmetic operations, such as addition and multiplication on entire variables to perform linear transformations. We’ll discuss one transformation in particular, the z-transformation, and see how it’s used to standardise the values of a variable. Finally, we will talk about how we can use simple maths to compare groups on a measured variable of interest.
Lecture 9: Tables and plots
In this lecture we will learn how to create neat tables and plots allowing us to convey a lot of information about data in a small space.
Lecture 10: Introduction to probability
In this lecture we’ll cover the basics of probability and how to reason about probabilities.
Lecture 11: Recap
The final lecture of Psychology as a Science focuses on recapitulating the topics from the previous lectures with a main focus on Q&A
Getting setup and algorithmic thinking
Working with R Project files
In this practical we’ll learn about how to work with R Project files, how to organise our files, and how to specify file paths
Writing and running code in R Studio
When to use the console and when not to? How do I include R code in R Markdown? How is R code executed anyway?
Data stuctures and assignment
Playing around with vectors and tibbles
Functions and packages
In this practical we’ll learn how to extend
R using packages and how to use functions
In this practical we’ll learn how to organise data in the tidy way
Data wrangling with dplyr
In this week’s practical we’re going to learn how to manipulate the transform data with the
Grouping, summarising, and piping
In this practical we’ll learn how to group data, summarise data, and use pipes
%>% to chain operations together