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 material

### Week 01

Lecture 1: Introduction

Handout for Lecture 1 of PAAS, School of Psychology @ UniSussex

### Week 02

Lecture 2: Philosophy of Science

We try to answer the question: 'What is this thing called "science"?'

### Week 03

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

### Week 04

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!

### Week 05

Lecture 5: Open Science

In this lecture we’ll talk about "open science", the replication crisis, preregistration, and the lab report.

### Week 06

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.

### Week 07

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.

### Week 08

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.

### Week 09

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.

### Week 10

Lecture 10: Introduction to probability

In this lecture we’ll cover the basics of probability and how to reason about probabilities.

### Week 11

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

## Practical worksheets

### Week 02

Getting setup and algorithmic thinking

Algorithmic thinking

### Week 03

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

### Week 04

R Markdown

Wiriting documents using R Markdown

### Week 05

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?

### Week 06

Data stuctures and assignment

Playing around with vectors and tibbles

### Week 07

Functions and packages

In this practical we’ll learn how to extend `R` using packages and how to use functions

### Week 08

Organizing data

In this practical we’ll learn how to organise data in the tidy way

### Week 09

Data wrangling with dplyr

In this week’s practical we’re going to learn how to manipulate the transform data with the `dplyr` package.

### Week 10

Grouping, summarising, and piping

In this practical we’ll learn how to group data, summarise data, and use pipes `%>%` to chain operations together

### Week 11

Pretty tables and plots

Creating pretty tables and plots in R the clever way.

Table and figures with kbl() and ggplot()