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Welcome to the Fundamentals of Quantitative Analysis

This book has been written and designed to help you learn core data skills through R and RStudio. These skills will lead to you being able to manipulate and analyse quantitative data - a key component of any accredited Psychology programme. In addition to this book the team will support you with helpful skills demonstration videos, and we would encourage you to use Teams to ask any questions that you have.

The ability to work with quantitative data is a key skill for Psychologists and by using R as our tool, for working with data, we can also promote reproducible research practices. Although at first it may seem like writing a programming script is more time-consuming than other point-and-click approaches, this is not the case! Once you have written a script that does what you need it to do, you can easily re-run your analysis without having to go through each step again manually which is a) easier and b) less likely to result in errors if you do something slightly different or forget one of the steps.

Crucially, with an analysis script other researchers can also see how you got from the raw data to the statistics you report in your final paper. Sharing analysis scripts online on sites such as the Open Science Framework is now seen as an important open science practice. Even if you don't continue with quantitative research, in the future, the skills you develop on this course will allow you to evaluate quantitative research and to understand what goes on behind the scenes with data before the conclusions are presented, allowing you to become much more confident and competent consumers and users of research.

How to use this book and the accompanying videos

Within the book itself, for many of the initial chapters, we will provide the code you need to use. We would always strongly encourage you to type out the code yourself, as this is good practice for learning to code, but remember you can copy and paste from the book if you need to. Typing the code will seem much slower at first and you will make errors, lots of them, but you will learn much more quickly this way so do try to write the code yourself where you can.

We also provide the solutions to many of the activities. No-one is going to check whether you tried to figured out an activity yourself rather than going straight to the solution but remember this, if you copy and paste without thinking, you will learn nothing. Learning data skills and the knowledge that underpins those skills is much like learning a language - the more you practice and the more you use it, the better you become.

Additionally, a number of the chapters of this book have an associated video or videos. These videos are there to support you as you get comfortable in your data skills. However, it is important that you use them wisely. You should always try to work through each chapter of the book (or if you prefer each activity) on your own first, and only then watch the video if you get stuck, or for extra information.

Finally, this book is a living document. What that means is that on occasion we will make updates to the book such as fixing typos and including additional detail or activities. When substantial changes are made, we will create new support materials such as an accompanying video. However, it would be impossible to record a new video every time we make a minor change to an activity, therefore, sometimes there may be slight differences between the videos and the content of this book. Where there are differences between the book and the video, the book should always be considered the definitive version.

Intended Learning Outcomes

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

  • Clean and wrangle data into appropriate forms for analysis
  • Visualise data using a range of plots
  • Conduct and interpret a core set of statistical tests (t-test, correlation, ANOVA, regression)