2  Course Resources

In addition to this course information book and the lectures, we have a range of resources to help develop your quantitative research methods skills.

2.1 Fundamentals of Quantitative Analysis

To support this course, we have the Fundamentals of Quantitative Analysis book which teaches you data skills in R/RStudio, like programming basics, data wrangling, visualisation, and inferential statistics. We work through chapters 1 to 11 in RM1, then you will continue with chapters 12 to 14 in RM2.

Data skills takes time and trial and error to learn. We direct you to one or two chapters per week to develop your initial skills. Each chapter has a range of “try this” activities to apply what you learnt and check your answers against solutions. We also have “error mode” activities to get you used to making errors in coding. This can be the most intimidating part of learning to code but experienced coders do not stop making mistakes, they just get better at diagnosing and fixing their mistakes. Finally, we have data analysis journey chapters. These provide longer less structured activities to get you wrangling, visualising, and/or analysing data sets. These are meant as the bridge between the core chapters to your assessments where you no longer have solutions to check your answers against.

2.2 Handy workbook

An additional resource we will link to time to time is A Handy Workbook for Research Methods & Statistics. From around week 6, we will introduce you to inferential statistics. When you use these practically, you will use R/RStudio to efficiently analyse larger amounts of data. In the Handy Workbook, we work through step-by-step how these statistical tests work, so you can gain a better understanding of what numbers go in, what happens to those numbers, and what numbers come out.

2.3 Course reading list

To support each week, there is a course reading list which is linked on the Moodle page, but you can access it by following this link. We appreciate you only have so much time each week and have other courses to complete, so the resources are labelled as essential, recommended, and further.

Essential sources are those that we have curated to directly supplement the lecture and lab material, and you should do your best to keep up with reading these each week.

Recommended sources are those that we think are useful and supplement the course, but you should only read them if you have time.

Further sources are those we find interesting and provide a deeper dive if you find you really enjoy the content in this course.