1  Introduction

In this 5-week block, we’ll cover five topics:

1.1 Working with Data in R (Module Week Two)

This section covers how to import raw data in different formats into R. We’ll also cover some basic coding principles that will underpin our coding across the MSc.

1.2 Data Structures in R (Module Week Three)

This section covers the different data structures that are available within R. We’ll also introduce some of the ways in which data within these structures can be manipulated and transformed.

1.3 Thinking about Data (Module Week Four)

Now that we have developed some basic understanding of how to work with data in R, we’ll start to think about important issues such as data quality and effective data collection. We’ll also cover some basic visualisations in R that can help us start to understand our data.

1.4 Data Analysis 1 (Module Week Five)

We’ll cover two key aspects of data analytics in this section:

First, we’ll examine the critical importance of data pre-processing, where we have to address a number of issues that (if not considered) can ruin any subsequent analysis.

Second, we’ll cover the concept of ‘exploratory data analysis’, where we start to explore our data to identify basic features (such as descriptive statistics) or emerging patterns.

1.5 Data Analysis 2 (Module Week Six)

In the final section of ‘Working with Sport Data in R’, we’ll move on from exploratory data analysis to think about how we can use data to predict the future (predictive analytics). We’ll also think about prescriptive analytics, where data can be used to determine the best course of action moving forward.

This section will introduce some fundamental statistical approaches that will be covered in greater detail in the final section of the module (weeks 7 - 10).