2  Introduction

2.1 How the module runs

The module is designed to accomplish two things.

First, you’ll be introduced to a wide range of quantitative techniques that can be applied to sport (and other) data. By the end of the module you should be confident in the application of these techniques.

Second, you’ll be introduced to a wide range of concepts and ideas that related to the research process in social science (including data collection, analysis, and reporting), drawing on both quantitative and qualitative paradigms.

These outcomes will be achieved through three different, but overlapping sets of activities:

The first is ‘pre-reading’. For each week, there will be a set of short tutorial-style readings that should be completed prior to the class meeting each Wednesday. These readings will cover the conceptual foundations that will be developed through the practical in-class activities. It’s essential that these readings are completed. I’ll release this material each Saturday.

The second is a series of in-class ‘practicals’. Each Wednesday, we will engage in a series of practical, hands-on activities that will allow you to develop your understanding and practice your applied data analysis skills. These practicals will include a walk-through/demonstration of the different techniques, and an opportunity for you to practice them on your own.

The final element to the module is ‘post-reading’. This is a set of short tutorial-style readings that should be completed after each class meeting. Generally, these readings will cover some of the more conceptual and theoretical elements of Research Methods.

2.2 Key topics

The module will cover eight key topics:

  1. Introduction to Research Methods

  2. Literature Reviews and Conceptual Frameworks

  3. Quantitative Methods

  4. Time-Series Analysis

  5. Validity in Sport Data

  6. Machine Learning

  7. Ethics in Research

  8. Reporting Research

2.3 Depth and breadth

The purpose of this module is to provide an overview of, and introduction to, a range of different concepts and techniques that are commonly used within research in sport.

It’s designed to given sufficient insight and experience in using these techniques that you’ll:

  1. Be able to understand research that has been undertaken using these methods and;
  2. Have enough confidence and understanding to explore these techniques and concepts further.

Some of the techniques we’ll encounter are quite complex and there is insufficient time to explore them all in depth. Rather, I’m hoping that you will be encouraged to explore these further, and deepen your understanding and confidence in their use.

The idea of the ‘toolbox’ is important here. It’s good to know what’s available and what it’s used for, even if you’re not an expert in every tool.

2.4 Required packages

During the module, we’ll be using the following packages. Please make sure you have these downloaded and installed prior to each Wednesday session:

  • car

  • caret

  • CCA

  • cluster

  • dendextend

  • dplyr

  • e1071

  • forecast

  • ggplot2

  • GPArotation

  • GGally

  • ggfortify

  • lavaan

  • lmtest

  • lubridate

  • MASS

  • mclust

  • multcomp

  • psych

  • semPlot

  • tseries

  • urca