Module Details

Module Code: DATA
Module Title: Introduction to Data Analysis for Sport
Title: Introduction to Data Analysis for Sport
Module Level:: 8
Credits:: 5
Module Coordinator: Myles Kelly
Module Author:: Denise Earle
Domains:  
Module Description: The aim of this module is to develop students' mathematical and statistical skills with a view to using these skills to analyse sports data. Students will be introduced to the areas of data visualisation, descriptive statistics and inferential statistics. The students will also be introduced to the use of statistical software for data analysis.
 
Learning Outcomes
On successful completion of this module the learner will be able to:
# Learning Outcome Description
LO1 Describe basic concepts in statistics, data visualisation and data analysis.
LO2 Evaluate and apply key descriptive analysis techniques when carrying out analysis of sports data.
LO3 Evaluate and apply key inferential statistical techniques when carrying out analysis of sports data.
LO4 Solve well-formed problems by selecting the appropriate techniques and presenting the answer in a sporting context.
Dependencies
Module Recommendations

This is prior learning (or a practical skill) that is recommended before enrolment in this module.
No recommendations listed
Co-requisite Modules
No Co-requisite modules listed
Additional Requisite Information
No Co Requisites listed
 
Indicative Content
Introduction to Statistics
Different data types, tabulation of data, and sampling. Measures of central tendency and dispersion including mean, median and standard deviation.
Data Visualisation
Description of different data visualisation techniques, their purpose and when they are suitable to use. Best practices in data visualisation.
Inferential Statistics
Application of correlation, linear regression and hypothesis testing to analysing sports data.
Computer Practicals
Application of theoretical material using relevant software.
Module Content & Assessment
Assessment Breakdown%
Continuous Assessment100.00%

Assessments

Full Time

Continuous Assessment
Assessment Type Other % of Total Mark 100
Timing n/a Learning Outcomes 1,2,3,4
Non-marked No
Assessment Description
Learners will be required to demonstrate achievement of the learning outcomes through continuous assessment. This work may take the form of a project (individual/group), practical exam, presentation, case analysis, poster presentation but is not limited to these formats.
No Project
No Practical
No End of Module Formal Examination
Reassessment Requirement
Exam Board
It is at the discretion of the Examination Board as to what the qualifying criteria are.

SETU Carlow Campus reserves the right to alter the nature and timings of assessment

 

Module Workload

Workload: Full Time
Workload Type Workload Category Contact Type Workload Description Frequency Average Weekly Learner Workload Hours
Contact Hours Contact A mix of lectures and practical sessions. Every Week 3.00 3
Independent Learning Non Contact Independent Learning completed by student. Every Week 6.00 6
Total Weekly Contact Hours 3.00
 
Module Resources
Recommended Book Resources
  • Thomas A. Severini. (2020), Analytic Methods in Sports, Chapman & Hall/CRC, [ISBN: 9780367469382].
  • O'Donoghue, P. & Holmes, L.. (2015), Data Analysis in Sport, Routledge, Taylor & Francis Group, London, New York.
  • O'Donoghue, P.. (2012), Statistics for Sports and Exercise Studies, 1st. Routledge.
Recommended Article/Paper Resources
  • Journal of Quantitative Analysis in Sports.
  • International Journal of Performance Analysis in Sport.
Other Resources
Discussion Note: