DATA SCIENCE AND STATISTICS FOR SPORT
SPE2DSS
2019
Credit points: 15
Subject outline
Students will develop an understanding of research methodology, statistical analysis and data science techniques specific to the application within sports and exercise science. Students will explore various research designs and statistical approaches that will allow them to critically analyse data to apply results in a practical environment. The subject will teach students how to perform various data handling techniques, statistical tests and explore data visualisation techniques to effectively demonstrate outcomes in a professional setting.
School: School Allied Health,Human Serv & Sport
Credit points: 15
Subject Co-ordinator: Andrew Govus
Available to Study Abroad Students: Yes
Subject year level: Year Level 2 - UG
Exchange Students: Yes
Subject particulars
Subject rules
Prerequisites: HLT1RAE
Co-requisites: N/A
Incompatible subjects: N/A
Equivalent subjects: N/A
Special conditions: N/A
Learning resources
Readings
| Resource Type | Title | Resource Requirement | Author and Year | Publisher |
|---|---|---|---|---|
| Readings | Statistics for sports and exercise science: a practical approach | Prescribed | Newell, J., Aitchison, T., & Grant, S. (2014) | Routledge |
Graduate capabilities & intended learning outcomes
01. Demonstrate an understanding of data types and research designs that are applicable to sports and exercise science.
- Activities:
- Workshops, Online learning modules, Lectures
02. Apply data handling techniques to correctly treat and process data to provide a range of descriptive statistical outcomes.
- Activities:
- Workshops, Online learning modules, Lectures
03. Select, apply and interpret various statistical tests to provide evidence-based recommendations.
- Activities:
- Workshops, Online learning modules, Lectures
04. Critically appraise statistical designs and research literature within sports and exercise science.
- Activities:
- Workshops, Online learning modules, Lectures
05. Apply a range of data visualization techniques to demonstrate meaningful outcomes.
- Activities:
- Workshops, Online learning modules, Lectures
Melbourne, 2019, Semester 1, Blended
Overview
Online enrolment: Yes
Maximum enrolment size: N/A
Enrolment information:
Subject Instance Co-ordinator: Andrew Govus
Class requirements
LectureWeek: 10 - 22
One 2.0 hours lecture per week on weekdays during the day from week 10 to week 22 and delivered via blended.
TutorialWeek: 10 - 22
One 2.0 hours tutorial per week on weekdays during the day from week 10 to week 22 and delivered via face-to-face.
Assessments
| Assessment element | Comments | % | ILO* |
|---|---|---|---|
| 5 x Online Quizzes - 10 questions each (750 words total) | 20 | 01, 04 | |
| Tutorial Workbook (1500 words) | 40 | 01, 02, 03, 05 | |
| Assignment (equivalent to 1500 words) | 40 | 01, 02, 03, 04, 05 |