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.

SchoolSchool Allied Health,Human Serv & Sport

Credit points15

Subject Co-ordinatorAndrew Govus

Available to Study Abroad StudentsYes

Subject year levelYear Level 2 - UG

Exchange StudentsYes

Subject particulars

Subject rules

Prerequisites HLT1RAE

Co-requisitesN/A

Incompatible subjectsN/A

Equivalent subjectsN/A

Special conditionsN/A

Readings

Resource TypeTitleResource RequirementAuthor and YearPublisher
ReadingsStatistics for sports and exercise science: a practical approachPrescribedNewell, 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

Subject options

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Start date between: and    Key dates

Melbourne, 2019, Semester 1, Blended

Overview

Online enrolmentYes

Maximum enrolment sizeN/A

Enrolment information

Subject Instance Co-ordinatorAndrew Govus

Class requirements

Lecture Week: 10 - 22
One 2.0 hours lecture per week on weekdays during the day from week 10 to week 22 and delivered via blended.

Tutorial Week: 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 elementComments% 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