spe2dss data science and statistics for sport
DATA SCIENCE AND STATISTICS FOR SPORT
SPE2DSS
2020
Credit points: 15
Subject outline
In this subject, you will explore research methods, statistical analysis and data science techniques specific to sport and exercise science. You will be taught various research designs and statistical approaches that will allow you to interpret data to apply results in a practical environment. The subject will teach you how to perform various data handling techniques, develop statistical models and data visualisation techniques to interpret data in sport and exercise context.
SchoolAllied Heath, Human Services & Sport
Credit points15
Subject Co-ordinatorMinh Huynh
Available to Study Abroad/Exchange StudentsYes
Subject year levelYear Level 2 - UG
Available as ElectiveNo
Learning ActivitiesN/A
Capstone subjectNo
Subject particulars
Subject rules
Prerequisites Students must be admitted in HBSES, HBESB or HZESPB and must have passed HLT1RAE All other enrolments require subject coordinator's approval
Co-requisitesN/A
Incompatible subjectsHLT2IEP
Equivalent subjectsN/A
Quota Management StrategyN/A
Quota-conditions or rulesN/A
Special conditionsN/A
Minimum credit point requirementN/A
Assumed knowledgeN/A
Learning resources
Statistics for sports and exercise science: a practical approach
Resource TypeBook
Resource RequirementPrescribed
AuthorNewell, J., Aitchison, T., & Grant, S.
Year2014
Edition/VolumeN/A
PublisherRoutledge
ISBNN/A
Chapter/article titleN/A
Chapter/issueN/A
URLN/A
Other descriptionN/A
Source locationN/A
Jamovi
Resource TypeWeb resource
Resource RequirementPrescribed
AuthorJamovi Project (Version 0.9)
YearN/A
Edition/VolumeN/A
PublisherJamovi
ISBNN/A
Chapter/article titleN/A
Chapter/issueN/A
URLN/A
Other descriptionN/A
Source locationN/A
Career Ready
Career-focusedNo
Work-based learningNo
Self sourced or Uni sourcedN/A
Entire subject or partial subjectN/A
Total hours/days requiredN/A
Location of WBL activity (region)N/A
WBL addtional requirementsN/A
Graduate capabilities & intended learning outcomes
Graduate Capabilities
Intended Learning Outcomes
Subject options
Select to view your study options…
Bendigo, 2020, Semester 1, Blended
Overview
Online enrolmentYes
Maximum enrolment sizeN/A
Subject Instance Co-ordinatorEmma Zadow
Class requirements
LectureWeek: 10 - 22
One 2.00 hours lecture per week on weekdays during the day from week 10 to week 22 and delivered via blended.
WorkShopWeek: 10 - 22
One 2.00 hours workshop per week on weekdays during the day from week 10 to week 22 and delivered via face-to-face.
Assessments
Assessment element | Category | Contribution | Hurdle | % | ILO* |
---|---|---|---|---|---|
Two 30 minute online tests (1,000 words equivalent) Two 30 min online short answer and multiple choice tests | N/A | N/A | No | 20 | SILO1, SILO2 |
Two written workshop data analysis activities (1,500 words equivalent) | N/A | N/A | No | 40 | SILO1, SILO2, SILO3, SILO5 |
One written data analysis inquiry project (1,500 words equivalent) | N/A | N/A | No | 40 | SILO1, SILO2, SILO3, SILO4, SILO5 |
Melbourne (Bundoora), 2020, Semester 1, Blended
Overview
Online enrolmentYes
Maximum enrolment sizeN/A
Subject Instance Co-ordinatorMinh Huynh
Class requirements
LectureWeek: 10 - 22
One 2.00 hours lecture per week on weekdays during the day from week 10 to week 22 and delivered via blended.
WorkShopWeek: 10 - 22
One 2.00 hours workshop per week on weekdays during the day from week 10 to week 22 and delivered via face-to-face.
Assessments
Assessment element | Category | Contribution | Hurdle | % | ILO* |
---|---|---|---|---|---|
Two 30 minute online tests (1,000 words equivalent) Two 30 min online short answer and multiple choice tests | N/A | N/A | No | 20 | SILO1, SILO2 |
Two written workshop data analysis activities (1,500 words equivalent) | N/A | N/A | No | 40 | SILO1, SILO2, SILO3, SILO5 |
One written data analysis inquiry project (1,500 words equivalent) | N/A | N/A | No | 40 | SILO1, SILO2, SILO3, SILO4, SILO5 |