APPLIED STATISTICAL METHODS

STA2ASM

2021

Credit points: 15

Subject outline

Building on the understanding of applied statistical methods developed in first year statistics subjects, STA2ASM provides an understanding of these methods at an intermediate level. The subject places a special emphasis on applications of statistics to biological and medical problems. There are specific questions in the assignments, project, test and examination that reflect such an emphasis. This subject does not require a knowledge of calculus. An introduction to the open source statistical computing package R is included.

SchoolEngineering and Mathematical Sciences

Credit points15

Subject Co-ordinatorDavid Farchione

Available to Study Abroad/Exchange StudentsYes

Subject year levelYear Level 2 - UG

Available as ElectiveNo

Learning ActivitiesN/A

Capstone subjectNo

Subject particulars

Subject rules

PrerequisitesSTA1SS OR STA1LS OR STA1PSY

Co-requisitesN/A

Incompatible subjectsSTA2ABS OR STA2AMS OR STA2RSP OR STA2AS

Equivalent subjectsN/A

Quota Management StrategyN/A

Quota-conditions or rulesN/A

Special conditionsN/A

Minimum credit point requirementN/A

Assumed knowledgeN/A

Readings

Fundamentals of Biostatistics

Resource TypeRecommended

Resource RequirementN/A

AuthorRosner B

Year2016

Edition/Volume8th Ed

PublisherCENAGE

ISBNN/A

Chapter/article titleN/A

Chapter/issueN/A

URLN/A

Other descriptionN/A

Source locationN/A

Applied Statistical Methods

Resource TypePrescribed

Resource RequirementN/A

AuthorLuke Prendergast

Year2018

Edition/VolumeN/A

PublisherLa Trobe University

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

01. Apply appropriate statistical and probabilistic methods for data analysis.
02. Discuss the importance of "thinking ahead" when planning and designing experiments.
03. Execute statistical software functionality for data analysis and interpret the output accurately and meaningfully.
04. Assess the effectiveness of statistical methods using simulation.
05. Explain the codes of conduct that govern professional competence and integrity in the field of statistics.
06. Formulate hypothesis testing related to biological and medical problems; draw and explain the conclusions that follow from a rigorous and systematic analysis.

Subject options

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Start date between: and    Key dates

Melbourne (Bundoora), 2021, Semester 1, Day

Overview

Online enrolmentYes

Maximum enrolment sizeN/A

Subject Instance Co-ordinatorDavid Farchione

Class requirements

Computer LaboratoryWeek: 11 - 22
One 1.00 h computer laboratory per week on weekdays during the day from week 11 to week 22 and delivered via face-to-face.

LectureWeek: 10 - 22
One 1.00 h lecture per week on weekdays during the day from week 10 to week 22 and delivered via face-to-face.
Recorded on Echo

Lecture/WorkshopWeek: 10 - 22
One 1.00 h lecture/workshop per week on weekdays during the day from week 10 to week 22 and delivered via face-to-face.
Recorded on Echo

PracticalWeek: 11 - 22
One 1.00 h practical per week on weekdays during the day from week 11 to week 22 and delivered via face-to-face.

Assessments

Assessment elementCommentsCategoryContributionHurdle% ILO*
2 hour exam (equivalent to 2000 words)N/AN/AN/ANo55 SILO1, SILO2, SILO5, SILO6
Four written assignments (equivalent to 200 words each, 800 words total)N/AN/AN/ANo20 SILO1, SILO2, SILO6
In-class computer test (equivalent to 600 words)N/AN/AN/ANo15 SILO3, SILO4
Statistical computing project (equivalent to 400 words)N/AN/AN/ANo10 SILO3, SILO4