BIOSTATISTICS

STA3BS

Not currently offered

Credit points: 15

Subject outline

Students will learn to design and analyse experiments in the life sciences and agriculture. The topics covered in this subject include a brief review of non-parametric methods; randomisation, blocking and randomised block designs; one-way and two-way layouts; multiple comparison procedures; fixed and random effects; mixed models; multiple linear regression; analysis of covariance; factorial designs; fractional factorial designs; and an introduction to cluster analysis. This subject makes use of the freely available software package R. STA3BS is co-taught with STA2BS. For STA3BS there is greater emphasis on inquiry with an expectation that students independently analyse some of the subject data.

SchoolEngineering and Mathematical Sciences

Credit points15

Subject Co-ordinatorAndriy Olenko

Available to Study Abroad/Exchange StudentsYes

Subject year levelYear Level 3 - UG

Available as ElectiveNo

Learning ActivitiesN/A

Capstone subjectNo

Subject particulars

Subject rules

PrerequisitesSTA2MD OR STA2AMS OR STA2ABS OR STM2PM

Co-requisitesN/A

Incompatible subjectsSTA2BS

Equivalent subjectsN/A

Quota Management StrategyN/A

Quota-conditions or rulesN/A

Special conditionsN/A

Minimum credit point requirementN/A

Assumed knowledgeN/A

Readings

Introduction to Linear Regression Analysis

Resource TypeRecommended

Resource RequirementN/A

AuthorMontgomery, DC, Peck, EA and Vining, G

Year2006

Edition/VolumeN/A

PublisherWILEY, 4TH EDITION. AVAILABLE ONLINE IN LATROBE EBL EBOOK LIBRARY

ISBNN/A

Chapter/article titleN/A

Chapter/issueN/A

URLN/A

Other descriptionN/A

Source locationN/A

Biostatistics with R

Resource TypeRecommended

Resource RequirementN/A

AuthorShahbaba, Babak

Year2012

Edition/VolumeN/A

PublisherSPRINGER, AVAILABLE ONLINE IN LATROBE EBL EBOOK LIBRARY

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. Present clear, well structured and rigorous proofs of important fundamental linear model results. This includes appropriate use of statistical and mathematical vocabulary and notation.
02. Formulate appropriate hypotheses and experimental designs.
03. Utilise randomization and blocking appropriately in the design of statistical experiments.
04. Construct statistical experiments using factorial and fractional factorial designs with an emphasis on the construction of simple estimators of effects associated with two-level factors.
05. Research, model and analyse data using known underlying factors.

Subject options

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