BIOSTATISTICS

STA2BS

2021

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.

SchoolEngineering and Mathematical Sciences

Credit points15

Subject Co-ordinatorHien Nguyen

Available to Study Abroad/Exchange StudentsYes

Subject year levelYear Level 2 - UG

Available as ElectiveNo

Learning ActivitiesN/A

Capstone subjectNo

Subject particulars

Subject rules

PrerequisitesSTA2AMS OR STA2ASM OR STM2PM OR STA2ABS

Co-requisitesN/A

Incompatible subjectsSTA3BS

Equivalent subjectsN/A

Quota Management StrategyN/A

Quota-conditions or rulesN/A

Special conditionsN/A

Minimum credit point requirementN/A

Assumed knowledgeN/A

Readings

Biostatistics with R, Springer

Resource TypeRecommended

Resource RequirementN/A

AuthorShahbaba, B

Year2012

Edition/VolumeN/A

PublisherAVAILABLE ONLINE IN LA TROBE EBL EBOOK LIBRARY

ISBNN/A

Chapter/article titleN/A

Chapter/issueN/A

URLN/A

Other descriptionN/A

Source locationN/A

Online learning materials (readings and examples)

Resource TypePrescribed

Resource RequirementN/A

AuthorOlenko, A.

Year2018

Edition/VolumeN/A

PublisherLa Trobe university, LMS

ISBNN/A

Chapter/article titleN/A

Chapter/issueN/A

URLN/A

Other descriptionN/A

Source locationN/A

Introduction to Linear Regression Analysis

Resource TypeRecommended

Resource RequirementN/A

AuthorMontgomery, D.C, Peck, E.A and Vining, G

YearN/A

Edition/VolumeN/A

PublisherWILEY, 4TH EDITION. AVAILABLE ONLINE IN LA TROBE 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.

Subject options

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Start date between: and    Key dates

Melbourne (Bundoora), 2021, Semester 2, Day

Overview

Online enrolmentYes

Maximum enrolment sizeN/A

Subject Instance Co-ordinatorHien Nguyen

Class requirements

LectureWeek: 30 - 42
One 2.00 h lecture per week on weekdays during the day from week 30 to week 42 and delivered via face-to-face.

PracticalWeek: 30 - 42
One 2.00 h practical per week on weekdays during the day from week 30 to week 42 and delivered via face-to-face.

Assessments

Assessment elementCommentsCategoryContributionHurdle% ILO*

10 Assignments (150 word equiv each)

N/AN/AN/ANo30 SILO1, SILO2, SILO3, SILO4

3-hour short answer Final Examination (3000 words equivalent)

N/AN/AN/ANo70 SILO1, SILO2, SILO3, SILO4