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.

School: Engineering and Mathematical Sciences (Pre 2022)

Credit points: 15

Subject Co-ordinator: Andriy Olenko

Available to Study Abroad/Exchange Students: Yes

Subject year level: Year Level 3 - UG

Available as Elective: No

Learning Activities: N/A

Capstone subject: No

Subject particulars

Subject rules

Prerequisites: STA2MD OR STA2AMS OR STA2ABS OR STM2PM

Co-requisites: N/A

Incompatible subjects: STA2BS

Equivalent subjects: N/A

Quota Management Strategy: N/A

Quota-conditions or rules: N/A

Special conditions: N/A

Minimum credit point requirement: N/A

Assumed knowledge: N/A

Learning resources

Introduction to Linear Regression Analysis

Resource Type: Book

Resource Requirement: Recommended

Author: Montgomery, DC, Peck, EA and Vining, G

Year: 2006

Edition/Volume: N/A

Publisher: WILEY, 4TH EDITION. AVAILABLE ONLINE IN LATROBE EBL EBOOK LIBRARY

ISBN: N/A

Chapter/article title: N/A

Chapter/issue: N/A

URL: N/A

Other description: N/A

Source location: N/A

Biostatistics with R

Resource Type: Book

Resource Requirement: Recommended

Author: Shahbaba, Babak

Year: 2012

Edition/Volume: N/A

Publisher: SPRINGER, AVAILABLE ONLINE IN LATROBE EBL EBOOK LIBRARY

ISBN: N/A

Chapter/article title: N/A

Chapter/issue: N/A

URL: N/A

Other description: N/A

Source location: N/A

Career Ready

Career-focused: No

Work-based learning: No

Self sourced or Uni sourced: N/A

Entire subject or partial subject: N/A

Total hours/days required: N/A

Location of WBL activity (region): N/A

WBL addtional requirements: N/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 not currently offered - Subject options not available.