BIOSTATISTICS

STA3BS

2015

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

SchoolSchool Engineering&Mathematical Sciences

Credit points15

Subject Co-ordinatorAndriy Olenko

Available to Study Abroad StudentsYes

Subject year levelYear Level 3 - UG

Exchange StudentsYes

Subject particulars

Subject rules

Prerequisites one of STA2ABS, STA2AMS, STA2MD, STM2PM

Co-requisitesN/A

Incompatible subjects AGR41EXP, AGR4AED, STA2BS

Equivalent subjectsN/A

Special conditionsN/A

Readings

Resource TypeTitleResource RequirementAuthor and YearPublisher
ReadingsBiostatistics with RRecommendedShahbaba, Babak 2012SPRINGER, AVAILABLE ONLINE IN LATROBE EBL EBOOK LIBRARY
ReadingsIntroduction to Linear Regression AnalysisRecommendedMontgomery, DC, Peck, EA and Vining, G 2006WILEY, 4TH EDITION. AVAILABLE ONLINE IN LATROBE EBL EBOOK LIBRARY

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.

Activities:
Weekly problem classes involve theoretical derivations of results introduced in lectures. 10 almost weekly assignments consist mainly of theoretical derivations. The second hour of the problem class allows for students to work through the assignment questions with guidance from the lecturer and fellow students.
Related graduate capabilities and elements:
Writing (Writing)
Quantitative Literacy/ Numeracy (Quantitative Literacy/ Numeracy)
Creative Problem-solving (Creative Problem-solving)
Discipline-specific GCs (Discipline-specific GCs)

02. Formulate appropriate hypotheses and experimental designs.

Activities:
Formulation of hypotheses is discussed and modelled via example in lectures. Experimental design concepts are discussed in lectures and weekly problem classes involve derivation of key theoretical and applied components to design of experiments. Assignments earlier in the semester largely involve hypothesis testing. Assignments later in the subject involve a mixture of hypothesis testing and experimental design. The second hour of the problem class allows for students to work through the assignment questions with guidance from the lecturer and fellow students.
Related graduate capabilities and elements:
Quantitative Literacy/ Numeracy (Quantitative Literacy/ Numeracy)
Discipline-specific GCs (Discipline-specific GCs)
Critical Thinking (Critical Thinking)
Writing (Writing)
Inquiry/ Research (Inquiry/ Research)

03. Utilize randomization and blocking appropriately in the design of statistical experiments.

Activities:
Randomization is a key component to much of the theory throughout the entire subject and is modelled/discussed in lectures and implemented by the students in weekly problems under guidance from the lecturer. Similarly, blocking is considered in weeks 3-6. Assignments consist mainly of theoretical derivations. The second hour of the problem class allows for students to work through the assignment questions with guidance from the lecturer and fellow students.
Related graduate capabilities and elements:
Quantitative Literacy/ Numeracy (Quantitative Literacy/ Numeracy)
Creative Problem-solving (Creative Problem-solving)
Discipline-specific GCs (Discipline-specific GCs)
Inquiry/ Research (Inquiry/ Research)

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.

Activities:
Introduced in lectures in weeks 10, 11 and 12. Key applications of theoretical results are shown during the problem classes of these weeks. Assignments 9 and 10 involve the student designing/recognising factorial and fractional factorial designs. The second hour of the problem class allows for students to work through the assignment questions with guidance from the lecturer and fellow students.
Related graduate capabilities and elements:
Quantitative Literacy/ Numeracy (Quantitative Literacy/ Numeracy)
Inquiry/ Research (Inquiry/ Research)
Creative Problem-solving (Creative Problem-solving)
Discipline-specific GCs (Discipline-specific GCs)

Subject options

Select to view your study options…

Start date between: and    Key dates

Melbourne, 2015, Semester 2, Day

Overview

Online enrolmentYes

Maximum enrolment sizeN/A

Enrolment information

Subject Instance Co-ordinatorAndriy Olenko

Class requirements

Lecture Week: 31 - 43
Two 1.0 hours lecture per week on weekdays during the day from week 31 to week 43 and delivered via face-to-face.

Practical Week: 31 - 43
One 2.0 hours practical per week on weekdays during the day from week 31 to week 43 and delivered via face-to-face.

Assessments

Assessment elementComments% ILO*
10 Assignments (approx. 200 words each)30 01, 02, 03, 04
3-hour short answer Final Examination70 01, 02, 03, 04