Credit points: 15

Subject outline

Quantitative Research Methods is concerned with the scientific method, the statistical design and analysis of studies in life sciences, and the critical evaluation of scientific literature. Students will learn how scientists discover causal relationships that explain how the natural world operates. Building upon the foundations learnt in STA1CTS Critical Thinking with Statistics, STA1LS Statistics for Life Sciences, or BIO2POS Practice of Science the subject covers the principles of statistical design for surveys, experiments, and observational studies; some new methods for analysing data, including analysis of variance (ANOVA), multiple regression, analysis of covariance (ANCOVA), and some nonparametric methods that are particularly suited to analysing multispecies ecological data; and how to critically evaluate the statistical arguments made in scientific reports and journal articles. Laboratory sessions and assignments will give students the opportunity to apply what they learn using the statistics packages SPSS and PRIMER.

SchoolLife Sciences

Credit points15

Subject Co-ordinatorPete Green

Available to Study Abroad/Exchange StudentsYes

Subject year levelYear Level 3 - UG

Available as ElectiveNo

Learning ActivitiesN/A

Capstone subjectNo

Subject particulars

Subject rules



Incompatible subjectsWEM2QRM

Equivalent subjectsN/A

Quota Management StrategyN/A

Quota-conditions or rulesN/A

Special conditionsN/A

Minimum credit point requirementN/A

Assumed knowledgeN/A

Learning resources

Statistics explained: An introductory guide for life scientists

Resource TypeBook

Resource RequirementRecommended

AuthorMcKillup, S.





Chapter/article titleN/A



Other descriptionN/A

Source locationN/A

Career Ready


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. Design a sample survey, experiment and observational study
02. Choose an appropriate analysis for a given research question and data set
03. Perform data analyses using SPSS and PRIMER statistics packages, interpret the results, and draw conclusions
04. Communicate statistical analyses in report form
05. Evaluate statistics reported in the media and scientific journal articles

Subject options

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Start date between: and    Key dates

Melbourne (Bundoora), 2021, Semester 1, Blended


Online enrolmentYes

Maximum enrolment sizeN/A

Subject Instance Co-ordinatorPete Green

Class requirements

Computer LaboratoryWeek: 10 - 22
One 3.00 hours computer laboratory per week on weekdays during the day from week 10 to week 22 and delivered via face-to-face.
Incorporates a 1 hr online workshop with lecturer via Collaborate. Tutor will be in attendance face to face and lecturer will attend via Collaborate.


Assessment elementCommentsCategoryContributionHurdle% ILO*

Assignment 1: Study Design (750 words) Assignment 2: Data Analysis & Critical Thinking (750 words)
Assignment 1 is due in week 5, and Assignment 2 is due in week 12.

N/AAssignmentIndividualNo40 SILO1, SILO2, SILO3, SILO4, SILO5

2 hour final exam (open book)

N/ACentral examIndividualNo40 SILO1, SILO2, SILO3, SILO4

Ten (10) online quizzes with 5-10 multiple choice questions on each quiz. (750 word equiv)
Due weekly.

N/AQuizzesIndividualNo20 SILO1, SILO2, SILO3, SILO4, SILO5