QUANTITATIVE RESEARCH METHODS

ENV3QRM

2020

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.

School: Life Sciences (Pre 2022)

Credit points: 15

Subject Co-ordinator: Warren Paul

Available to Study Abroad/Exchange Students: Yes

Subject year level: Year Level 3 - UG

Exchange Students: No

Available as Elective: No

Learning Activities: N/A

Capstone subject: No

Subject particulars

Subject rules

Prerequisites: BIO2POS OR STA1LS OR STA1CTS

Co-requisites: N/A

Incompatible subjects: WEM2QRM

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

Statistics explained: An introductory guide for life scientists

Resource Type: Book

Resource Requirement: Recommended

Author: McKillup, S.

Year: 2006

Edition/Volume: N/A

Publisher: CAMBRIDGE UNIVERSITY PRESS

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. 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

Melbourne (Bundoora), 2020, Semester 1, Blended

Overview

Online enrolment: Yes

Maximum enrolment size: N/A

Enrolment information: N/A

Subject Instance Co-ordinator: Warren Paul

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.

Assessments

Assessment element	Comments	Category	Contribution	Hurdle	%	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/A	N/A	N/A	No	40	SILO1, SILO2, SILO3, SILO4, SILO5
2 hour final exam (open book)	N/A	N/A	N/A	No	40	SILO1, SILO2, SILO3, SILO4
Ten (10) online quizzes with 5-10 multiple choice questions on each quiz. (750 word equiv)Due weekly.	N/A	N/A	N/A	No	20	SILO1, SILO2, SILO3, SILO4, SILO5