QUANTITATIVE RESEARCH METHODS IN HEALTH

PHE5QRM

2020

Credit points: 15

Subject outline

In this subject, students will learn biostatistical techniques and methods required to analyse and draw inferences from health data. Students will be introduced to a statistical software package and will learn how to use this to perform various statistical analyses. The subject covers the analysis of both continuous and categorical data commonly encountered in cross-sectional and cohort designs in public health. Students will be introduced to how to display and visualise data before going on to learn how to compare groups using-tests, ANOVA, and chi-squared tests, and how to test for relationships between two (or more) variables using correlation and linear and logistic regression. We will also look at how to calculate sample size and power estimates.

School: Psychology and Public Health (Pre 2022)

Credit points: 15

Subject Co-ordinator: Bircan Erbas

Available to Study Abroad/Exchange Students: Yes

Subject year level: Year Level 5 - Masters

Exchange Students: No

Available as Elective: No

Learning Activities: N/A

Capstone subject: No

Subject particulars

Subject rules

Prerequisites: Students enrolled in one of the following course codes HMPHC or HZPHID or HMG or HMHS or HMASCR or HZPHHA must pass all core first year subjects Students from all other courses must pass PHE5HDD or an equivalent

Co-requisites: N/A

Incompatible subjects: N/A

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

Essential Medical statistics

Resource Type: Book

Resource Requirement: Recommended

Author: Kirkwood and Sterne

Year: 2003

Edition/Volume: N/A

Publisher: Blackwell

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. Apply appropriate data exploration methods including descriptive data types, distributions, and graphical procedures to interpret statistical evidence and assess underlying assumptions.

02. Apply the correct statistical tests (ANOVA, ANCOVA, linear and logistic regression using Stata software package to address research questions.

03. Design ethical quantitative research projects using analytical approaches.

04. Critically appraise research evidence and methods.

City Campus, 2020, Semester 1, Blended

Overview

Online enrolment: Yes

Maximum enrolment size: N/A

Enrolment information: N/A

Subject Instance Co-ordinator: Bircan Erbas

Class requirements

Computer LaboratoryWeek: 10 - 22
One 3.00 hours computer laboratory every two weeks on weekdays during the day from week 10 to week 22 and delivered via face-to-face.
Additional curriculum delivered via LMS

Assessments

Assessment element	Comments	Category	Contribution	Hurdle	%	ILO*
Three Online quizzes (500-words equivalent, each - total 1,500-words equiv.)	N/A	N/A	N/A	No	30	SILO1, SILO2, SILO3, SILO4
Two written reports (750-words equivalent, each - total 1,500-words equiv.)	N/A	N/A	N/A	No	30	SILO1, SILO3, SILO4
Written data analysis assignment (2,000-words equiv.)	N/A	N/A	N/A	No	40	SILO1, SILO2

On-Line, 2020, Semester 1, Online