HSH216 - Epidemiology and Biostatistics 2

Unit details

Note: You are seeing the 2022 view of this unit information. These details may no longer be current. [Go to the current version]
Year:

2022 unit information

Important Update:

Unit delivery will be in line with the most current COVIDSafe health guidelines. We continue to tailor learning experiences for each unit to achieve the best possible mix of online and on-campus activities that successfully blend our approaches to learning, working and research. Please check your unit sites for announcements and updates.

Last updated: 4 March 2022

Enrolment modes:Trimester 2: Burwood (Melbourne), Waurn Ponds (Geelong), Online
Credit point(s):1
EFTSL value:0.125
Unit Chair:Trimester 2: Adrian Cameron
Prerequisite:

HSH205

Corequisite:

Nil

Incompatible with:

Nil

Typical study commitment:

Students will on average spend 150 hours over the teaching period undertaking the teaching, learning and assessment activities for this unit.

Scheduled learning activities - campus:

Computer laboratory sessions (seminars) will be held in person (unless advised otherwise), with one session recorded and uploaded to the unit site. Students are encouraged to attend computer practicals where they can receive direct assistance.

It is also possible to use SPSS statistical software online via Blackboard Collaborate and Apps on demand - details will be provided in week 1.

Practical laboratory classes (seminars) will be held weekly on Wednesdays at 12:00 and 14:00 (both in Burwood) and on Thursday at 11:00 (in Geelong).

Content

The purpose of this unit is to introduce students to the basic principles of biostatistics used in public health and health promotion practice. It builds on HSH205 Epidemiology and Biostatistics 1. The main topics covered include understanding, application and interpretation of fundamental biostatistical concepts. Students will also participate in computer practicals to develop their skills and knowledge as well as learn to use statistical software programs to conduct biostatistical analysis of data.

ULO These are the Learning Outcomes (ULO) for this unit. At the completion of this unit, successful students can: Deakin Graduate Learning Outcomes
ULO1 Describe fundamental biostatistical concepts.

GLO1: Discipline-specific knowledge and capabilities
GLO4: Critical thinking
GLO5: Problem solving

ULO2 Identify, differentiate, select and apply biostatistical concepts as appropriate.

GLO1: Discipline-specific knowledge and capabilities
GLO4: Critical thinking
GLO5: Problem solving

ULO3 Interpret the output of biostatistical tests. GLO1: Discipline-specific knowledge and capabilities
GLO2: Communication
GLO4: Critical thinking
GLO5: Problem solving
ULO4 Use statistical software programs to conduct biostatistical analysis of data.

GLO1: Discipline-specific knowledge and capabilities
GLO3: Digital literacy
GLO6: Self-management

Assessment

Trimester 2:

Assessment description

Student output

Grading and weighting
(% total mark for unit)

Indicative due week

Assessment 1: Assignment

1500 words

40%

  • Week 5

Assessment 2: Online MCQ test

 

20%

  • Information not yet available

Assessment 3: Assignment

1500 words

40%

  • Information not yet available

The assessment due weeks provided may change. The Unit Chair will clarify the exact assessment requirements, including the due date, at the start of the teaching period.

Learning Resource

The texts and reading list for the unit can be found on the University Library via the link below: HSH216 Note: Select the relevant trimester reading list. Please note that a future teaching period's reading list may not be available until a month prior to the start of that teaching period so you may wish to use the relevant trimester's prior year reading list as a guide only.

Recommended texts

Argyrous, G (2011) Statistics for research: With a guide to SPSS, 3rd edition. Sage Publications.

Cronk, BC (2018) How to Use SPSS®, A Step-By-Step Guide to Analysis and Interpretation, 10th Edition. Routledge.

Unit Fee Information

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