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HSH947 - Biostatistics 2

Year:	2024 unit information
Enrolment modes:	Trimester 2: Burwood (Melbourne), Online
Credit point(s):	0
EFTSL value:	0.000
Unit Chair:	Trimester 2: Eric Lau
Prerequisite:	HSH946
Corequisite:	Nil
Incompatible with:	HSH747
Educator-facilitated (scheduled) learning activities - on-campus unit enrolment:	All teaching material is online in the form of short narrated PowerPoints - with the students expected to view 4 to 6 each week. We will have one 2 hour on-campus practical experience (computer practical) each week to facilitate the practical exercises.
Educator-facilitated (scheduled) learning activities - online unit enrolment:	All teaching material is online in the form of short narrated PowerPoints - with the students expected to view 4 to 6 each week. Online independent and collaborative learning and 1 X 2 hour zoom based practical experience (computer practical) each week - scheduled for the online session to facilitate the practical exercises. Zoom recording will also be available.

Content

This unit will cover topics in regression analysis with a focus on practical application to data and problems in public health, health economics and variety of health settings. Topics include: linear regression, including model fitting, measures of goodness of fit and using regression to explore confounding and effect modification; logistic regression, extending regression to modelling proportions, rates and odds ratios and the analysis of case-control studies; and Poisson and other generalised linear models. Unit delivery is designed to facilitate the syntheses of the components of learning through practical exercises, statistical computing labs and the application of regression techniques to realistic health-related data. All content will be delivered online, with short narrated PowerPoints/videos providing the main content delivery supported by links to online resources and appropriate journal articles. Face-to-face sessions for on campus students will focus on applying the week’s content to real/realistic data. Detailed notes on these practical sessions will be posted on the unit site so that off campus students can work through the practical sessions at home. Weekly online sessions for off-campus students facilitated by the unit chair will allow them to workshop the online content and practical sessions. Practical work will use the Stata statistical analysis software.

ULO	These are the Learning Outcomes (ULO) for this unit. At the completion of this unit, successful students can:	Deakin Graduate Learning Outcomes
ULO1	Identify suitable regression models to analyse continuous data.	GLO1: Discipline-specific knowledge and capabilities GLO4: Critical thinking
ULO2	Fit regression models to continuous data using statistical software and interpret the results.	GLO1: Discipline-specific knowledge and capabilities GLO2: Communication GLO3: Digital literacy GLO4: Critical thinking GLO5: Problem solving
ULO3	Identify suitable regression models for count data, proportions, rates and odds ratios.	GLO1: Discipline-specific knowledge and capabilities GLO4: Critical thinking
ULO4	Fit regression models to count data, proportions, rates and odds ratios using statistical software and interpret the results.	GLO1: Discipline-specific knowledge and capabilities GLO2: Communication GLO3: Digital literacy GLO4: Critical thinking GLO5: Problem solving
ULO5	Apply regression techniques to assessing confounding and effect modification and to analyse case-control studies and interpret the results.	GLO1: Discipline-specific knowledge and capabilities GLO2: Communication GLO3: Digital literacy GLO4: Critical thinking GLO5: Problem solving
ULO6	Conduct a statistical analysis which integrates the different statistical techniques taught in this unit and interpret the results.	GLO1: Discipline-specific knowledge and capabilities GLO2: Communication GLO3: Digital literacy GLO4: Critical thinking GLO5: Problem solving GLO6: Self-management

Assessment

Trimester 2:

Assessment description	Student output	Grading and weighting (% total mark for unit)	Indicative due week
Assessment 1: Theoretical questions and applied analyses	Equivalent to 1000 words	20%	Week 5
Assessment 2: Theoretical questions and applied analyses	Equivalent to 1500 words	30%	Week 9
Assessment 3: Data analysis, reporting and interpretation	Equivalent to 2500 words	50%	End-of-unit assessment period

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

There is no prescribed text. Unit materials are provided via the unit site. This includes unit topic readings and references to further information.

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