HSH746 - Biostatistics 1
Unit details
| 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 1: Burwood (Melbourne), CBD*, Cloud (online) |
| Credit point(s): | 1 |
| EFTSL value: | 0.125 |
| Unit Chair: | Trimester 1: Julie Abimanyi-Ochom Trimester 3: Lan Gao |
| Prerequisite: | Nil |
| 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: | Online independent and collaborative learning including 1 x 2 hours face to face or online computer practical each week |
| Scheduled learning activities - cloud: | Online independent and collaborative learning including 1 x 2 hour online computer practical each week |
Note:*CBD refers to the National Indigenous Knowledges, Education, Research and Innovation (NIKERI) Institute; Community Based Delivery | |
Content
In this introductory unit on biostatistics, students will explore the philosophical basis of statistical thought, examine fundamental statistical concepts and methods and explore their application in a variety of health settings. The delivery of the Unit is designed to facilitate the syntheses of the basic components of learning through practical exercises, statistical computing labs and the application of biostatistical techniques to realistic health-related data. The main topic areas covered will include: descriptive statistics, hypothesis testing, confidence intervals, comparison of means, inference on proportions, contingency tables, correlation and basic regression concepts.
| 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 the basic data types and summarise them. | GLO1: Discipline-specific knowledge and capabilities |
| ULO2 | Critique basic sample designs. | GLO1: Discipline-specific knowledge and capabilities |
| ULO3 | Apply basic statistical analysis techniques using statistical software and interpret the results. | GLO1: Discipline-specific knowledge and capabilities |
| ULO4 | Calculate and interpret confidence intervals. | GLO1: Discipline-specific knowledge and capabilities |
| ULO5 | Apply regression techniques to study the association between variables. | GLO1: Discipline-specific knowledge and capabilities |
| ULO6 | Conduct a statistical analysis which integrates different statistical techniques and interpret the results. | GLO1: Discipline-specific knowledge and capabilities |
Assessment
Trimester 1 and Trimester 3:| Assessment description | Student output | Grading and weighting (% total mark for unit) | Indicative due week |
|---|---|---|---|
| Assessment 1: Data manipulation and analysis | Equivalent to 1000 words | 20% |
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| Assessment 2: Data manipulation, analysis and interpretation | Equivalent to 1500 words | 30% |
|
| Assessment 3: Examination | 2 hours | 50% |
|
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.
Unit Fee Information
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