sta2ams applied medical statistics
APPLIED MEDICAL STATISTICS
STA2AMS
2016
Credit points: 15
Subject outline
Building on the understanding of applied statistical methods developed in first year statistics subjects, STA2AMS provides an understanding of these methods at an intermediate level. In terms of content, STA2AMS is similar to STA2ABS, but the subject places a special emphasis on medical applications. There are specific questions in the assignments, project, test and examination that reflect such an emphasis. This subject does not require a knowledge of calculus. An introduction to the open source statistical computing package R is included.
SchoolSchool Engineering&Mathematical Sciences
Credit points15
Subject Co-ordinatorAgus Salim
Available to Study Abroad StudentsYes
Subject year levelYear Level 2 - UG
Exchange StudentsYes
Subject particulars
Subject rules
Prerequisites STA1PSY or STA1LS or STA1SS or ECO1ISB
Co-requisitesN/A
Incompatible subjects STA2AS, STA2MS, STA2RSP, STA2ABS
Equivalent subjectsN/A
Special conditionsN/A
Graduate capabilities & intended learning outcomes
01. Apply appropriate statistical and probabilistic methods for data analysis.
- Activities:
- Discussed and demonstrated in lectures and lecture/workshops. Related problems solved by students in practice classes. Assignment questions, with feedback.
- Related graduate capabilities and elements:
- Critical Thinking(Critical Thinking)
- Discipline-specific GCs(Discipline-specific GCs)
- Quantitative Literacy/ Numeracy(Quantitative Literacy/ Numeracy)
- Writing(Writing)
- Creative Problem-solving(Creative Problem-solving)
02. Discuss the importance of "thinking ahead" when planning and designing experiments.
- Activities:
- Discussed and demonstrated in lectures and lecture/workshops. Related problems solved by students in practice classes. Assignment questions, with feedback.
- Related graduate capabilities and elements:
- Writing(Writing)
- Critical Thinking(Critical Thinking)
- Discipline-specific GCs(Discipline-specific GCs)
- Inquiry/ Research(Inquiry/ Research)
03. Execute statistical software functionality for data analysis and interpret the output accurately and meaningfully.
- Activities:
- Some discussion in lectures and lecture/workshops. Related problems solved by students in computer laboratory classes. Computer laboratory project, with guidance and feedback.
- Related graduate capabilities and elements:
- Critical Thinking(Critical Thinking)
- Creative Problem-solving(Creative Problem-solving)
- Quantitative Literacy/ Numeracy(Quantitative Literacy/ Numeracy)
- Discipline-specific GCs(Discipline-specific GCs)
04. Assess the effectiveness of statistical methods using simulation.
- Activities:
- Some discussion in lectures and lecture/workshops. Related problems solved by students in computer laboratory classes. Computer laboratory project, with guidance and feedback.
- Related graduate capabilities and elements:
- Quantitative Literacy/ Numeracy(Quantitative Literacy/ Numeracy)
- Writing(Writing)
- Critical Thinking(Critical Thinking)
- Creative Problem-solving(Creative Problem-solving)
- Discipline-specific GCs(Discipline-specific GCs)
05. Explain the codes of conduct that govern professional competence and integrity in the field of statistics.
- Activities:
- Discussed and demonstrated in lectures and lecture/workshops.
- Related graduate capabilities and elements:
- Ethical Awareness(Ethical Awareness)
06. Formulate hypothesis testing related to medical problems; draw and explain the conclusions that follow from a rigorous and systematic analysis.
- Activities:
- Discussed and demonstrated in lectures and lecture/workshops. Related problems solved by students in practice classes. Assignment questions, with feedback.
- Related graduate capabilities and elements:
- Quantitative Literacy/ Numeracy(Quantitative Literacy/ Numeracy)
- Creative Problem-solving(Creative Problem-solving)
- Critical Thinking(Critical Thinking)
- Writing(Writing)
- Discipline-specific GCs(Discipline-specific GCs)
- Inquiry/ Research(Inquiry/ Research)
Subject options
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Melbourne, 2016, Semester 1, Day
Overview
Online enrolmentYes
Maximum enrolment sizeN/A
Enrolment information
Subject Instance Co-ordinatorAgus Salim
Class requirements
Lecture/WorkshopWeek: 10 - 22
One 1.0 hours lecture/workshop per week on weekdays during the day from week 10 to week 22 and delivered via face-to-face.
LectureWeek: 10 - 22
One 1.0 hours lecture per week on weekdays during the day from week 10 to week 22 and delivered via face-to-face.
Laboratory ClassWeek: 10 - 22
One 1.0 hours laboratory class per week on weekdays during the day from week 10 to week 22 and delivered via face-to-face.
Computer LaboratoryWeek: 10 - 22
One 1.0 hours computer laboratory per week on weekdays during the day from week 10 to week 22 and delivered via face-to-face.
Assessments
| Assessment element | Comments | % | ILO* |
|---|---|---|---|
| 2.5 hour exam | 55 | 01, 02, 05, 06 | |
| 45 minute in-class computer test | 15 | 03, 04 | |
| Computing project (equivalent to 600 words) | 10 | 03, 04 | |
| Four written assignments (equivalent to 1200 words) | 20 | 01, 02, 06 |