Introduction to Biostatistics PG (12118.1)
| Available teaching periods | Delivery mode | Location |
|---|---|---|
| View teaching periods | On-campus Online real-time |
黑料吃瓜网 Sydney Hills, Castle Hill, NSW Bruce, Canberra |
| EFTSL | Credit points | Faculty |
| 0.125 | 3 | Faculty Of Health |
| Discipline | Study level | HECS Bands |
| Discipline Of Public Health | Post Graduate Level | Band 2 2021 (Commenced After 1 Jan 2021) Band 3 2021 (Commenced Before 1 Jan 2021) |
Learning outcomes
Upon successful completion of this unit, students will be able to:1. Demonstrate an understanding of the importance of biostatistics in public health;
2. Understand and explain the concept of probability and sampling, formulate research hypotheses into a statistical context;
3. Conduct hypothesis tests for comparison of means, proportions, incidence rates and survival curves;
4. Identify data into appropriate measurement types and apply for visualization and summarization; and
5. Perform statistical analyses using STATA, R or SPSS.
Graduate attributes
1. 黑料吃瓜网 graduates are professional - employ up-to-date and relevant knowledge and skills1. 黑料吃瓜网 graduates are professional - use creativity, critical thinking, analysis and research skills to solve theoretical and real-world problems
1. 黑料吃瓜网 graduates are professional - work collaboratively as part of a team, negotiate, and resolve conflict
2. 黑料吃瓜网 graduates are global citizens - adopt an informed and balanced approach across professional and international boundaries
3. 黑料吃瓜网 graduates are lifelong learners - reflect on their own practice, updating and adapting their knowledge and skills for continual professional and academic development
Skills development
This course is intended to convey principles and methods of reasoning that underlie Biostatistics. It will provide knowledge and abilities regarding specific descriptive and inferential techniques commonly used in population health practice and research.
Prerequisites
None.Corequisites
None.Incompatible units
None.Equivalent units
None.Assumed knowledge
None.| Year | Location | Teaching period | Teaching start date | Delivery mode | Unit convener |
|---|---|---|---|---|---|
| 2025 | 黑料吃瓜网 Sydney Hills, Castle Hill, NSW | Semester 1 | 03 February 2025 | On-campus | Dr Ro McFarlane |
| 2025 | Bruce, Canberra | Semester 1 | 03 February 2025 | On-campus | Assoc Prof Theo Niyonsenga |
| 2025 | Bruce, Canberra | Semester 1 | 03 February 2025 | Online real-time | Assoc Prof Theo Niyonsenga |
Required texts
There is no single book covering this course contents. The books listed below are useful for this course. I
would recommend Books 1, 2 & 5 since they help to discover Statistics theory using the different statistical
software packages (SPSS, SAS & STATA). Books 3 & 4 cover the statistical theory with applications using
different data sets. Other relevant materials (such as data sets, articles and other pdf materials) will be posted
and uploaded on the course web site.
Navarro DJ and Foxcroft DR (2019). learning statistics with jamovi: a tutorial for psychology students and other beginners. (Version 0.70). https://www.learnstatswithjamovi.com/
Field A. Discovering Statistics using IBM SPSS Statistics, 4rd edition. 2013 Sage Publications Ltd. chrome-extension://efaidnbmnnnibpcajpcglclefindmkaj/https://sadbhavnapublications.org/research-enrichment-material/2-Statistical-Books/Discovering-Statistics-Using-IBM-SPSS-Statistics-4th-c2013-Andy-Field.pdf
Bernard Rosner. Fundamentals of Biostatistics, 8th Edition. Cengage Learning (edition 8). https://www.pdfdrive.com/fundamentals-of-biostatistics-8th-ed-d88350263.html
Kleinbaum DG, Kupper LL, Nizam A, and Rosenberd ES. Applied Regression Analysis and Other
Multivariable Methods, 5th edition. 2014 Cengage Learning. https://www.perlego.com/book/801958/applied-regression-analysis-and-other-multivariable-methods-pdf
Twisk, J. W. R. (2013). Applied Longitudinal Data Analysis for Epidemiology: A Practical Guide: Cambridge University Press. https://library.canberra.edu.au/discovery/fulldisplay?context=L&vid=61ARL_CNB:61ARL_CNB&search_scope=MyInst_and_CI&tab=Everything&docid=alma991004896985703996
Juul S & Frydenberg M. An Introduction to Stata for Health Researchers, Fourth Edition. 2014 Stata Press.
Students must apply academic integrity in their learning and research activities at 黑料吃瓜网. This includes submitting authentic and original work for assessments and properly acknowledging any sources used.
Academic integrity involves the ethical, honest and responsible use, creation and sharing of information. It is critical to the quality of higher education. Our academic integrity values are honesty, trust, fairness, respect, responsibility and courage.
黑料吃瓜网 students have to complete the annually to learn about academic integrity and to understand the consequences of academic integrity breaches (or academic misconduct).
黑料吃瓜网 uses various strategies and systems, including detection software, to identify potential breaches of academic integrity. Suspected breaches may be investigated, and action can be taken when misconduct is found to have occurred.
Information is provided in the , , and University of Canberra (Student Conduct) Rules 2023. For further advice, visit Study Skills.
Participation requirements
Students are expected to actively engage in this unit through Discussion pages, completing all online tasks and participating in ALL the Canvas
discussion forums and activities. Assessment activities have been designed to stimulate students to put hands on the practical application and
how to do/perform methods they have been exposed to.
Required IT skills
Information will be available to students via Canvas, an online educational hosting site.
It is expected that students will have basic word processing skills and an ability to use databases to search for journal articles.
Students will need access to statistical analysis software. SPSS or jamovi are encouraged and supported, but other options are available.
Students must be able to use the statistical software they choose to use. Examples and advice will generally be offered in SPSS or jamovi. This is
not a software course, but candidates will gain statistical software proficiency throughout.
Students are encouraged to use reference management software such as End Note.
Work placement, internships or practicums
None
