Part A: Course Overview
Course Title: Biostatistics
Credit Points: 12.00
Terms
Course Code |
Campus |
Career |
School |
Learning Mode |
Teaching Period(s) |
MATH2456 |
Bundoora Campus |
Undergraduate |
171H School of Science |
Face-to-Face |
Sem 2 2024 |
Course Coordinator: Dr Alice Johnstone
Course Coordinator Phone: +61 3 9925 2683
Course Coordinator Email: alice.johnstone@rmit.edu.au
Course Coordinator Location: 15.03.012
Course Coordinator Availability: By Appointment
Pre-requisite Courses and Assumed Knowledge and Capabilities
None.
Course Description
This course will introduce you to the foundations and application of statistics in biological, medical and epidemiological fields. The course will begin with an introduction to summary statistics, data visualisation and probability as a measure for uncertainty. The course will then build upon these topics by introducing statistical data investigations, sampling, sampling distributions and confidence intervals as the basis for statistical inference. The course will finish with a series of modules looking at common hypothesis testing methods for different types of data. The course emphasises conceptual understanding, interpretation of statistical output and the use of statistical software packages for statistical computation.
Please note that if you take this course for a Bachelor Honours program, your overall mark in this course will be one of the course marks that will be used to calculate the weighted average mark (WAM) that will determine your award level. (This applies to students who commence enrolment in a Bachelor Honours program from 1 January 2016 onwards. See the WAM information web page for more information.)
The WAM web page link: https://www.rmit.edu.au/students/my-course/assessment-results/results-grades/wam
Objectives/Learning Outcomes/Capability Development
This course contributes to the program learning outcomes for the following programs:
Bachelor of Laboratory Medicine (Honours)
PLO1 Apply coherent and advanced laboratory medicine theories, concepts and evidence in various real-world settings using a scientific approach.
PLO2 Apply systematic thinking and a range of advanced analytical and technical skills using a blend of digital and traditional methods, tools and technologies to solve complex scientific and medical problems.
PLO3 Apply research principles and methodology to design and implement a laboratory medicine research project to address complex real-world scientific challenges, and make original contribution to disciplinary knowledge.
PLO5 Communicate and collaborate with diverse audiences utilising contemporary and traditional formats employing inclusivity, integrity, judgement, adaptability and culturally safe practices related to laboratory medicine.
PLO6 Demonstrate responsibility, accountability and autonomy for own learning and professional practice as part of a multidisciplinary team.
PLO7 Apply and demonstrate the cultural intelligence and safety to practice, with consideration of the experience and perspectives of First Nations peoples and the global community in all aspects of work.
On completion of this course you should be able to:
- Identify and pose statistical questions requiring investigation through the application of an appropriate statistical design in the biosciences and related fields.
- Apply fundamental biostatistical methods to explore, summarise and visualise data, and test statistical hypotheses to enable reproducible analysis
- Interpret biostatistical analyses and draw conclusions in context and in the presence of uncertainty.
- Communicate statistical concepts and analyses results clearly and effectively as an individual and in teams.
Overview of Learning Activities
This course is delivered face to face and supported online through the learning management system (Canvas). This will give you access to course information, communication tools, online notes and assessment activities. The course is delivered through lectorials and practical classes. Completion of the regular module submissions, summative assessments and a major course project will help you develop and assess your understanding. The course modules emphasise conceptual understanding and the use of technology for statistical computation.
You are encouraged to be proactive and self-directed in your learning, asking questions of your lecturer and/or peers and seeking out information as required, especially from the numerous sources available through the RMIT library, and through links and material specific to this course that is available through myRMIT Studies, the Canvas website.
Overview of Learning Resources
RMIT will provide you with resources and tools for learning in this course through myRMIT Studies Course.
There are services available to support your learning through the University Library. The Library provides guides on academic referencing and subject specialist help as well as a range of study support services. For further information, please visit the Library page on the RMIT University website and the myRMIT student portal.
Overview of Assessment
Assessment Tasks
Assessment Task 1: Module Assignments (11)
Weighting 20%
This assessment task supports CLOs 1, 2 & 3
Assessment Task 2: Invigilated Assessments (2)
Weighting 40%
This assessment task supports CLOs 1, 2 & 3
Assessment Task 3: Project
Weighting 40%
This assessment task supports CLOs 1, 2, 3, & 4
If you have a long-term medical condition and/or disability it may be possible to negotiate to vary aspects of the learning or assessment methods. You can contact the program coordinator or Equitable Learning Services if you would like to find out more.