Unit convenor and teaching staff |
Unit convenor and teaching staff
Nino Kordzakhia
TBA
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Credit points |
Credit points
10
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Prerequisites |
Prerequisites
Admission to MBiotech or GradDipBioTech or MBiotechMCom or MConsBiol or GradDipConsBiol or GradDipResFSE or GradCertResFSE
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Corequisites |
Corequisites
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Co-badged status |
Co-badged status
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Unit description |
Unit description
This unit introduces the statistical and probabilistic concepts that are the basis for the study of bioinformatics. Topics include an introduction to probability and conditional probability, probability distributions, sampling distributions and an introduction to Markov processes. Particular attention is paid to how they relate to specific applications in the field of bioinformatics. A basic understanding of calculus will be an advantage. Learning in this unit enhances student understanding of global challenges identified by the United Nations Sustainable Development Goals (UNSDGs) Good Health and Well Being; Industry, Innovation and Infrastructure |
Information about important academic dates including deadlines for withdrawing from units are available at https://www.mq.edu.au/study/calendar-of-dates
On successful completion of this unit, you will be able to:
Achieve a total mark equal to or greater than 50% across all assessments.
We strongly encourage students to actively participate in all learning activities. Regular engagement is crucial for your success in this unit, as these activities provide opportunities to
- enhance your understanding of the material
- collaborate with peers
- and receive valuable feedback from instructors
to assist in completing the unit assessments.
Your active participation is essential for the successful completion of the unit.
Unless a Special Consideration request has been submitted and approved, a 5% penalty (of the total possible mark of the task) will be applied for each day a written report or presentation assessment is not submitted, up until the 7th day (including weekends).
After the 7th day, a grade of ‘0’ will be awarded even if the assessment is submitted.
The submission time for all uploaded assessments is 11:55 pm.
A 1-hour grace period will be provided to students who experience a technical concern.
For any late submission of time-sensitive tasks, such as scheduled tests/exams, performance assessments/presentations, and/or scheduled practical assessments/labs, please apply for Special Consideration.
Assignments - YES, Standard Late Penalty applies
Test - NO, unless Special Consideration is Granted
Practical Test - NO, unless Special Consideration is Granted
The Special Consideration Policy aims to support students who have been impacted by short-term circumstances or events that are serious, unavoidable and significantly disruptive, and which may affect their performance in assessment. If you experience circumstances or events that affect your ability to complete the assessments in this unit on time, please inform the convenor and submit a Special Consideration request through https://connect.mq.edu.au.
Name | Weighting | Hurdle | Due |
---|---|---|---|
Assignment | 25% | No | Week 4 |
Test | 25% | No | Week 9 |
Practical test | 50% | No | Week 12 |
Assessment Type 1: Quantitative analysis task
Indicative Time on Task 2: 18 hours
Due: Week 4
Weighting: 25%
Reinforce and apply skills learned in computer labs through data analysis.
Assessment Type 1: Quiz/Test
Indicative Time on Task 2: 18 hours
Due: Week 9
Weighting: 25%
This is a paper based mid-semester test. Further information will be provided in the iLearn site of the unit.
Assessment Type 1: Quantitative analysis task
Indicative Time on Task 2: 24 hours
Due: Week 12
Weighting: 50%
The task is designed to examine data analysis and R output interpretation skills taught in the unit.
1 If you need help with your assignment, please contact:
2 Indicative time-on-task is an estimate of the time required for completion of the assessment task and is subject to individual variation
Week 1 classes
Week 2-12 classes
iLearn
All unit-related materials including lecture notes, SGTA's, and instructions for assessment tasks and administrative updates, will be published on iLearn.
The statistical software R will be used. This is a free software environment for statistical computing and graphics and can be downloaded from the website
There is no required textbook for this unit.
Recommended reference sources:
We will communicate with you via your university email and through announcements on iLearn
Enquiries to the unit convenor can be sent via the contact email on iLearn or through your university email account.
Students can access the iLearn page by logging on at https://ilearn.mq.edu.au. Students must log in regularly to read the Announcements and access the teaching material.
StudyWeeks |
Lecture Topics |
W1 |
Introduction |
W2 |
Discrete random variables and their characteristics |
W3 - W5 |
Hardy-Weinberg Equilibrium (HWE);
Departures from HWE; Statistical testing of HWE. |
W6 - W7 |
HWE for X-linked loci. Introduction to continuous random variables: Uniform Distribution. |
Recess |
|
W8 |
Continuous random variables |
W9 - W10 |
Hypothesis testing and its applications |
W11 |
Markov Chains and their applications |
W12 |
Practical Test |
Macquarie University policies and procedures are accessible from Policy Central (https://policies.mq.edu.au). Students should be aware of the following policies in particular with regard to Learning and Teaching:
Students seeking more policy resources can visit Student Policies (https://students.mq.edu.au/support/study/policies). It is your one-stop-shop for the key policies you need to know about throughout your undergraduate student journey.
To find other policies relating to Teaching and Learning, visit Policy Central (https://policies.mq.edu.au) and use the search tool.
Macquarie University students have a responsibility to be familiar with the Student Code of Conduct: https://students.mq.edu.au/admin/other-resources/student-conduct
Results published on platform other than eStudent, (eg. iLearn, Coursera etc.) or released directly by your Unit Convenor, are not confirmed as they are subject to final approval by the University. Once approved, final results will be sent to your student email address and will be made available in eStudent. For more information visit connect.mq.edu.au or if you are a Global MBA student contact globalmba.support@mq.edu.au
At Macquarie, we believe academic integrity – honesty, respect, trust, responsibility, fairness and courage – is at the core of learning, teaching and research. We recognise that meeting the expectations required to complete your assessments can be challenging. So, we offer you a range of resources and services to help you reach your potential, including free online writing and maths support, academic skills development and wellbeing consultations.
Macquarie University provides a range of support services for students. For details, visit http://students.mq.edu.au/support/
The Writing Centre provides resources to develop your English language proficiency, academic writing, and communication skills.
The Library provides online and face to face support to help you find and use relevant information resources.
Macquarie University offers a range of Student Support Services including:
Got a question? Ask us via the Service Connect Portal, or contact Service Connect.
For help with University computer systems and technology, visit http://www.mq.edu.au/about_us/offices_and_units/information_technology/help/.
When using the University's IT, you must adhere to the Acceptable Use of IT Resources Policy. The policy applies to all who connect to the MQ network including students.
To enable students more time to focus on learning, understanding, and reflecting on the content of the unit we have revised the assessment structure as follows.
There are now only three assessments: one assignment, a mid-session test, and a practical test.
The activities in the unit are designed to enhance your understanding of the content and support the completion of assessments.
Unit information based on version 2025.04 of the Handbook