Unit convenor and teaching staff |
Unit convenor and teaching staff
Unit Convenor/Lecturer
Nino Kordzakhia
Contact via Email
12WW 610
see iLearn
Thomas Fung
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Credit points |
Credit points
10
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Prerequisites |
Prerequisites
Admission to MBiotech or (MSc or MScInnovation) or GradDipBioTech or MBiotechMCom or MBioBus or MLabQAMgt or GradDipLabQAMgt or GradCertLabQAMgt or MConsBiol or GradDipConsBiol or MMarScMgt or GradDipMarScMgt or MRadiopharm
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Corequisites |
Corequisites
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Co-badged status |
Co-badged status
STAT7830
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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.
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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:
If there are circumstances, that mean you will miss an assessment you should apply for Special Consideration via ask.mq.edu.au
All assessment tasks must be submitted by the official due date and time.
Name | Weighting | Hurdle | Due |
---|---|---|---|
Assignment 1 | 10% | No | Week 4 |
Test | 30% | No | Week 8 |
Assignment 2 | 10% | No | Week 11 |
Practical Test | 50% | No | Week 12 |
Assessment Type 1: Quantitative analysis task
Indicative Time on Task 2: 28.5 hours
Due: Week 4
Weighting: 10%
Reinforce and apply skills learned in computer labs through data analysis. The tasks given during computer lab sessions are to be completed within the allocated time and submitted via iLearn.
Assessment Type 1: Quiz/Test
Indicative Time on Task 2: 1 hours
Due: Week 8
Weighting: 30%
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: 28.5 hours
Due: Week 11
Weighting: 10%
Reinforce and apply skills learned in computer labs through data analysis. The tasks given during computer lab sessions are to be completed within the allocated time and submitted via iLearn.
Assessment Type 1: Quiz/Test
Indicative Time on Task 2: 2 hours
Due: Week 12
Weighting: 50%
The practical test 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
Classes
Lectures begin in Week 1. SGTA begin in Week 2.
Students must attend two hours of lectures and two hours of SGTA per week. The lecture notes will be made available on iLearn before the lecture.
SGTA exercises will be set weekly and will be available on iLearn before each class.
The timetable for classes can be found at http://www.timetables.mq.edu.au
iLearn
All unit related materials including lecture notes, SGTA's and instructions for assessment tasks and administrative updates, will be published on iLearn at
https://ilearn.mq.edu.au/login/
Software
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
Texts and materials:
There is no required textbook for this unit.
Recommended reference sources:
Weeks |
Lecture Topics |
Due |
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W1 |
Introduction |
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W2 |
Discrete random variables and their characteristics |
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W3 - W5 |
Hardy-Weinberg Equilibrium (HWE); Departures from HWE; Statistical testing of HWE. |
Week 4 Assignment 1 |
W6 - W7 |
HWE for X-linked loci. Introduction to continuous random variables: Uniform Distribution. |
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MID-SESSION BREAK |
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W8 |
Continuous random variables and their characteristics |
Test |
W10 - W11 |
Hypothesis testing and its applications |
Week 11 Assignment 2 |
W12 |
Markov Chains and their applications |
Practical Test |
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Unit information based on version 2022.03 of the Handbook