Coronavirus (COVID-19) Update
Due to the Coronavirus (COVID-19) pandemic, any references to assessment tasks and on-campus delivery may no longer be up-to-date on this page.
Students should consult iLearn for revised unit information.
Find out more about the Coronavirus (COVID-19) and potential impacts on staff and students
Unit convenor and teaching staff |
Unit convenor and teaching staff
Unit Convenor/Lecturer
Nino Kordzakhia
Contact via Email
12WW 610
please refer to iLearn
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Credit points |
Credit points
10
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Prerequisites |
Prerequisites
Admission to MRes
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Corequisites |
Corequisites
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Co-badged status |
Co-badged status
STAT8830
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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:
Coronavirus (COVID-19) Update
Assessment details are no longer provided here as a result of changes due to the Coronavirus (COVID-19) pandemic.
Students should consult iLearn for revised unit information.
Find out more about the Coronavirus (COVID-19) and potential impacts on staff and students
ATTENDANCE and PARTICIPATION: If there are circumstances that mean you will miss a class, you can apply for Special Consideration via ask.mq.edu.au
ASSIGNMENT SUBMISSION: Assignment submission will be online through the iLearn page.
Submit assignments online via the appropriate assignment link on the iLearn page.
LATE SUBMISSION OF WORK: All assessment tasks must be submitted by the official due date and time. In the case of a late submission for a non-timed assessment (e.g. an assignment), if special consideration has NOT been granted, 20% of the earned mark will be deducted for each 24-hour period (or part thereof) that the submission is late for the first 2 days (including weekends and/or public holidays). For example, if an assignment is submitted 25 hours late, its mark will attract a penalty equal to 40% of the earned mark. After 2 days (including weekends and public holidays) a mark of 0% will be awarded. Timed assessment tasks (e.g. tests, examinations) do not fall under these rules.
Coronavirus (COVID-19) Update
Any references to on-campus delivery below may no longer be relevant due to COVID-19.
Please check here for updated delivery information: https://ask.mq.edu.au/account/pub/display/unit_status
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:
Coronavirus (COVID-19) Update
The unit schedule/topics and any references to on-campus delivery below may no longer be relevant due to COVID-19. Please consult iLearn for latest details, and check here for updated delivery information: https://ask.mq.edu.au/account/pub/display/unit_status
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 |
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W13 |
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Practical Test |
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