MAST20006 Probability for Statistics

Credit Points: 12.5
Level: 2 (Undergraduate)
Dates & Locations:

This subject has the following teaching availabilities in 2017:

Semester 1, Parkville - Taught on campus.Show/hide details
Pre-teaching Period Start not applicable
Teaching Period 27-Feb-2017 to 28-May-2017
Assessment Period End 23-Jun-2017
Last date to Self-Enrol 10-Mar-2017
Census Date 31-Mar-2017
Last date to Withdraw without fail 05-May-2017

Timetable can be viewed here.
For information about these dates, click here.
Time Commitment: Contact Hours: 3 x one hour lectures per week, 1 x one hour practice class per week, and 1 x one hour computer laboratory class per week
Total Time Commitment:

Estimated total time commitment of 170 hours


One of

Study Period Commencement:
Credit Points:
Semester 1, Semester 2

and one of

Study Period Commencement:
Credit Points:
Summer Term, Semester 1, Semester 2
Semester 2

MAST10013 UMEP Maths for High Achieving Students

Corequisites: None
Recommended Background Knowledge: None
Non Allowed Subjects:

Students may only gain credit for one of

  • MAST20004 Probability
  • MAST20006 Probability for Statistics
  • MAST30015 Statistics for Mechanical Engineers (prior to 2011)
  • ELEN30002 Stochastic Signals and Systems (prior to 2011)
Core Participation Requirements:

For the purposes of considering request for Reasonable Adjustments under the Disability Standards for Education (Cwth 2005), and Student Support and Engagement Policy, academic requirements for this subject are articulated in the Subject Overview, Learning Outcomes, Assessment and Generic Skills sections of this entry.

It is University policy to take all reasonable steps to minimise the impact of disability upon academic study, and reasonable adjustments will be made to enhance a student's participation in the University's programs. Students who feel their disability may impact on meeting the requirements of this subject are encouraged to discuss this matter with a Faculty Student Adviser and Student Equity and Disability Support: http://services.unimelb.edu.au/disability


Dr Guoqi Qian


Email: qguoqi@unimelb.edu.au

Subject Overview:

This subject develops the probability theory that is necessary to understand statistical inference. Properties of probability are reviewed, random variables are introduced, and their properties are developed and illustrated through common univariate probability models. Models for the joint behaviour of random variables are introduced, along with conditional probability and Markov chains. Methods for obtaining the distributions of functions of random variables are considered along with techniques to obtain the exact and approximate distributions of sums of random variables. These methods will be illustrated through some well known normal approximations to discrete distributions and by obtaining the exact and approximate distributions of some commonly used statistics. Computer packages are used for numerical and theoretical calculations but no programming skills are required.

Learning Outcomes:

At the completion of the subject, students are expected to:

  • Develop a systematic understanding of probability, random variables, probability distributions and probability models, and their relevance to statistical inference;
  • Be able to formulate standard probability models from real world applications and critically assess them;
  • Be able to apply the properties of probability distributions, moment generating functions, variable transformations and conditional expectations to analyse common random variables and probability models;
  • Be able to use a computer package to perform algebraic and computational tasks in probability analyses.

Five written assignments due at regular intervals during semester amounting to a total of up to 50 pages (20%), a 45-minute computer laboratory test held at the end of semester (10%), and a 3-hour written examination in the examination period (70%).

Prescribed Texts:

Hogg and Tanis, Probability and Statistical Inference. 8th Edition, Prentice Hall, 2010.

Breadth Options:

This subject potentially can be taken as a breadth subject component for the following courses:

You should visit learn more about breadth subjects and read the breadth requirements for your degree, and should discuss your choice with your student adviser, before deciding on your subjects.

Fees Information: Subject EFTSL, Level, Discipline & Census Date
Generic Skills:

In addition to learning specific skills that will assist students in their future careers in science, they should progressively acquire generic skills from this subject that will assist them in any future career path. These include

  • problem-solving skills: the ability to engage with unfamiliar problems and identify relevant solution strategies;
  • analytical skills: the ability to construct and express logical arguments and to work in abstract or general terms to increase the clarity and efficiency of analysis;
  • collaborative skills: the ability to work in a team;
  • time management skills: the ability to meet regular deadlines while balancing competing commitments.
  • Become familiar with statistical computing packages.

This subject is available for science credit to students enrolled in the BSc (both pre-2008 and new degrees), BASc or a combined BSc course.

Students undertaking Actuarial Studies should take MAST20004 Probability instead of MAST20006 Probability for Statistics.

Students undertaking this subject are required to regularly use computers with the computer algebra system Maple and statistics package R installed.

Students undertaking this subject are not assumed to have any special computer skills at the beginning. They will learn the basic skills of using Maple in the subject.

Related Majors/Minors/Specialisations: Applied Mathematics
Applied Mathematics
Discrete Mathematics / Operations Research
Discrete Mathematics / Operations Research
Environmental Science major
Environments Discipline subjects
Science-credited subjects - new generation B-SCI and B-ENG.
Selective subjects for B-BMED
Statistics / Stochastic Processes
Statistics / Stochastic Processes
Related Breadth Track(s): Mathematics and Statistics
Mathematics for Economics
Accelerated Mathematics

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