Handbook

MAST30020 Probability for Inference

Credit Points: 12.5
Level: 3 (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
Total Time Commitment:

Estimated total time commitment of 170 hours

Prerequisites:

One of

Subject
Study Period Commencement:
Credit Points:
Semester 1, Semester 2
12.50

Plus either

Subject
Study Period Commencement:
Credit Points:
Semester 1
12.50

Or

Subject
Study Period Commencement:
Credit Points:

(MAST20006 must have a result grade of H2B or above)

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

Coordinator

Prof Konstantin Borovkov

Contact

Email: borovkov@unimelb.edu.au

Subject Overview:

This subject introduces a measured-theoretic approach to probability theory and presents its fundamentals concepts and results.

Topics covered include: probability spaces and random variables, expectation, conditional expectation and distributions, elements of multivariate distribution theory, modes of convergence in probabilty theory, characteristics functions and their application in key limit theorems.

Learning Outcomes:

On completion of this subject students should:

  • Have a systematic understanding of the fundamentals of modern probability theory;
  • Know and be able to work with the most important univariate and multivariate probability distributions;
  • Have a good knowledge of general conditional expectations, integral transforms and key ideas of different modes of convergence of random variables and distributions.
Assessment:

Ten written assignments due at weekly intervals during semester amounting to a total of up to 50 pages (30%), and a 3-hour written examination in the examination period (70%).

Prescribed Texts:

None

Recommended Texts:

A.F. Karr, Probability, 1st Ed. Springer, New York, 1993.

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 will have the opportunity to develop generic skills 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.
Notes:

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.

This subject was previously titled MAST30020 Probability and Statistical Inference

Related Majors/Minors/Specialisations: Science-credited subjects - new generation B-SCI and B-ENG.
Selective subjects for B-BMED
Statistics / Stochastic Processes
Statistics / Stochastic Processes
Statistics / Stochastic Processes
Statistics / Stochastic Processes
Statistics / Stochastic Processes (specialisation of Mathematics and Statistics major)

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