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coloured square The University of Melbourne
620-301
Stochastic Modelling
Semester I, 2008
Last modified: Bulletin

Office hours during the swot vac (2-6 June): Mon 2nd June 1:30 pm--2:30 pm, Friday 6th June 11 am--1 pm.

To compensate for the loss of prac classes due to the public holidays and my absence, we will hold a prac from 9:30 to 12:30 on Wednesday 4 June at Old Geology Theatre 2. Please prepare your questions beforehand and I'll demonstrate how to do these problems.

Lectures are on Monday 1:00 - 2:00 at Old Geology-Theatre 2, Wednesday 2:15 - 3:15 at Redmond Barry-Lowe Theatre and Friday 1:00 - 2:00 at Richard Berry-Russell Love Theatre.

 Prac class (problem solving session) starts from the first week of the semester (i.e. week beginning on 3 March). It is on Friday 10:00 - 11:00 at Richard Berry-Russell Love Theatre.

A/Prof. Aihua Xia

Room 220, Richard Berry Building

xia@ms.unimelb.edu.au

A/Prof. Aihua Xia

Monday 2:15 - 3:15

Room 220, 2nd floor

Thursday 11 - 12

Richard Berry Building

Friday 11 - 12

  • Textbook:

K. Borovkov, Elements of stochastic modelling, World Scientific Publishing Co.

The purchase of books is voluntary; copies are available on reserve in Baillieu and Mathematical Sciences Libraries with call number 519.23 BORO.

The book covers the whole course. Please note that the book contains more material than what we can do in this subject nowadays. It is therefore not expected that students will know all what is in them!

What is expected is that by the end of the semester the students will know most of the stuff we are discussing in lectures and that they will have attempted all the problems from problem sheets and assignments.

  • Recommended books:

You do not have to buy any books. The books below are recommended as additional optional reading only.

  • Ross, S.M., Introduction to Probability Models. 7th edn. Academic Press, New York, 2000.
  • Parzen, E., Stochastic Processes. Holden Day, San Francisco, 1962.
  • Ross, S. M., Simulation. Academic Press, New York, 1997.
  • Grimmett, G. R. and Stirzaker, D. R., Probability and Random Processes. Clarendon Press, Oxford, 1992.
    •

    • Uni handbook:

    entry for 620-301 Stochastic Modelling.

    • Assessment:


    Anti-plagiarism declaration form can be downloaded from here.

    Assessment is based on three Take Home Assignments and a 3-hour end-of-semester Exam. The proportion that each of these assessment components counts towards the final result is tabled below.

    Component

    Proportion
    Examination a 3-hour exam
    80%
    Assignments Three assignments of equal weight
    20%
    100%

    • Assignments:

    Date handed out
    Date due in
    Answers
    2:15 pm Monday, 7 April
    5:00pm Friday, 11 April
    2:15 pm Monday, 28 April
    5:00pm Friday, 2 May
    2:15 pm Monday, 19 May
    5:00pm Friday, 23 May

    Late assignments will receive no mark (unless you qualify for special consideration; please contact the lecturer if this is the case).

    • Lecture handouts:

    Review of Prob 1; Review of Prob 2; Review of Prob 3; Lecture 4; Lecture 5; Lecture 6; Lecture 7; Lecture 8; Lecture 9; Lecture 10; Lecture 11; Lecture 12; Lecture 13; Lecture 14; Lecture 15; Lecture 16; Lecture 17; Lecture 18; Lecture 19; Lecture 20; Lecture 21; Lecture 22; Lecture 23; Lecture 24; Lecture 25; Lecture 26; Lecture 27; Lecture 28; Lecture 29; Lecture 30; Lecture 31; Lecture 32; Lecture 33.

     

    • Student Representatives:

  • Anastasia Abbey: aabbey@ugrad.unimelb.edu.au
    •

    • Problems:

    Problem sheets are (usually) distributed in class on Wednesdays. Solutions to problems (usually) appear on the Web one week later.

    Problem sets

    Solutions

    		 sol 1 sol 2 sol 3 sol 4 sol 5 sol 6 sol 7 sol 8 sol 9 sol 10 sol 11

    • Past exam papers:

    • Summary Notes of Probability:

    If you forgot about what you learned in 620201 Probability, here is the pdf file of the Summary Notes which will help you to refress your memory.

    • Generic Skills

    On completion of the subject, students should be able to:

  • Learn to adopt new ideas, from participation in the lecture program.
  • Think critically, and organize knowledge, from consideration of the lecture material.
  • Present a mathematical argument, by reflecting on those presented in the lecture series.
  • Develop creative ways of solving unfamiliar problems, especially through practice classes.
  • Plan effective work schedules, to meet the regular deadlines for submission of assessable work.
  • Through practice classes and other interactions with fellow students, you will develop the ability to work in a team. The department distinguishes between ethical collaboration, which is strongly encouraged, and plagiarism, which is prohibited.
    •

    © The University of Melbourne 1994-2001. Disclaimer and Copyright Information. 
    Created       : 12/12/2000 
Last modified : 

Authorised by: The Head, Department of Mathematics and Statistics.

    Maintained by: Aihua Xia, Department of Mathematics and Statistics.
    Email: xia@ms.unimelb.edu.au