coloured square The University of Melbourne
MAST30020
Probability and Statistical Inference
Semester 1, 2013

A stable LMS-independent URL of this page is:
http://www.ms.unimelb.edu.au/~s620323

  • Uni handbook:

    entry for MAST30020 Probability and Statistical Inference

  • Lectures & Pracs:

    All lectures will take place in Rm 213, Richard Berry Bldg, on:

    Mondays: 12:00 noon - 1:00 pm.
    Tuesdays: 10:00 am - 11:00 am.
    Thursdays: 4:15 pm - 5:15 pm.

    Starting week 1 of semester, there is a 1-hour prac per week on:

    Fridays: 11:00 am - 12:00 noon, Rm 213, Richard Berry Bldg.

    To be on the safe side, one must check the official timetable!
    [The days/times above were retrieved on 6 February 2013.]

  • Lecturer:

    Prof. Kostya Borovkov

    Office hours for MAST30020:

    Tuesday, 11am - 1pm (as discussed in the first lecture).

    Room 225, Richard Berry Bldg,
    e-mail: borovkovZ@Zunimelb.Zedu.au

    Attention: antispam measure! You may wish to remove all the three literals Z from the above e-mail address before using it. If you don't do that, the probability of your email reaching me will be quite low.

  • A few end-of-semester announcements:

    A pre-exam consultation will be held on Tuesday, 18 June 2012, starting at 2:15 pm. Venue: Room 213, Richard Berry Bldg.

    No Tuesday morning consultation on that day therefore.

  • Lecture slides:

    NB: Most of the downloadable from this page files are PDFs; you will need Adobe Acrobat Reader or the Acrobat plugin for your Web browser to view/print these documents. Most likely, the software has already been installed on the computer/tablet/smartphone you are using. If not, Adobe Acrobat Reader is a freely distributable software, and you can click here to download it. Here is a complete set of lecture slides for our course. You may wish to download and print out the lecture slides in advance, in case you desire to bring them to the class and/or read them at your convenience elsewhere. Note, however, that parts of our lectures may be given in an old-fashioned style, on the blackboard, whiteboard or otherwise.

    It may happen that not all the slides available on the Web will be shown/used in lectures.

    For the curious ones: click here to find a typeset description (see Example 10, p.6) of the example of a nonmeasurable set (usually) given in our first lecture.

    For your convenience, here is an outline of the course, with references to slide numbers.

  • Recommended books:

    To a large extent, the subject will be taught following selected chapters from this text:

    Alan F. Karr, Probability, Springer (1993); 312 pp.
    ISBN-10: 0387940715
    ISBN-13: 978-0387940717

    To preview the text on Google Books, click HERE.

    One copy of the text is held on 2h reserve at our ERC Library; one copy will be available for overnight loan.

    In fact, University of Melbourne students can access an electronic version of the book by clicking HERE (you can be asked to log in using your central UofM e-mail username and password).

    The book is available from Amazon (prices starting at US$73.25 [for used], as seen on 06/02/13) and can be ordered from this site: click HERE.

    Moreover, a Kindle edition of the text is available for immediate sale and delivery from Amazon. It costs US$91.15 Please note that one doesn't need to have a Kindle device to use Kindle editions: one can simply install a free Kindle reading application on one's computer and read the books from the screen. Here are links to downloads for different operating systems: Windows, Mac, Android. If you prefer Linux, click HERE for instructions.

    Or you can use the Kindle Cloud Reader, a "free application that lets you read Kindle books using Google Chrome, Firefox, or Safari on your PC or Mac computer, Firefox or Chrome on your Linux computer, or Safari on your iPad -- no Kindle required."

    Having access to the textbook would be beneficial, but purchasing it is not mandatory. Other intermediate level decent probability textbooks could be used as optional reading, e.g.

    • G R Grimmett, D R Stirzaker, Probability and random processes. Oxford: Oxford University Press, 2001 (3rd edn) or 1992 (2nd edn). [Library call no: UniM ERC 519.2 GRIM.]
    • A N Shiryaev, Probability. New York: Springer, 1984 or 1996 (2nd edn). [Library call no: UniM ERC 519.2 SHIR.]

  • Problems:

    Problem sheets will (usually) be distributed in lectures on Thursdays (or on Fridays) and appear on the Web (see below) on the same day (or a bit later). A typical problem sheet consists of two parts: Tutorial problems and Homework problems.

  • Assessment:

    • You will be given weekly homeworks, to make sure you will be doing some work on the subject material during the semester.

      Each week you will have to submit your solutions to the problems from the homework by the due time. Only one of the homework problems will be marked each time, and this problem will be chosen at random after the submission time. Late homeworks will receive no mark (unless you qualify for special consideration, in which case special arrangements may be made - please contact your tutor).

    • There will be a 3-hour end of semester exam.

    • Final Mark = 0.8 x Exam Mark (out of 100) + 0.2 x Total Homework Mark (out of 100)

  • Generic skills:

    In addition to learning specific technical skills that will assist you in your future careers in science, engineering, commerce, education or elsewhere, you will have the opportunity to develop in this subject generic skills that will assist you whatever your future career path:

    • you will develop problem-solving skills including engaging with unfamiliar problems and identifying relevant strategies;
    • you will develop 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 the analysis;
    • through 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;
    • 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.

    (From the Department's generic statement.)

    [It used to be a University requirement that a generic skills statement appears on each subject's Web site. It may still be the case.]

  • A brief summary of the QoT survey feedback:

    The subject is interesting and stimulating enough.

    The lecturer is OK, too.

  • Miscellanea

    • The student rep in our class:

      Sarah Murphy-Gamble.

    • Click HERE to download the 2010 exam paper.

    • And if you click HERE then you will download the 2011 exam paper!

    • And there is more: if you click HERE, you will also download solutions to that exam paper!!

    • We will talk about the exam paper in class, closer to the end of semester. Please note that I have never ever said that the 2013 exam paper will be quite similar to the 2010 and/or 2011 ones. It might, though.

 

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Created: 6 February 2013
Last modified: recently (on 6 February 2013 or even later)
Authorised by: K Borovkov, Department of Mathematics and Statistics.

Maintained by: K.Borovkov, Department of Mathematics and Statistics.
Email: borovkovZ@Zunimelb.Zedu.au

Attention: antispam measure! Remove all the three literals Z from the e-mail address in case you want me to receive your message.