Elements of Statistics

Subject MAST90058 (2016)

Note: This is an archived Handbook entry from 2016.

Credit Points: 12.5
Level: 9 (Graduate/Postgraduate)
Dates & Locations:

This subject has the following teaching availabilities in 2016:

Semester 2, Parkville - Taught on campus.
Pre-teaching Period Start not applicable
Teaching Period 25-Jul-2016 to 23-Oct-2016
Assessment Period End 18-Nov-2016
Last date to Self-Enrol 05-Aug-2016
Census Date 31-Aug-2016
Last date to Withdraw without fail 23-Sep-2016


Timetable can be viewed here. For information about these dates, click here.
Time Commitment: Contact Hours: 36 hours: Three 1-hour lectures per week, one 1-hour tutorials per week, and one 1-hour computer laboratory classes per week.
Total Time Commitment:

170 hours
Prerequisites:

One of the following, or equivalent:

Subject
Study Period Commencement:
Credit Points:
Semester 1
12.50
Corequisites:

None
Recommended Background Knowledge:

None
Non Allowed Subjects:

Students who have taken second year level subjects in Statistics or its equivalent may not take this subject.
Core Participation Requirements:

It is University policy to take all reasonable steps to minimise the impact of disability upon academic study and reasonable steps will be made to enhance a student’s participation in the University’s programs. Students who feel their disability may impact upon their active and safe participation in a subject are encouraged to discuss this with the relevant subject coordinator and the Disability Liaison Unit.

Coordinator

Dr Davide Ferrari

Contact

Email: dferrari@unimelb.edu.au

Subject Overview:

The analysis of data arising in Bioinformatics and Biostatistics requires the use of sophisticated statistical techniques and computing packages. This subject introduces the theory underlying modern statistical inference and statistical computation. Both classical and Bayesian statistical methods are developed and many standard statistical methods are included as applications of a common theory. This subject is co-taught with MAST20005 Statistics.
Learning Outcomes:

  • Students completing this subject should be familiar with the basic ideas of estimation and hypothesis testing and be able to carry out many standard statistical procedures using a statistical computing package.
  • Students should develop the ability to fit probability models to data by both estimating and testing hypotheses about model parameters.
Assessment:

30 pages of written assignments due during the semester (20%); a 45-minute computer laboratory test held mid-semester (10%); a 3-hour written examination in the examination period (70%).
Prescribed Texts:

Hogg and Tanis, Probability and Statistical Inference. Eighth Edition, Prentice Hall, 2009.
Breadth Options:

This subject is not available as a breadth subject.
Fees Information: Subject EFTSL, Level, Discipline & Census Date
Generic Skills:

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 a major statistical computing package.
Related Course(s): Doctor of Philosophy - Engineering
Master of Commerce (Finance)
Master of Philosophy - Engineering
Master of Science (Bioinformatics)

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