Statistics for Research Workers

Subject MAST90007 (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:

July, Parkville - Taught on campus.
Pre-teaching Period Start not applicable
Teaching Period 07-Jul-2016 to 19-Jul-2016
Assessment Period End 05-Aug-2016
Last date to Self-Enrol 07-Jul-2016
Census Date 15-Jul-2016
Last date to Withdraw without fail 29-Jul-2016


Timetable can be viewed here. For information about these dates, click here.
Time Commitment: Contact Hours: 8 days intensive: 48 hours (24 hours of lectures and 24 hours of practical classes)
Total Time Commitment:

170 hours.

Classes will not be held on Wednesday for both weeks of the course.

Prerequisites:

It is expected that participants will have studied mathematics at VCE level, or equivalent. Students must be enrolled in a Masters-Level program or above.

This subject will involve mathematical, statistical and computing skills.

Corequisites:

None

Recommended Background Knowledge:

None

Non Allowed Subjects:

Students who have completed any of the following may not enrol in this subject for credit

Subject

Students who have completed MAST10010 Data Analysis 1 or MAST10011 Experimental Design and Data Analysis must obtain subject coordinator’s approval before enrolling in this subject.

Core Participation Requirements:

For the purposes of considering requests for Reasonable Adjustments under the Disability Standards for Education (Cwth 2005), and Students Experiencing Academic Disadvantage Policy, academic requirements for this subject are articulated in the Subject Description, Subject Objectives, Generic Skills and Assessment Requirements for this entry.

The University is dedicated to provide support to those with special requirements. Further details on the disability support scheme can be found at the Disability Liaison Unit website: http://www.services.unimelb.edu.au/disability/

Coordinator

Prof Ian Gordon

Contact

Email: irg@unimelb.edu.au

Subject Overview:

This subject is designed to provide students with detailed training in statistical methods as applied to the design and analysis of projects undertaken by postgraduate students, across all disciplines.

Learning Outcomes:

Students who complete this subject should:

  • learn sound principles of design and research;
  • acquire skills in the analysis of research;
  • gain skills in the use of statistical software;
  • develop the ability to assess published research critically from a statistical point of view.
Assessment:
  • Up to 12 short exercises conducted during the subject, including the use of software (continuous assessment), involving a total of no more than 15 written pages (30%);
  • A 1.5-hour examination at the conclusion of the subject (50%);
  • A 1500-word assignment on the analysis and interpretation of quantitative data from an empirical research study (20%) to be submitted two weeks after completion of the subject.
Prescribed Texts:

None

Breadth Options:

This subject is not available as a breadth subject.

Fees Information: Subject EFTSL, Level, Discipline & Census Date
Links to further information: http://www.scc.ms.unimelb.edu.au/
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Master of Science (Information Systems)
Master of Science (Physics)
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