Final examination:

• There is no final examination for this unit.

Assessment marks:

• It is the responsibility of students to view their marks for each within session assessment on iLearn within 20 working days of posting. If there are any discrepancies, students must contact the unit convenor immediately. Failure to do so will mean that queries received after the release of final results regarding assessment marks (not including the final exam mark) will not be addressed.

Extensions and penalties on within session assessment tasks:

• Tasks 10% or less – No extensions will be granted. Students who have not submitted the task prior to the deadline will be awarded a mark of 0 for the task, except for cases in which an application for special consideration is made and approved.

• Tasks above 10% - No extensions will be granted. There will be a deduction of 10% of the total available marks made from the total awarded mark for each 24 hour period or part thereof that the submission is late (for example, 25 hours late in submission – 20% penalty). This penalty does not apply for cases in which an application for special consideration is made and approved. No submission will be accepted after solutions have been posted.

Classes

• This unit is taught through 3 hours of lectures and/or tutorials per week.

• The timetable for classes can be found on the University web site at: http://www.timetables.mq.edu.au/

Technology Used and required:

• You will need access to the internet to obtain course information and download teaching materials from the unit website.

• It is your responsibility to check the unit website regularly to make sure that you are up-to-date with the information for the unit.

• Statistical software R will be used to calculate numerical results from time to time.

Required unit materials and/or recommended readings:

• Lecture Notes are the required materials and will be posted on the website before the lectures.

• Relevant references will be provided in Lecture Notes as recommended materials.  Some of them will be posted on the website.

Week 1: Nonparametric statistical methods; background knowledge

Week 2: One-sample location problem

Week 3: Estimation of location parameters; Two-sample location problem

Week 4: Two-sample dispersion and other problems

Week 5: One-way layout

Week 6: One-way layout; Assignment 1

Week 7: Two-way layout

Week 8: Two-way layout; Assignment 2

Week 9: Independence problem

Week 10: Independence problem; regression problem

Week 11: Nonparametric inference for regression problem

Week 12: Bootstrap estimation

Week 13: Revision; Assignment 3

Note: This is only a tentative schedule. The actual schedule will be adjusted from time to time in accordance with the progress of lectures.