Unit convenor and teaching staff 
Unit convenor and teaching staff
Unit Convenor
Gillian Heller
Contact via gillian.heller@mq.edu.au
Room 6.19, 12 Wally's Walk
Wednesday 1112
Lecturer
A/Prof Robin van den Honert
Contact via rob.vandenhonert@mq.edu.au
Room 6.13, 12 Wally's Walk
Thursday 35pm


Credit points 
Credit points
3

Prerequisites 
Prerequisites
6cp at 200 level including (STAT270 or STAT271 or BIOL235(P) or PSY222 or PSY248(P))

Corequisites 
Corequisites

Cobadged status 
Cobadged status

Unit description 
Unit description
This unit discusses statistical modelling in general and in particular demonstrates the wide applicability of linear and generalised linear models. Topics include multiple linear regression, logistic regression and Poisson regression. The emphasis is on practical issues in data analysis with some reference to the theoretical background. Statistical packages are used for both model fitting and diagnostic testing.

Information about important academic dates including deadlines for withdrawing from units are available at http://students.mq.edu.au/student_admin/enrolmentguide/academicdates/
Extensions to assignments are at the discretion of the lecturer. It is the responsibility of the student to prove that there has been Disruption to Studies. If no extension has been given, 5% of the earned mark for an assignment will be deducted for each day that an assignment is late, up to a maximum of 50%.
The only exception to not sitting an examination at the designated time is because of documented illness or unavoidable disruption. In this case, you may notify the University of your disruption to studies by providing required documentation through https://ask.mq.edu.au/. Please see Disruption to Studies policy at http://www.mq.edu.au/policy/docs/disruption_studies/policy.html for further information.
If you notify the University of your disruption to studies for your examination, you must make yourself available for the week of July 24 – 28 2017. If you are not available at that time, there is no guarantee an additional examination time will be offered. Specific examination dates and times will be determined at a later date.
The University Examination timetable will be available in draft form approximately eight weeks before the commencement of the examinations and in final form approximately four weeks before the commencement of the examinations at:http://www.timetables.mq.edu.au/
Name  Weighting  Hurdle  Due 

Test of prerequisite knowledge  0%  No  26 March 
Assignment 1  15%  No  28 March 
Assignment 2  15%  No  2 May 
Assignment 3  15%  No  30 May 
Tutorials  5%  No   
Examination  50%  No  TBA 
Due: 26 March
Weighting: 0%
This quiz is available from Week 1, and is intended as a check on your assumed level of knowledge of linear models. If you do not score well, you are advised to consider withdrawal from the unit before the census date.
Due: 28 March
Weighting: 15%
There are three assignments, worth 15% each. They should be submitted to the lecturer, by the due time and date. They give you an opportunity to reinforce and apply the concepts covered in lectures and the skills learned in tutorial sessions.
Due: 2 May
Weighting: 15%
As Assignment 1.
Due: 30 May
Weighting: 15%
As Assignment 1.
Due: 
Weighting: 5%
A mark worth 5% of your final mark, will be given for your participation in the laboratory tutorials, on the basis of collected laboratory sheets.
Due: TBA
Weighting: 50%
The examination will cover the material studied in the whole unit and address all the unit outcomes. You may take one A4 sheet, handwritten on both sides, into the final examination.
You should attend the following classes each week:
· 2 hour lecture: Wednesday 8  10am, 12 Second Way (C5A), room 315
· 2 hour laboratory tutorial: Wednesday 12  2pm, 6 Eastern Rd (E4B), room 104 OR Thursday 9  11am, 6 Eastern Rd (E4B), room 206
Lectures begin in Week 1. Students should print off the course notes from iLearn, and bring them to lectures.
Tutorials begin in week 1 and are based on work from the current week’s lecture. Tutorials are held in computing labs and allow you to practise techniques learnt in lectures. We will mainly use SPSS, but we will supplement this with other statistical software. You will complete worksheets as part of the learning process. SPSS is installed in the computing labs in E4B, and will be used in tutorial sessions and for assignments. Assignments may be completed in these rooms. It is most convenient to bring a memory stick when using these computers.
Text book The recommended text (available from the Coop Bookshop) is: Chatterjee S & Hadi AS (2012). Regression Analysis By Example, 5th Revised edition, Wiley.
Calculator You will need a calculator with statistical mode for the final examination.
Software The statistical software SPSS will be the main package used. In addition, we will be demonstrating applications using other statistical software such as Minitab and Arc. All of this software is available in the computer labs in E4B.
Staff consultation hours Members of the Statistics Department have consultation hours each week when they are available to help students. These consultation hours are available on iLearn.
Week 
Topic 
Text chapter 
Assessment 
1 
Simple linear regression 
1,2 

2 
Simple linear regression contd, introduction to multiple linear regression 
2 

3 
The model in matrix form, hypothesis tests, residuals, residual & partial regression plots 
3,4 

4 
Diagnostics contd: extreme observations (leverage, DFBETAs, Cook’s distances); transformations 


5 
Transformations contd; collinearity 
4, 6 
Assignment 1 due 
6 
Polynomial regression; categorical covariates 
6, 9 

7 
Analysis of change 
5 


Midsemester break 


8 
Interaction and confounding 
 
Assignment 2 due 
9 
Variable selection, model building 
5 

10 
Introduction to generalized linear models; Logistic regression 
11 

11 
Logistic regression ; Poisson regression 
12 

12 
Poisson regression; Gamma regression 
12, 13 
Assignment 3 due 
13 
Gamma regression; revision 
13 

Macquarie University policies and procedures are accessible from Policy Central. Students should be aware of the following policies in particular with regard to Learning and Teaching:
Academic Honesty Policy http://mq.edu.au/policy/docs/academic_honesty/policy.html
Assessment Policy http://mq.edu.au/policy/docs/assessment/policy_2016.html
Grade Appeal Policy http://mq.edu.au/policy/docs/gradeappeal/policy.html
Complaint Management Procedure for Students and Members of the Public http://www.mq.edu.au/policy/docs/complaint_management/procedure.html
Disruption to Studies Policy (in effect until Dec 4th, 2017): http://www.mq.edu.au/policy/docs/disruption_studies/policy.html
Special Consideration Policy (in effect from Dec 4th, 2017): https://staff.mq.edu.au/work/strategyplanningandgovernance/universitypoliciesandprocedures/policies/specialconsideration
In addition, a number of other policies can be found in the Learning and Teaching Category of Policy Central.
Macquarie University students have a responsibility to be familiar with the Student Code of Conduct: https://students.mq.edu.au/support/student_conduct/
Results shown in iLearn, or released directly by your Unit Convenor, are not confirmed as they are subject to final approval by the University. Once approved, final results will be sent to your student email address and will be made available in eStudent. For more information visit ask.mq.edu.au.
Macquarie University provides a range of support services for students. For details, visit http://students.mq.edu.au/support/
Learning Skills (mq.edu.au/learningskills) provides academic writing resources and study strategies to improve your marks and take control of your study.
For all student enquiries, visit Student Connect at ask.mq.edu.au
Students with a disability are encouraged to contact the Disability Service who can provide appropriate help with any issues that arise during their studies.
For help with University computer systems and technology, visit http://www.mq.edu.au/about_us/offices_and_units/information_technology/help/.
When using the University's IT, you must adhere to the Acceptable Use of IT Resources Policy. The policy applies to all who connect to the MQ network including students.
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