Requirements to Pass this Unit

To pass this unit you must:

• Achieve a total mark equal to or greater than 50%.

Hurdle Assessments

There is no Hurdle Assessment.

Participation

We strongly encourage all students to actively participate in all learning activities. Regular engagement is crucial for your success in this unit, as these activities provide opportunities to deepen your understanding of the material, collaborate with peers, and receive valuable feedback from instructors, to assist in completing the unit assessments. Your active participation not only enhances your own learning experience but also contributes to a vibrant and dynamic learning environment for everyone.

Release

• Assignment – To be released no later than 14^th August.
• Case study/analysis – To be released no later than 9^th October.
• Final Exam – To be released on the scheduled final examination date.

Late Assessment Submission Penalty

Unless a Special Consideration request has been submitted and approved, a 5% penalty (of the total possible mark of the task) will be applied for each day a written report or presentation assessment is not submitted, up until the 7^th day (including weekends). After the 7^th day, a grade of ‘0’ will be awarded even if the assessment is submitted. The submission time for all uploaded assessments is 11:55 pm. A 1-hour grace period will be provided to students who experience technical concerns. For any late submission of time-sensitive tasks, such as scheduled tests/exams, performance assessments/presentations, and/or scheduled practical assessments/labs, please apply for Special Consideration. For example, if the assignment is worth 8 marks (of the entire unit) and your submission is late by 19 hours (or 23 hours 59 minutes 59 seconds), 0.4 marks (5% of 8 marks) will be deducted. If your submission is late by 24 hours (or 47 hours 59 minutes 59 seconds), 0.8 marks (10% of 8 marks) will be deducted, and so on.

Assessments where Late Submissions will be accepted

• Assignment – YES, Standard Late Penalty applies
• Case study/analysis – YES, Standard Late Penalty applies
• Final Exam – NO, unless Special Consideration is granted

Special Consideration

The Special Consideration Policy aims to support students who have been impacted by short-term circumstances or events that are serious, unavoidable and significantly disruptive, and which may affect their performance in assessment. If you experience circumstances or events that affect your ability to complete the assessments in this unit on time, please inform the convenor and submit a Special Consideration request through http://connect.mq.edu.au/.

Short Extension

For some assessment types, students are allowed to request an extra 3 calendar days to complete eligible assessments. No reason or evidence is required.

Classes

Lectures (beginning in Week 1): There is one two-hour lectures each week.

SGTA classes (beginning in Week 2): Students must register for one one-hour class per week.

The timetable for classes can be found on the University website at: https://publish.mq.edu.au

Enrolment can be managed using eStudent at: https://students.mq.edu.au/support/technology/systems/estudent

Suggested textbooks

The following textbooks are useful as supplementary resources for additional questions and explanations. They are available from the Macquarie University library.

1. Fahrmeir, L., Kneib, T., Lang, S. and Marx, B. (2013). Regression: Models, Methods and Applications, Springer.   
2. Faraway, J. J. (2016). Extending the linear model with R: generalized linear, mixed effects and nonparametric regression models. CRC Press.  
3. De Jong, P. and Heller, G.Z. (2008). Generalized Linear Models for Insurance Data, Cambridge University Press.  
4. Wood, Simon N. (2017). Generalized additive models: an introduction with R, 2nd edition. CRC Press.  
5. Stasinopoulos M. D., Rigby R. A., Heller G. Z., Voudouris V., De Bastiani F. (2017). Flexible Regression and Smoothing: Using GAMLSS in R. CRC Press.  
6. Dobson, A. J. and Barnett, A. G. (2018). An Introduction to Generalized Linear Models, 4th edition, Chapman & Hall.  
7. Lindsey, J.K. (1997). Applying Generalized Linear Models, Springer.   
8. McCullagh, P. and Nelder, J.A. (1989). Generalized Linear Models, 2nd edition, Chapman & Hall.

Technology Used and Required

This unit requires the use of the following computer software:

• R: R is a free statistical software package. Access and installation instructions may be found at: https://www.r-project.org/
• RStudio: RStudio is an open source tool that is used to manage and present work performed using R. Access and installation instructions may be found at https://rstudio.com/products/rstudio/download/
• LaTeX: LaTeX is a free mathematical typesetting program. You should use this to help to typeset your assignment. Access and installation instructions may be found at: https://www.latex-project.org/get/. Alternatively, Overleaf is an excellent online platform that allows you to write and compile LaTeX documents without installing any software.

Communication

We will communicate with you via your university email or through announcements on iLearn. Queries to convenors can either be placed on the iLearn discussion forum or sent to the unit convenor via the contact email on iLearn.

We value student feedback to be able to continually improve the way we offer our units. As such we encourage students to provide constructive feedback via student surveys, to the teaching staff directly, or via the FSE Student Experience & Feedback link in the iLearn page.

Student feedback from the previous offering of this unit was very positive overall, with students pleased with the clarity around assessment requirements and the level of support from teaching staff. As such, no change to the delivery of the unit is planned, however we will continue to strive to improve the level of support and the level of student engagement.