Notice
As part of Phase 3 of our return to campus plan, most units will now run tutorials, seminars and other small group learning activities on campus for the second half-year, while keeping an online version available for those students unable to return or those who choose to continue their studies online.
To check the availability of face to face activities for your unit, please go to timetable viewer. To check detailed information on unit assessments visit your unit's iLearn space or consult your unit convenor.
Unit convenor and teaching staff |
Unit convenor and teaching staff
Tania Prvan
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Credit points |
Credit points
10
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Prerequisites |
Prerequisites
Admission to MRes
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Corequisites |
Corequisites
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Co-badged status |
Co-badged status
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Unit description |
Unit description
We present the principles of effective graphical presentation, set them in a historical context and apply them to a variety of statistical data sets. Emphasis is given to use of modern multivariate graphical techniques such as trellis/lattice graphs and mosaic plots to show a variety of displays of data and model fits, and to display model consistency with data. To present graphics, we introduce and use R, as well as other standard packages. Participants choose an area for further investigation related to their interests.
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Information about important academic dates including deadlines for withdrawing from units are available at https://www.mq.edu.au/study/calendar-of-dates
On successful completion of this unit, you will be able to:
Name | Weighting | Hurdle | Due |
---|---|---|---|
Portfolio | 25% | No | Week 7 |
Assignment 1 | 25% | No | Week 9 |
Assignment 2 | 25% | No | Week 12 |
Online Final Examination | 25% | No | Exam Period |
Assessment Type 1: Portfolio
Indicative Time on Task 2: 20 hours
Due: Week 7
Weighting: 25%
An individual portfolio of five items relating to statistical graphics, each item using a maximum of two pages, on topics or questions given in the lecture notes.
Assessment Type 1: Qualitative analysis task
Indicative Time on Task 2: 20 hours
Due: Week 9
Weighting: 25%
Five statistical graphics should be collected during the first half of the semester from newspaper articles or journal articles published this year. You must not draw your own graphics or get someone else to do so for you. Credit will be given for interesting, carefully chosen graphics which show evidence of searching widely. The five statistical graphics must be included in your submission along with the source of each graphic (title of the article, authors, source, page numbers or url etc.) and each graphic must be discussed.
This discussion must include strengths and weaknesses of each graphic. It may include the reason why you chose the graphic.
Assessment Type 1: Quantitative analysis task
Indicative Time on Task 2: 20 hours
Due: Week 12
Weighting: 25%
A data set with some documentation will be given. This data set must be analysed and a concise, well-organised report on your analysis must be prepared. The analysis must be appropriate and be substantially graphical. Appropriate statistical graphics explored or mentioned in the lectures should be used. The statistical package R must be used.
Assessment Type 1: Examination
Indicative Time on Task 2: 3 hours
Due: Exam Period
Weighting: 25%
The final examination is nominally two hours longs with 10 minutes reading time. It will be done online. There will be extra time to upload handwritten solutions to iLearn.
1 If you need help with your assignment, please contact:
2 Indicative time-on-task is an estimate of the time required for completion of the assessment task and is subject to individual variation
There are 2 hours of lectures and 1 practical each week in this unit. Lectures commence in Week 1 and practicals commence in Week 2. Lecture material will be put up on iLearn. There is no specified textbook for this unit and a variety of readings will be available.
The following books are good general references that may be used during the semester.
There will be weekly readings.
Technologies used and required
Lecture material will be placed on iLearn. R (https://www.r-project.org/) and Mondrian (http://www.theusrus.de/Mondrian/) will be used in some of the lectures. Students will need to use R and Mondrian. All assessments except for the final examination must be word processed and converted to pdf files for online submission in iLearn. A Word document can be saved as pdf.
Below is an outline of topics to be covered.
Week | Topic |
1 | Introduction to statistical graphics |
2 | Principles of statistical graphics |
3 | Getting familiar with R |
4 | More R |
5 | Mosaic Plots |
6 | Parallel Coordinate Plots |
7 | More R |
8 | Linear Models I |
9 | Linear Models II |
10 | Time and time-oriented data |
11 | Visual Data Mining |
12 | High dimensional graphics |
13 | Review |
Macquarie University policies and procedures are accessible from Policy Central (https://staff.mq.edu.au/work/strategy-planning-and-governance/university-policies-and-procedures/policy-central). Students should be aware of the following policies in particular with regard to Learning and Teaching:
Students seeking more policy resources can visit the Student Policy Gateway (https://students.mq.edu.au/support/study/student-policy-gateway). It is your one-stop-shop for the key policies you need to know about throughout your undergraduate student journey.
If you would like to see all the policies relevant to Learning and Teaching visit Policy Central (https://staff.mq.edu.au/work/strategy-planning-and-governance/university-policies-and-procedures/policy-central).
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Learning Skills (mq.edu.au/learningskills) provides academic writing resources and study strategies to help you improve your marks and take control of your study.
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