Unit convenor and teaching staff |
Unit convenor and teaching staff
Unit Convenor
Ken Siu
|
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Credit points |
Credit points
10
|
Prerequisites |
Prerequisites
Admission to Master of Research
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Corequisites |
Corequisites
|
Co-badged status |
Co-badged status
|
Unit description |
Unit description
This unit develops some of the core skills needed for the practice of modern business analytics. Statistical inference and associated statistical computing will be covered along with an introduction to analytical techniques needed for working with both structured and unstructured data. The reporting of the results from quantitative style research will also be studied. |
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:
Assessment criteria for all assessment tasks will be provided on the unit iLearn site.
It is the responsibility of students to view their marks for each within-session-assessment on iLearn within 20 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 tasks (not including the final exam mark) will not be addressed.
Late submissions of assessments Unless a Special Consideration request has been submitted and approved, no extensions will be granted. There will be a deduction of 10% of the total available assessment-task marks made from the total awarded mark for each 24-hour period or part thereof that the submission is late. Late submissions will only be accepted up to 96 hours after the due date and time.
No late submissions will be accepted for timed assessments – e.g., quizzes, online tests.
Table 1: Penalty calculation based on submission time
Submission time after the due date (including weekends) |
Penalty (% of available assessment task mark) |
Example: for a non-timed assessment task marked out of 30 |
< 24 hours |
10% |
10% x 30 marks = 3-mark deduction |
24-48 hours |
20% |
20% x 30 marks = 6-mark deduction |
48-72 hours |
30% |
30% x 30 marks = 9-mark deduction |
72-96 hours |
40% |
40% x 30 marks = 12-mark deduction |
> 96 hours |
100% |
Assignment won’t be accepted |
Special Consideration
To request an extension on the due date/time for a timed or non-timed assessment task, you must submit a Special Consideration application. An application for Special Consideration does not guarantee approval.
The approved extension date for a student becomes the new due date for that student. The late submission penalties above then apply as of the new due date.
Name | Weighting | Hurdle | Due |
---|---|---|---|
Online Quiz 1 | 10% | No | Week 5 |
Literature Review | 20% | No | Week 7 |
Online Quiz 2 | 10% | No | Week 10 |
Final Examination | 60% | No | University Examination Period 6 to 24 June |
Assessment Type 1: Quiz/Test
Indicative Time on Task 2: 5 hours
Due: Week 5
Weighting: 10%
Students will be given a dataset and required to perform various calculations based on the techniques taught in classes.
Assessment Type 1: Literature review
Indicative Time on Task 2: 15 hours
Due: Week 7
Weighting: 20%
Students will produce a literate review on a particular topic. Details will be provided on iLearn.
Assessment Type 1: Quiz/Test
Indicative Time on Task 2: 5 hours
Due: Week 10
Weighting: 10%
Students will complete some multiple choice and/or short answer questions.
Assessment Type 1: Examination
Indicative Time on Task 2: 20 hours
Due: University Examination Period 6 to 24 June
Weighting: 60%
A two hour exam to be held during the University Exam Period.
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
Please refer to iLearn for details. It is the responsibility of individual students to stay up to date with the unit material.
1. R for Data Science, Wickham and Grolemund
2. An Introduction to Statistical Learning, James et al.
3. Collaborative Statistics, Illowsky and Dean
These are all open-source textbooks and are available freely and legally online.
Some references or recommended reading materials will be introduced whenever appropriate. Please refer to iLearn for details.
Calculator
A calculator will be required during the Final Examination. Note: students are expected to clearly show all steps (working) in their solutions to 'calculation' questions.
Non-programmable calculators with no text-retrieval functionality are permitted. Calculators that have a full alphabet on the keyboard are not permitted. Graphics calculators are not permitted. Calculators need the following minimum functionality: xy or ^, 1/x and log or ln functions, and a memory. Non-programmable financial calculators are permitted but it is not a requirement to use a financial calculator.
Students are assumed to already be familiar with the basic operation of their calculator prior to the start of this unit.
Computing
Prior to the start of this unit, students are expected to be familiar at least with the basic operation of their computing device.
Software
This unit does use R. Whilst it is not strictly necessary that students have any background using R, it will certainly be beneficial.
Knowledge of Mathematics and Statistics
A background of basic mathematics and statistics is assumed. Students entering the unit should be familiar with basic calculus, as well as concepts such as expected value, variance, and standard deviation.
Please refer to iLearn.
Macquarie University policies and procedures are accessible from Policy Central (https://policies.mq.edu.au). Students should be aware of the following policies in particular with regard to Learning and Teaching:
Students seeking more policy resources can visit Student Policies (https://students.mq.edu.au/support/study/policies). It is your one-stop-shop for the key policies you need to know about throughout your undergraduate student journey.
To find other policies relating to Teaching and Learning, visit Policy Central (https://policies.mq.edu.au) and use the search tool.
Macquarie University students have a responsibility to be familiar with the Student Code of Conduct: https://students.mq.edu.au/admin/other-resources/student-conduct
Results published on platform other than eStudent, (eg. iLearn, Coursera etc.) 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 or if you are a Global MBA student contact globalmba.support@mq.edu.au
At Macquarie, we believe academic integrity – honesty, respect, trust, responsibility, fairness and courage – is at the core of learning, teaching and research. We recognise that meeting the expectations required to complete your assessments can be challenging. So, we offer you a range of resources and services to help you reach your potential, including free online writing and maths support, academic skills development and wellbeing consultations.
Macquarie University provides a range of support services for students. For details, visit http://students.mq.edu.au/support/
The Writing Centre provides resources to develop your English language proficiency, academic writing, and communication skills.
The Library provides online and face to face support to help you find and use relevant information resources.
Macquarie University offers a range of Student Support Services including:
Got a question? Ask us via AskMQ, or contact Service Connect.
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.
Unit information based on version 2022.04 of the Handbook