Students
ENGG255 – Data Analysis and Visualisation
2017 – S1 Day
General Information
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| Unit convenor and teaching staff |
Unit convenor and teaching staff
Lecturer
Mohsen Asadnia
Contact via +61-2-9850-9528
Room 112, Level 1, E6B
Wednesday 2pm-5pm
Associate Professor
Stuart Jackson
Contact via +61-2-9850-9137
Room 123, Level 1, E6B
Tuesday 2pm-4pm
Stuart Jackson
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| Credit points |
Credit points
3
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| Prerequisites |
Prerequisites
COMP115 and ENGG150 and MATH135
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| Corequisites |
Corequisites
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| Co-badged status |
Co-badged status
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| Unit description |
Unit description
This unit provides knowledge and skills for further study in electrical and mechanical disciplines of engineering. Sound engineering relies on adequate modelling and visualisation of data. This unit develops the concept that engineering data consists of discrete and vectored quantities that is fit to a model of reality.
Foundation knowledge and skill in computer programming, electrical and mechanical concepts, and mathematics is assumed. The concept of data as discrete numerical vectors is developed using computer controlled interfaces to acquire real electrical and mechanical measurements. Spreadsheets and numerical computing environments, are introduced and used to manipulate, process, view and present data. The adequacy of simple models of transient responses, temperature dependence, and other physical process is explored. Judgement is developed in the appropriate visualisation of data to best expose physical processes and check the design of experiment.
The concepts developed in this unit are required in the advanced engineering units for treatment of modelling, simulation, optimisation, and computer aided design. The skills in this unit also will be used in subsequent engineering units dealing with presentation of data.
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Important Academic Dates
Information about important academic dates including deadlines for withdrawing from units are available at https://www.mq.edu.au/study/calendar-of-dates
Learning Outcomes
On successful completion of this unit, you will be able to:
- Demonstrate a good understanding of the different types of data confronting engineers and the methods of data visualisation.
- To apply mathematics, physics and engineering principles to the analysis of measured data.
- Demonstrate knowledge of data acquisition systems, noise and error analysis.
- Demonstrate knowledge in engineering through the relationship between theoretical, mathematical and computational modelling to solve real world and dynamical problems. and
General Assessment Information
Notifications
Formal notification of assessment tasks, grading rubrics and due dates will be posted on iLearn. Although all reasonable measures to ensure the information is accurate, the University reserves the right to make changes without notice. Each student is responsible for checking iLearn for changes and updates.
Weekly Plan
A weekly plan of lectures, assignments, tests, laboratory and workshop sessions will be posted on iLearn. Students are expected to be aware of possible minor variations.
Assignment Tasks
Assignment questions will be posted on iLearn. Assignment solutions will be posted within one to three days after the submission date. Submissions will not be accepted once the solution is posted.
All assignments must be submitted electronically through iLearn (in pdf format). Submissions are expected to be typed in a logical layout and sequence. Markers WILL NOT grade poorly organized or illegible scans or drafts. The expected workload includes preparation of final copies and clear diagrams. Resubmissions will be permitted up to due date.
All assignments should be prepared individually. It is expected that students consult tutors, lecturers or other students while learning the concepts, but copying assignments from others is not accepted. Students are expected to have read and understood the academic honesty policy.
Absences
Late notices or absences from tests, workshops and laboratories will be considered under extenuating circumstances upon lodgement and approval of a formal notice of disruption of studies.
Grading
To obtain a passing grade (P/CR/D/HD) a total mark of 50 more is required AND a mark of 50 or more is required for the final examination. The final exam is a hurdle requirement because it is the only reliable assessment of individual performance for this unit. A passing grade of 50% or more in the final examination is a condition of passing this unit. Students who make a serious attempt but fail to meet the hurdle requirement will be given one further opportunity to pass. A serious attempt is defined as achievement of a mark of 40% or greater.
Laboratory
Due: Weekly
Weighting: 20%
Practical sessions start in Week 2. They are comprised of laboratory or problem-solving workshop sessions linked to each learning outcome; and they are compulsory for all students. Students are expected to arrive on time and use the laboratory time efficiently. Students should enroll in one practical class at the beginning of the semester. Laboratory or workshop worksheets, required data and other necessary items will be posted on iLearn prior to the weekly sessions and it is compulsory for students to complete the preparatory work before coming to the session.
Practicals will be largely assessed in class but there will some "take-home" assignments for the laboratory sections. More information will be available on iLearn
In laboratory sessions, students learn how to utilise their data visualisation knowledge in processing real-world engineering problems. Students will work on different skills such as advance plotting in MATLAB and Excel, programming in MATLAB, data visualisation and programming in LabVIEW. Students do not need to bring their personal laptop to the laboratory sessions. Computers with the required software (such as MATLAB, Excel, LabVIEW) will be provided.
Assignment 1
Due: Week 3
Weighting: 5%
Questions to be solved at home on the concepts contained within learning outcome 1 and to be submitted electronically to iLearn.
Assignment 2
Due: Week 6
Weighting: 7%
Questions to be solved at home on the concepts contained within learning outcome 2 and to be submitted electronically to iLearn.
Assignment 3
Due: Week 9
Weighting: 9%
Questions to be solved at home on the concepts contained within learning outcome 3 and to be submitted electronically to iLearn.
Assignment 4
Due: Week 12
Weighting: 9%
Questions to be solved at home on the concepts contained within learning outcome 4 and to be submitted electronically to iLearn
Final Exam
Due: Will appear in Exam Calendar
Weighting: 50%
A closed-book 3-hour exam will be conducted in the formal examination period.
Assessment Tasks
| Name | Weighting | Hurdle | Due |
|---|---|---|---|
| Laboratory | 20% | No | Weekly (starts in week 2) |
| Assignment 1 | 5% | No | Week 3 |
| Assignment 2 | 7% | No | Week 6 |
| Assignment 3 | 9% | No | Week 9 |
| Assignment 4 | 9% | No | Week 12 |
| Final exam | 50% | Yes | Based on the exam calender |
Laboratory
Due: Weekly (starts in week 2)
Weighting: 20%
At the end of each laboratory session, there will be an assignment to test the students understanding about the concepts of that session.
On successful completion you will be able to:
- Demonstrate a good understanding of the different types of data confronting engineers and the methods of data visualisation.
- To apply mathematics, physics and engineering principles to the analysis of measured data.
- Demonstrate knowledge of data acquisition systems, noise and error analysis.
- Demonstrate knowledge in engineering through the relationship between theoretical, mathematical and computational modelling to solve real world and dynamical problems. and
Assignment 1
Due: Week 3
Weighting: 5%
Assignment 1: On learning out come 1
On successful completion you will be able to:
- Demonstrate a good understanding of the different types of data confronting engineers and the methods of data visualisation.
Assignment 2
Due: Week 6
Weighting: 7%
Assignment 2: On learning out come 2
On successful completion you will be able to:
- To apply mathematics, physics and engineering principles to the analysis of measured data.
Assignment 3
Due: Week 9
Weighting: 9%
Assignment 3: On learning outcome 1
On successful completion you will be able to:
- Demonstrate knowledge of data acquisition systems, noise and error analysis.
Assignment 4
Due: Week 12
Weighting: 9%
Assignment 4 on learning out come 3
On successful completion you will be able to:
- Demonstrate knowledge in engineering through the relationship between theoretical, mathematical and computational modelling to solve real world and dynamical problems. and
Final exam
Due: Based on the exam calender
Weighting: 50%
This is a hurdle assessment task (see assessment policy for more information on hurdle assessment tasks)
3 hours close book exam
On successful completion you will be able to:
- Demonstrate a good understanding of the different types of data confronting engineers and the methods of data visualisation.
- To apply mathematics, physics and engineering principles to the analysis of measured data.
- Demonstrate knowledge of data acquisition systems, noise and error analysis.
- Demonstrate knowledge in engineering through the relationship between theoretical, mathematical and computational modelling to solve real world and dynamical problems. and
Delivery and Resources
Text books:
ENG255 book, from McGrawHill. Link is available on iLearn.
Technology used and required
• Library and internet search engines
• Word processing package
• MATLAB
• Excel
• LabVIEW
Learning and Teaching Activities
Practicals
Assignments
Policies and Procedures
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/strategy-planning-and-governance/university-policies-and-procedures/policies/special-consideration
In addition, a number of other policies can be found in the Learning and Teaching Category of Policy Central.
Student Code of Conduct
Macquarie University students have a responsibility to be familiar with the Student Code of Conduct: https://students.mq.edu.au/support/student_conduct/
Results
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.
Student Support
Macquarie University provides a range of support services for students. For details, visit http://students.mq.edu.au/support/
Learning Skills
Learning Skills (mq.edu.au/learningskills) provides academic writing resources and study strategies to improve your marks and take control of your study.
Student Services and Support
Students with a disability are encouraged to contact the Disability Service who can provide appropriate help with any issues that arise during their studies.
Student Enquiries
For all student enquiries, visit Student Connect at ask.mq.edu.au
IT Help
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.
Graduate Capabilities
Creative and Innovative
Our graduates will also be capable of creative thinking and of creating knowledge. They will be imaginative and open to experience and capable of innovation at work and in the community. We want them to be engaged in applying their critical, creative thinking.
This graduate capability is supported by:
Learning outcomes
- Demonstrate a good understanding of the different types of data confronting engineers and the methods of data visualisation.
- To apply mathematics, physics and engineering principles to the analysis of measured data.
- Demonstrate knowledge of data acquisition systems, noise and error analysis.
- Demonstrate knowledge in engineering through the relationship between theoretical, mathematical and computational modelling to solve real world and dynamical problems. and
Assessment tasks
- Laboratory
- Assignment 1
- Assignment 2
- Assignment 4
- Final exam
Capable of Professional and Personal Judgement and Initiative
We want our graduates to have emotional intelligence and sound interpersonal skills and to demonstrate discernment and common sense in their professional and personal judgement. They will exercise initiative as needed. They will be capable of risk assessment, and be able to handle ambiguity and complexity, enabling them to be adaptable in diverse and changing environments.
This graduate capability is supported by:
Assessment tasks
- Assignment 2
- Assignment 3
- Assignment 4
Discipline Specific Knowledge and Skills
Our graduates will take with them the intellectual development, depth and breadth of knowledge, scholarly understanding, and specific subject content in their chosen fields to make them competent and confident in their subject or profession. They will be able to demonstrate, where relevant, professional technical competence and meet professional standards. They will be able to articulate the structure of knowledge of their discipline, be able to adapt discipline-specific knowledge to novel situations, and be able to contribute from their discipline to inter-disciplinary solutions to problems.
This graduate capability is supported by:
Assessment tasks
- Laboratory
- Final exam
Critical, Analytical and Integrative Thinking
We want our graduates to be capable of reasoning, questioning and analysing, and to integrate and synthesise learning and knowledge from a range of sources and environments; to be able to critique constraints, assumptions and limitations; to be able to think independently and systemically in relation to scholarly activity, in the workplace, and in the world. We want them to have a level of scientific and information technology literacy.
This graduate capability is supported by:
Learning outcomes
- Demonstrate a good understanding of the different types of data confronting engineers and the methods of data visualisation.
- To apply mathematics, physics and engineering principles to the analysis of measured data.
- Demonstrate knowledge of data acquisition systems, noise and error analysis.
- Demonstrate knowledge in engineering through the relationship between theoretical, mathematical and computational modelling to solve real world and dynamical problems. and
Assessment tasks
- Laboratory
- Assignment 1
- Assignment 2
- Assignment 3
- Assignment 4
- Final exam
Problem Solving and Research Capability
Our graduates should be capable of researching; of analysing, and interpreting and assessing data and information in various forms; of drawing connections across fields of knowledge; and they should be able to relate their knowledge to complex situations at work or in the world, in order to diagnose and solve problems. We want them to have the confidence to take the initiative in doing so, within an awareness of their own limitations.
This graduate capability is supported by:
Learning outcomes
- Demonstrate a good understanding of the different types of data confronting engineers and the methods of data visualisation.
- To apply mathematics, physics and engineering principles to the analysis of measured data.
- Demonstrate knowledge of data acquisition systems, noise and error analysis.
- Demonstrate knowledge in engineering through the relationship between theoretical, mathematical and computational modelling to solve real world and dynamical problems. and
Assessment tasks
- Laboratory
- Assignment 1
- Assignment 2
- Assignment 3
- Assignment 4
- Final exam
Effective Communication
We want to develop in our students the ability to communicate and convey their views in forms effective with different audiences. We want our graduates to take with them the capability to read, listen, question, gather and evaluate information resources in a variety of formats, assess, write clearly, speak effectively, and to use visual communication and communication technologies as appropriate.
This graduate capability is supported by:
Assessment task
- Laboratory