Unit Guide
Data visualisation and analytics
Summer semester B, 2020
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Handbook link:
http://monash.edu.au/pubs/2020handbooks/units/ETX2250.html
The information contained in this unit guide is correct at time of publication. The University has the right to change any of the elements contained in this document at any time.
Last updated: 19 Dec 2019
Table of contents
ETX2250 Data visualisation and analytics – Summer semester B (SSB-01) – 2020
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Table of contents
Unit handbook information 4 Synopsis 4 Mode of delivery 4 Workload requirements 4 Unit relationships 4
Prerequisites 4 Prohibitions 4 Co-requisites 4 Enrolment rules 5
Chief Examiner 5 Unit Coordinator(s) 5 Academic overview 5 Unit learning outcomes 5 Teaching approach 5 Recording of lectures 6 Unit schedule 7 Assessment summary 8 Second marking 8 Return of final marks 8 Exam viewing 8 Assessment criteria 9 Assessment requirements 9 Hurdle requirement 9 Assessment tasks 9 ETX2250/ETF5922 Data Visualisation and Analytics 11 Referencing requirements 11 Feedback 12 Bring your own device 12 Learning resources 12 Required resources 12 Technological requirements 13 Q Manual 13 Prescribed text and readings 13 Other information 13 Policies 13
ETX2250 Data visualisation and analytics – Summer semester B (SSB-01) – 2020
Student Academic Integrity Policy 13 Special Consideration 14 Graduate Attributes Policy 14 Student Charter 14 Student Services 14 Monash University Library 14 Disability Support Services 14
ETX2250 Data visualisation and analytics – Summer semester B (SSB-01) – 2020
Programming Help, Add QQ: 749389476
Unit handbook information
Business analytics can unlock the hidden insights in data to give businesses a competitive advantage. Many businesses have masses of data about customers and operations, and need skilled analysts to uncover insights and make informed predictions.
This unit uses data visualisation to explore and analyse data sets of all sizes, and it introduces some business analytic models for interpretation and prediction.
It will introduce an appropriate software environment for data visualisation, and analytics, and cover visualisation and analysis techniques for categorical and numerical variables. Visualisation methods to be covered include some of Box-and-whisker plots, Mosaics, Rotatable 3D scatter plots, Heat maps, Motion charts, cluster and association charts. Models to be covered may include linear regression models, classification and regression trees, and random forests. Methods for evaluating model performance will also be discussed. Examples from marketing, finance, economics and related disciplines will be included.
Mode of delivery
Caulfield (On-campus block of classes)
Workload requirements
Minimum total expected workload to achieve the learning outcomes for this unit is 144 hours per semester typically comprising a mixture of scheduled learning activities and independent study. Independent study may include associated readings, assessment and preparation for scheduled activities. The unit requires on average four hours of scheduled activities per week when taught in trimester mode, and three to four hours three times per week when taken as a summer unit. Scheduled activities may include a combination of teacher directed learning, peer directed learning and online engagement.
Unit relationships
Prerequisites
ETC1000 or SCI1020 or ETS1102 or FIT1006 or ETW1100 or ETF1100 or STA1010 or ETW1000
Prohibitions
Co-requisites
ETX2250 Data visualisation and analytics – Summer semester B (SSB-01) – 2020
Enrolment rules
Chief Examiner
Name: Dr Klaus Ackermann
Campus: Clayton
Phone: +61 3 990 54695
Unit Coordinator(s)
Name: Dr Klaus Ackermann
Campus: Clayton
Email: Phone: +61 3 990 54695
Academic overview
Unit learning outcomes
On successful completion of this unit you should be able to:
1. select, create and interpret appropriate types of visual representation for a given set of data
2. select and develop model types with explanatory and/or predictive ability
3. make appropriate use of in-sample and out-of-sample evaluation of models
4. apply the above research skills to produce innovative solutions in finance, marketing, economics and related areas
5. use visualisation and modelling to effectively communicate the results of their investigations
6. explain the sequence of procedures that should be applied to analyse a given dataset.
Teaching approach
Active learning in workshops with team teaching
ETX2250 Data visualisation and analytics – Summer semester B (SSB-01) – 2020
Active learning in workshops with team teaching
Recording of lectures
As this unit does not have lectures or seminars, there are no recordings made of face-to-face classes.
ETX2250 Data visualisation and analytics – Summer semester B (SSB-01) – 2020
Unit schedule
For units with on-campus classes, teaching activities are normally scheduled to start on the hour (teaching will commence on the hour and conclude 10 minutes prior to the scheduled end time).
Students should note that the program outlined below is a guide to the material to be covered in this unit and not a definitive statement of when that material will be covered. Specific details relating to the timing will be discussed in class.
Day Topics and Activities Assessment
1 Introduction to the unit and to R Participation
2 Concepts in data visualisation Participation and implementation in R
3 Concepts in data visualisation Participation and implementation in R
4 Concepts in data visualisation Participation / Assignment 1 due and implementation in R
5 Concepts in data visualisation Participation and implementation in R
6 Concepts in data visualisation Participation and implementation in R
7 Hierarchical Clustering Participation
8 K-Means Clustering Participation / Assignment 2 due
9 Association Analysis Participation
10 Classification trees Participation
11 Regression trees Participation
12 Review Participation / Assignment 3 due
Calendar for class days
Day 01: Day 02: Day 03: Day 04: Day 05: Day 06: Day 07:
Monday, 6.1.2020 Wednesday, 8.1.2020 Friday, 10.1.2020 Monday, 13.1.2020 Wednesday, 15.1.2020 Friday, 17.1.2020 Monday, 20.1.2020
Day 08: Wednesday, 22.1.2020
ETX2250 Data visualisation and analytics – Summer semester B (SSB-01) – 2020
Day 07: Monday, 20.1.2020
Day 08: Day 09: Day 10: Day 11: Day 12:
Wednesday, 22.1.2020
Friday, 24.1.2020
Tuesday, 28.1.2020 (after Australia day) Wednesday, 29.1.2020
Friday, 31.1.2020
Class 9am – 12pm, Day 1-Day 12
Assessment summary
Within semester assessment: 50% + Examination: 50%
Assessment task Value Due date
Assignment 1 10% Day 4 (13 January)
Assignment 2 15% Day 8 (22 Janaury 2020)
Assignment 3 15% Day 12 (31 January)
Participation – Flux Polls 10% Day 2-11
ETX2250/ETF5922 Data Visualisation and Analytics 50% To be advised
A student’s final mark is normally the sum of the marks obtained in all of the individual assessment items in the unit.
Second marking
In the Faculty of Business and Economics, all of the following assessment items graded as a fail by the first marker are blind marked by a second marker:
● examination papers
● in-semester assessment items worth 20% or more
Return of final marks
Faculty policy states that ‘the final mark that a student receives for a unit will be determined by the Board of Examiners taking into account all aspects of assessment’.
The final mark for this unit will be released by the Board of Examiners on the date nominated in the Faculty Calendar. Student results will be accessible through the my.monash portal.
Exam viewing
Feedback on student performance in examinations and other end-of-semester assessment is required. The feedback should be in accordance with the University’s procedures on Unit Assessment. Details of the examination script viewing arrangements set down by the Faculty of
Business and Economics are available at https://www.monash.edu/business/current-students ETX2250 Data visualisation and analytics – Summer semester B (SSB-01) – 2020
Business and Economics are available at https://www.monash.edu/business/current-students /forms-and-guidelines/policies-and-procedures/examination-feedback-procedure
Assessment criteria
Assessment Criteria Grading Descriptors available at:
https://www.monash.edu/__data/assets/pdf_file/0006/801690/Assessment-in-Coursework-Units- Grading-and-Marking-Procedures.pdf
Assessment requirements
Hurdle requirement
There is a hurdle requirement in this unit. The hurdle requirement is that students must attain a mark of at least 50% in the Final Exam / Final Major Assessment Task. A student’s final mark is normally the sum of the marks obtained in all of the assessment tasks in the unit. Where a student does not meet the hurdle requirement, the maximum mark that may be returned for the unit is 48.
Assessment tasks
Assessment task title: Assignment 1
Due Date: Day 4 (13 January)
Weighting/Value: 10%
Details of Task: Visualising and modifying data sets using R Release date: Day 1 (6 January 2020)
Word limit: TBA
Presentation requirements: Jupyter R notebook file
Estimated return date: 22 January
Criteria for marking: Marking criteria will be provided on the question paper Learning objectives assessed: 1
Submission details: Submit the digital file through Moodle.
Penalties for late lodgement: 30% for each day late
Assessment coversheet: Appropriate cover sheets will be provided on Moodle. Additional information: Additional information will be supplied with question paper.
Assessment task title: Assignment 2
Due Date: Day 8 (22 Janaury 2020)
Weighting/Value: 15%
Details of Task: Visualising and describing data sets using R Release date: Day 4 (13 January 2020)
Word limit: TBA
Presentation requirements: Document as PDF – details to be provided on question paper. Estimated return date: 31 January
Criteria for marking: Marking criteria will be provided on the question paper
Learning objectives assessed: 1,6
ETX2250 Data visualisation and analytics – Summer semester B (SSB-01) – 2020
Learning objectives assessed: 1,6
Submission details: Submitted in as a soft copy through Moodle.
Penalties for late lodgement: 30% for each day late
Assessment coversheet: Appropriate cover sheets will be provided on Moodle. Additional information: Additional information will be supplied with question paper.
Assessment task title: Assignment 3
Due Date: Day 12 (31 January)
Weighting/Value: 15%
Details of Task: Applying analytics methods to a dataset. Release date: Day 8 (21 January)
Word limit: NA
Presentation requirements: Document as PDF – details to be provided on question paper. Estimated return date: TBA
Criteria for marking: Supplied on question paper
Learning objectives assessed: 2,3,4,5,6
Submission details: Submitted in as a soft copy through Moodle.
Penalties for late lodgement: Except where you are eligible for within-semester special consideration, no late assignments will be accepted. In the case of severe illness or other exceptional circumstances, you may submit a special consideration form which can be found at http://www.monash.edu/connect/forms
Assessment coversheet: Provided on Moodle
Additional information: Will be supplied on question paper
Assessment task title: Participation – Flux Polls Due Date: Day 2-11
Weighting/Value: 10%
Details of Task:
Students will be required to complete in-workshop polls.
Release date: Day 2-11
Word limit: NA
Presentation requirements: n/a
Estimated return date: 2 days after submission Criteria for marking: Supplied with each task. Learning objectives assessed:
All Learning Objectives
Submission details:
During the workshop
Penalties for late lodgement:
No late lodgement is possible.
ETX2250 Data visualisation and analytics – Summer semester B (SSB-01) – 2020
Assessment coversheet: n/a Additional information:
A wifi enabled laptop or smart device is required to complete this task in workshops.
The overall mark for this assessment category will be determined using a ‘best of’ approach.
Of the n assessments in the category, the final mark will use the best (i.e., highest) (n-1) assessments to calculate your final mark in this assessment category.
This implies that for each assessment in this category one submission may be omitted for students who are absent without documented reasons/medical certificates.
You will get zero marks if you do not enter your name and Monash student authcate correctly (as required).
ETX2250/ETF5922 Data Visualisation and Analytics
This unit may employ electronic assessment for the final exam. Further details will be provided to you by Week 4 of Semester.
Weighting: 50%
Length: 2 hours with 10 minutes reading time Type (open/closed book): closed book
Exam details:
The learning outcomes in this unit require students to demonstrate in the final summative assessment task a comprehensive understanding of topics covered in the unit. This is demonstrated by the requirement that the student must attain a mark of at least 50% in the final examination. There will be a two-hour closed book exam during the official summer examination period. Students will find it useful to have a calculator (which must be HP10bII+), and also a ruler.
Electronic devices allowed in the exam:
Calculators are permitted in the exam. The only Faculty approved calculators permitted in tests and examinations for all Australian campuses and locations is the HP10bII+ or Casio FX82 (any suffix). Students are required to purchase their own calculator and are responsible for ensuring the calculator is in good working order and to have a set of spare batteries.
Referencing requirements
ETX2250 Data visualisation and analytics – Summer semester B (SSB-01) – 2020
To build your skills in citing and referencing, and using different referencing styles, see the online tutorial Academic Integrity: Demystifying Citing and Referencing at http://www.lib.monash.edu /tutorials/citing/
Our feedback to you
Types of feedback you can expect to receive in this unit are:
● Formal individual feedback on assignments expressed as a letter grade
● Answers to questions relating to the discipline or the unit’s work
● Advice about seeking additional help to develop your writing or research skills
● Informal feedback relating to class activities
Your feedback to us
One of the formal ways students have to provide feedback on teaching and their learning experience is through the Student Evaluation of Teaching and Units (SETU) survey. The feedback is anonymous and provides the Faculty with evidence of aspects that students are satisfied with and areas for improvement.
Previous student evaluations of this unit
In response to previous SETU results of this unit, the following changes have been made:
In response to previous comments, readings will be recommended for each workshop.
If you wish to view how previous students rated this unit, please go to:
https://www.monash.edu/ups/setu/about/setu-results/unit-evaluation-reports
Bring your own device
Please note: This is a bring your own device unit. You will be expected to bring a web-connected device to class to access specialist software. The applications for your class can be accessed at the website move.monash.edu
For more information, visit monash.edu/move Learning resources
Monash Library Unit Reading List (if applicable to the unit): http://monash.rl.talis.com/index.html Research and Learning Online: www.monash.edu/rlo
Required resources
ETX2250 Data visualisation and analytics – Summer semester B (SSB-01) – 2020
Students generally must be able to complete the requirements of their course without the imposition of fees that are additional to the student contribution amount or tuition fees. However, students may be charged certain incidental fees or be expected to make certain purchases to support their study. For more information about this, refer to the Higher Education Administrative Information for Providers, Chapter 18, Incidental Fees at http://education.gov.au/help-resources- providers
Students will want to use their own laptop in the class and assignments. However, some lab space will be available for private study and tutor consultation on the afternoons of class days.
Technological requirements
Virtual learning environment (VLE): Moodle
Material used in class together with other information of importance to you will be published online via the unit’s Moodle site. In order to access information about this unit in Moodle you must be enrolled in the unit and have a valid student account with authcate username and password. Moodle can be accessed through my.monash portal by clicking on the Moodle link under “Online systems”. If you need some help with Moodle then check out the Moodle Support for Students page.
Work submitted for assessment must be consistent with the guidelines set down in the Q Manual, which is the faculty’s student guide for producing quality work on time. Copies of this manual can be purchased at the bookshop or accessed online at https://www.monash.edu/business/current- students/study-resources/qmanual.pdf
Prescribed text and readings
Shmueli, Galit, Peter C. Bruce, Inbal Yahav, Nitin R. Patel, and Kenneth C. Lichtendahl Jr. Data mining for business analytics: concepts, techniques, and applications in R. John Wiley & Sons, 2017.
Other information
Monash has educational policies, procedures and guidelines, which are designed to ensure that staff and students are aware of the University’s academic standards, and to provide advice on how they might uphold them. You can find Monash’s Education Policies at: http://www.policy.monash.edu/policy-bank/academic/education/index.html
Student Academic Integrity Policy
ETX2250 Data visualisation and analytics – Summer semester B (SSB-01) – 2020
www.monash.edu/__data/assets/pdf_file/0004/801841/Student-Academic-Integrity-Policy.pdf
Special Consideration
For information on applying for special consideration, please visit: http://www.monash.edu/exams /changes/special-consideration
Graduate Attributes Policy
http://www.monash.edu/policy-bank/academic/education/course-governance-and-design/course- design-policy
Student Charter
www.monash.edu/students/policies/student-charter.html
Student Services
The University provides many different kinds of services to help you gain the most from your studies. Further information is available at www.monash.edu/students
You can also access important information from the Faculty of Business and Economics current students page https://www.monash.edu/business/current-students
English Connect provide services to improve and develop your language skills with workshops and programs, including online English Connect Grammar Resources, Let’s Chat conversational and oral skills group sessions, workshops on oral presentation and public speaking skills (Speaking with Confidence) and grammar for academic English (Polish Up Your Grammar). Peer Support (one on one service) runs out of the Library and is to assist you with written assignments. You can register or gain more information at http://www.monash.edu/english-connect
Monash University Library
The Monash University Library provides a range of services, resources and programs that enable you to save time and be more effective in your learning and research.
Go to http://www.monash.edu/library or the library tab in my.monash portal for more information.
Disability Support Services
Students who have a disability, ongoing medical or mental health condition should contact Disability Support Services.
Disability Support Services also support students who are carers of a person who is aged and frail or has a disability, medical condition or mental health condition.
Disability Support Services will assess each student and recommend reasonable adjustment to teaching and assessment practices.
For within semester assessment activities, it is the students responsibility to provide confirmation of their requirement for alternative arrangements to the Chief Examiner or appropriate faculty
contact person responsible for administering the arrangements no later than two week before the
ETX2250 Data visualisation and analytics – Summer semester B (SSB-01) – 2020
contact person responsible for administering the arrangements no later than two week before the assessment.
For mid semester tests being conducted at the Caulfield Racecourse, DSS provide the adjustments (eg larger font) and instructions to Exams Branch.
https://www.monash.edu/__data/assets/pdf_file/0004/801616/Assessment-in-Coursework-Units- Adjustments-to-Assessment-Procedures.pdf
Students Disability Advisers visit all Victorian campuses on a regular basis.
● Australian Campus Website: monash.edu/disability
● Monash Malaysia Website: https://www.monash.edu.my/student-services/support-services
/disability-support
● Monash South Africa Website: https://www.iiemsa.co.za/disability-support/
Copyright © Monash University 2020. All rights reserved. Except as provided in the Copyright Act 1968, this work may not be reproduced in any form without the written permission of the host Faculty and School/Department.
ETX2250 Data visualisation and analytics – Summer semester B (SSB-01) – 2020
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