MIS771 - Descriptive Analytics and Visualisation

Unit details

Year:

2024 unit information

Enrolment modes:

Trimester 1: Burwood (Melbourne), Online
Trimester 2: Burwood (Melbourne), Online
Trimester 3: Burwood (Melbourne), Online, GIFT City (India)^

Credit point(s):1
EFTSL value:0.125
Previously coded as:MSQ791
Assumed Knowledge:

The unit assumes students have already completed foundational study in statistics at undergraduate level and have some familiarity with basic statistical concepts and inferential techniques. In particular, understanding of descriptive statistics and structure of probability is necessary.

Unit Chair:Trimester 1: Dilal Saundage
Trimester 2: Scott Salzman
Trimester 3: Arman Kaldi
Prerequisite:

MIS770, MIS770A

Corequisite:Nil
Incompatible with: MAF256
Typical study commitment:

Students will on average spend 150 hours over the teaching period undertaking the teaching, learning and assessment activities for this unit.

This will include educator guided online learning activities within the unit site.

Educator-facilitated (scheduled) learning activities - on-campus unit enrolment:

1 x 2 hour on-campus (livestreamed) lecture (recordings provided) and 1 x 1 hour on-campus practical experience (laboratory) each week

Educator-facilitated (scheduled) learning activities - online unit enrolment:

1 x 2 hour recorded lecture provided and 1 x 1 hour online seminar (recordings provided) each week

Note:

^GIFT City (India) offering is available to students enrolled at the GIFT City (India) campus only.

Content

This unit focuses on the techniques and approaches to analysing business data to support decision making. It covers exploratory data analysis, visualisation of data and evidence-based decision making. The unit aims to give students a broad understanding of statistical approaches used to support business decisions, their limitations, typical application areas, managerial reporting of statistical results and incorporating insights into the business decision-making process. Extensive use is made of software to develop data visualisation and analysis skills and to enhance the appreciation of various techniques studied. The unit assumes students have already completed foundational study in statistics at undergraduate level and have some familiarity with basic statistical concepts and inferential techniques. In particular, understanding of descriptive statistics and structure of probability is necessary.

ULO These are the Learning Outcomes (ULO) for this unit. At the completion of this unit, successful students can: Deakin Graduate Learning Outcomes
ULO1

Solve complex problems using quantitative reasoning skills.

GLO1: Discipline-specific knowledge and capabilities
GLO5: Problem-solving
ULO2

Plan, monitor, and evaluate own learning as an analytics professional.

GLO6: Self-management
ULO3

Communicate solutions that inform decision-making and ongoing research to a variety of stakeholders.

GLO1: Discipline-specific knowledge and capabilities
GLO2: Communication

Assessment

Assessment Description Student output Grading and weighting
(% total mark for unit)
Indicative due week
Assessment 1: (Individual) Case Study:  

Part A: Data Analysis
Part B: Report (Analytical)

Part A: Data analysis file
Part B: 1500 words
Part A: 10%
Part B: 20%
Week 5

Assessment 2: (Individual) Case Study:  

Part A: Data Analysis
Part B: Report (Analytical)

Part A: Data analysis file
Part B: 1500 words
Part A: 15%
Part B: 20%
Week 9

Assessment 3 

(Individual) Case Study: 

Part A: Interactive Dashboard
Part B: Web Report
Part C: Written Reflection (Self) 

Part A: Data analysis file
Part B: 1000 words
Part C: 500 words
Part A: 15%
Part B: 10%
Part C: 10%
Week 13

The assessment due weeks provided may change. The Unit Chair will clarify the exact assessment requirements, including the due date, at the start of the teaching period.

Learning Resource

The texts and reading list for the unit can be found on the University Library via the link below: MIS771 Note: Select the relevant trimester reading list. Please note that a future teaching period's reading list may not be available until a month prior to the start of that teaching period so you may wish to use the relevant trimester's prior year reading list as a guide only.

Unit Fee Information

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