ETC2420 Statistical thinking
Faculty of Business and Economics
ETC2420 Statistical thinking is a level 2, 6-credit-point, undergraduate unit from the Faculty of Business and Economics, offered in 2022 in Semester 2 at Clayton. It needs ETW1001, ETX1100, ETB1100, FIT1006, ETC1000, SCI1020, ETF1100 or STA1010 and unlocks 11 units, leading on to 16 units in all.
- Credit points
- 6
- Offered in 2022
- Semester 2
- Clayton
- Assessment
- Exam 45%
- and 1 other task
- Workload
- 144 hours
- per semester
This is the 2022 handbook entry. See the 2027 entry.
Reviews
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Requisites
Before ETC2420
Prerequisites
Pass these before you enrol.
- ETW1001Introduction to statistical analysisNo reviews yet
- ETX1100Business statisticsNo reviews yet
- ETB1100Business statisticsNo reviews yet
- FIT1006Business information analysisNo reviews yet
- ETC1000Business and economic statisticsNo reviews yet
- SCI1020Introduction to statistical reasoningNo reviews yet
- ETF1100Business statisticsNo reviews yet
- STA1010Statistical methods for scienceNo reviews yet
After ETC2420
11 units list ETC2420 as a prerequisite or corequisite.
- ETC3250Introduction to machine learningNo reviews yet
- ETC3420Applied insurance methodsNo reviews yet
- ETC3550Applied forecastingNo reviews yet
- ETC3580Advanced statistical modellingNo reviews yet
- ETC5250Introduction to machine learningNo reviews yet
- ETC5342Applied insurance methodsNo reviews yet
- ETC5550Applied forecastingNo reviews yet
- ETF3231Business forecastingNo reviews yet
Enrolment rules
To be successful in this unit, background knowledge and application of maths is required at the equivalent of VCE Year 12 Higher level. You may have satisfied this by completing relevant prerequisite unit/s, or you have covered relevant topics in your final years of secondary study. You should self-assess your maths competency prior to enrolling in this unit.
Equivalent units
The same content under another code. Only one of them counts.
Overview
This unit focuses on the tools for a large, digital data world, including the building blocks for business analytics, modern insurance and risk assessment. A computational approach is employed to teach the concepts of statistics, and decision making in the presence of uncertainty. Topics covered will include exploratory data analysis, simulation and randomisation methods, Bayesian analysis, decision and credibility theory, and model assessment.
Offerings in 2022
| Teaching period | Campus | Mode |
|---|---|---|
| Second semester | Clayton | On campus |
Assessment
- Within semester assessment55%
- Examination45%
Learning outcomes
When you finish this unit, you should be able to:
- 1
characterise the variability in data
- 2
build statistical models to support decision-making and risk assessment
- 3
use randomisation methods to assess uncertainty in relation to parameter estimates, hypothesis testing, predictions and model assessments
- 4
explain the basic concepts of Bayesian analysis and credibility theory, and be able to implement them in conjugate settings
- 5
explain the differences between the frequentist and Bayesian frameworks
- 6
develop computing and communication skills, using reproducible reporting.
Workload and teaching
- Lectures24 hours
- Tutorials24 hours
- Teaching approachProblem-based learning
- Teaching approachCase-based teaching
- Teaching approachActive learning
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 three/four hours of scheduled activities per week. Scheduled activities may include a combination of teacher directed learning, peer directed learning and online engagement.
This unit includes problem-based learning approaches, where you engage in research, integrate theory and practice and apply knowledge and skills to develop viable solutions in response to a problem or set of problems.
This unit includes case-based teaching, where you apply your knowledge and engage in analytical and reflective thinking to solve complex contextual scenarios. Activities are often designed so that there is not one clear answer, but you need to work together to examine, analyse and make decisions to resolve the situation.
This unit engages you in actively applying your knowledge, skills and attributes in interactive, collaborative and reflective activities.
Where it fits
ETC2420 is part of 6 areas of study in the 2022 handbook.
- ACTRLSTD02Core unitsActuarial studiesNo reviews yet
- ACTRLSTD06Core unitsActuarial studiesNo reviews yet
- BUSANLMJ01Core unitsBusiness analyticsNo reviews yet
- BUSANLYT05ClaytonBusiness analyticsNo reviews yet
- ECONOMTR02Core unitsEconometricsNo reviews yet
- ECONOMTR05Additional econometrics unitsEconometricsNo reviews yet
Contacts
- Chief Examiners
- Professor Brett Inder
Common questions
What are the prerequisites for ETC2420?
You need ETW1001, ETX1100, ETB1100, FIT1006, ETC1000, SCI1020, ETF1100 or STA1010 before you enrol. Enrolment rules also apply.
What can I take after ETC2420?
ETC2420 is a prerequisite or corequisite for 11 units, including ETC3250, ETC3420, ETC3550, ETC3580, ETC5250 and ETC5342. Those lead on to 16 units in all.
When is ETC2420 offered?
In 2022, ETC2420 runs in Semester 2 at Clayton.
How much work is ETC2420?
The handbook expects about 144 hours of study across the semester. No students have rated its difficulty yet.
Does ETC2420 have an exam?
Yes. The exam is worth 45% of the final mark, alongside 1 other task.
Which majors and minors include ETC2420?
ETC2420 is part of Actuarial studies, Business analytics and Econometrics.