ETC2420 · Statistical thinking

Overview

This unit presents data analysis, statistical modelling and decision-making in the presence of uncertainty, using a computational approach. You will use different frameworks of probability that are helpful for analysing real-world problems. Topics covered will include probability distributions, statistical inference (classical & Bayesian), simulation, permutation and randomisation methods, regression models, decision theory, and model assessment and diagnosis.

Offerings

Assessment

The Handbook lists an examination for this unit.

Assessment details may change. Please refer to the assessment information in Moodle closer to the start of the teaching period.

Requisites

Learning outcomes

1. characterise and understand uncertainty using data
2. build statistical models to support decision-making, hypothesis testing and risk assessment
3. use randomisation methods in data collection and to assess causality and uncertainty
4. learn about and use concepts from probability
5. understand Bayesian and frequentist approaches to statistical modelling
6. further develop computational skills for statistical analysis.

Workload

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. You are expected to complete all pre-class activities prior to your scheduled class, and post-class activities should be completed after your scheduled class. Learning activities may include a combination of teacher directed, peer directed and online engagement activities.

Student experience, not official rules. Nothing here changes what the Handbook says.