ETM2100 · Principles of statistical inference

Overview

Uncertainty is the basic element of statistical science. Various theories and methods (including algorithms) in econometrics, business statistics, and business analytics focused on the understanding of uncertainty and its subsequent use in optimal decision-making. In this unit, you will learn different approaches in the conduct of statistical inference. Specifically, you will be exposed to various paradigms of estimation and hypothesis testing, their utilisation and limitations. Upon unit completion, you will also develop statistical thinking process, an important element that will contextualise your progression in the study of Econometrics and Business Statistics or in Business Analytics.

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. recognise uncertainty as basic element in statistical science
2. characterise and articulate various paradigms of inference in statistical analysis
3. identify strength and limitations of different estimation procedures and approaches in hypothesis testing in statistical analysis
4. develop statistical thinking process in the conduct of 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.