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

S1-01-MALAYSIA-ON-CAMPUS

S2-01-MALAYSIA-ON-CAMPUS

Requisites

Prerequisite

Prohibition

Rules

Enrolment Rule

Contacts

Chief Examiner(s)

Professor Erniel Bayhon Barrios

Learning outcomes

On successful completion of this unit, you should be able to:

recognise uncertainty as basic element in statistical science

characterise and articulate various paradigms of inference in statistical analysis

identify strength and limitations of different estimation procedures and approaches in hypothesis testing in statistical analysis

develop statistical thinking process in the conduct of statistical analysis.

Teaching approach

Research activities

Active learning

Enquiry-based learning

Problem-based learning

Assessment

1 - Within semester assessment

Scheduled and non-scheduled teaching activities

Tutorials

Workload requirements

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.