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ETM1030 · Mathematical statistics

Official Handbook

2026 Handbook6 credit pointsLevel 1Department of Econometrics and Business Statistics

Last checked: 23 Aug 2026 UTC

Overview

In this unit, you will be exposed to a comprehensive study of statistical methods and data analysis. Specifically, you will be introduced to the essential concepts and techniques in probability and statistical methods to equip you with the skills needed to extract meaningful insights from data. You will be given a robust foundation in data analysis, probability distributions, generating functions, joint distributions, conditional expectation, and the central limit theorem. The curriculum extends to cover crucial aspects of statistical inference, including sampling, point estimation, confidence intervals, hypothesis testing, the concepts of Bayesian statistics, and Bayesian estimators, and the applications of these methods in solving real-world problems. Upon unit completion, you will develop the ability to apply statistical methodologies in practical scenarios which will prepare you for the challenges of actuarial analytics and provide sufficient expertise for use in various later units.

Offerings

CampusTeaching periodMode
MalaysiaSecond semesterTeaching activities are on-campus (ON-CAMPUS)
MalaysiaFirst semesterTeaching activities are on-campus (ON-CAMPUS)

Assessment

The Handbook lists an examination for this unit.

#AssessmentTypeWeightHurdle
11 - WrittenWritten40%
22 - Quiz / TestQuiz / Test20%
33 - ExaminationExamination40%

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

Requisites

prohibitions

  • ETB1100 — Business statistics
  • ETC1000 — Business and economic statistics
  • ETF1100 — Business statistics
  • ETW1001 — Introduction to statistical analysis
  • ETW2001 — Foundations of data analysis
  • ETX1100 — Business statistics
  • FIT1006 — Business information analysis
  • SCI1020 — Introduction to statistical reasoning
  • STA1010 — Statistical methods for science

Joined by OR.

Learning outcomes

  1. use appropriate statistical analysis, descriptive statistics and graphical presentation to summarise data
  2. describe the essential features of statistical distributions
  3. apply the principles of statistical inference
  4. apply the fundamental concepts of Bayesian statistics to compute Bayesian estimators.

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.

ActivityDuration
Tutorials24 hours

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