ETM1030 - Mathematical statistics

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 … For more content click the Read More button below. 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.

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

S2-01-MALAYSIA-ON-CAMPUS

Requisites

Prohibition

STA1010

6 CP

Statistical methods for science

Business and economic statistics

Introduction to statistical analysis

ETW2001

6 CP

Foundations of data analysis

Business information analysis

SCI1020

6 CP

Introduction to statistical reasoning

Learning outcomes

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

use appropriate statistical analysis, descriptive statistics and graphical presentation to summarise data

describe the essential features of statistical distributions

apply the principles of statistical inference

apply the fundamental concepts of Bayesian statistics to compute Bayesian estimators.

Teaching approach

Problem-based learning

Active learning

Assessment

1 - Within semester assessment

2 - Examination

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.