Overview

Introduction to probability - a mathematical treatment. Topics include: probability axioms, conditional probabilities and the law of total probability, discrete and continuous random variables, univariate and multivariate distributions, independence and conditioning, conditional distributions and conditional expectations, moment generating functions, simulation, the law of large numbers and the central limit theorem.

Offerings

S1-01-CLAYTON-ON-CAMPUS

Contacts

Chief Examiner(s)

Associate Professor Andrea Collevecchio

Unit Coordinator(s)

Dr Meng Shi

Learning outcomes

On successful completion of this unit, you should be able to:
1.

Understand the basic concepts of probability including conditioning and independence, univariate and multivariate probability distributions, expectations, generating functions and limit theorems;

2.

Appreciate the relevance of probability models to a variety of areas including Science, Engineering, Actuarial Science and Finance;

3.

Derive means, variances, moments and distributions in a variety of univariate and multivariate contexts;

4.

Use conditioning and moment generating functions to solve a variety of problems involving two or more events or random variables;

5.

Understand the way random numbers are generated;

6.

Formulate in probabilistic terms real-life situations involving uncertainty.

Assessment

1 - Continuous assessment
2 - Final assessment - Exam (3 hours and 10 minutes)

Scheduled and non-scheduled teaching activities

Applied sessions
Seminars

Workload requirements

Workload

Learning resources

Required resources

Other unit costs

Costs are indicative and subject to change.
Miscellaneous items required (unit course reader, printing, stationery) - $120

Availability in areas of study

Applied mathematics
Financial and insurance mathematics
Mathematical statistics
Mathematics
Pure mathematics