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Sample spaces, probability, random variables and probability distributions; examples of discrete and continuous distributions; Central Limit Theorem; statistical inference, confidence intervals and hypothesis testing; bivariate normal distribution, optimal mean square estimation, introduction to the multivariate normal distribution; linear regression and least squares estimation; inference in the linear model; on-line and off-line estimation; statistical quality control; models, applications and statistical algorithms relevant to the fields of computer, electrical, software and telecommunications engineering. Note: Available only to students for whom it is specifically required as part of their program.

Study Level


Offering Terms

Term 2



Delivery Mode

Fully on-site

Indicative contact hours


Conditions for Enrolment

Prerequisite: MATH1231 or MATH1241 or MATH1251 or DPST1014; Exclusion: MATH2089; MATH2099; MATH2801; MATH2901; BEES2041; BIOS2041.

Course Outline

To access course outline, please visit:


Pre-2019 Handbook Editions

Access past handbook editions (2018 and prior)

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