The University of Newcastle, Australia
Available in 2019

Course handbook

Description

Introduces key areas of statistical theory directly relevant to Engineering.

This course develops concepts of probability, random variables and their distributions, and shows how these ideas provide the theoretical foundation for data analysis through statistical modelling, estimation and hypothesis testing with a major emphasis on applications in electrical engineering and computer systems.


Availability2019 Course Timetables

Callaghan

  • Semester 2 - 2019

Learning outcomes

On successful completion of the course students will be able to:

1. Understand the basic concepts underlying probability and hypothesis testing.

2. Explain the underlying assumptions and the applicability of each of the approaches studied.

3. Use statistical models and statistical concepts including probability and hypothesis testing to solve engineering problems.

4. Apply linear algebra concepts and methods to statistical models.

5. Demonstrate an enhanced analytical ability.


Content

The course will include the following topics:

  • Sample space, events, axioms of probability and Bayes’ theorem
  • Random variables and their distributions: Univariate
  • Expected values and their properties
  • Functions of random variables
  • Vector and matrix calculations
  • Random vectors and joint distributions: Multivariate
  • Samples, sampling distributions and Central Limit Theorem
  • Hypothesis testing
  • Estimation
  • Simple linear regression models
  • Monte Carlo Simulation

Requisite

This course has similarities to STAT2010. If you have successfully completed STAT2010 you cannot enrol in this course.


Assumed knowledge

MATH1110 Mathematics for Engineering, Science and Technology 1

OR

MATH1120 Mathematics for Engineering, Science and Technology 2

OR

MATH1210 Mathematical Discovery 1

OR

MATH1220 Mathematical Discovery 2


Assessment items

Quiz: In-class quizzes

Formal Examination: Examination

Written Assignment: Written Assessment


Contact hours

Callaghan

Computer Lab

Face to Face On Campus 2 hour(s) per Week for Full Term starting in week 1

Lecture

Face to Face On Campus 2 hour(s) per Week for Full Term starting in week 1