Available in 2024
Course code

STAT2110

Units

10 units

Level

2000 level

Course handbook

Description

Statistics provides us with a quantitative framework to utilise data for describing, summarising, and modelling the world around us. Engineering statistics combines engineering and statistics using scientific methods for analysing data. This course introduces students to the fundamental 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. On completion of this course students will be able to apply statistical theory to make informed decisions and predictions relevant to engineering.


Availability2024 Course Timetables

Callaghan

  • Semester 1 - 2024

Learning outcomes

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

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

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

3. Apply 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 STAT1300 and STAT2010. If you have successfully completed STAT1300 or 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

Knowledge of and experience in Python


Assessment items

Quiz: Quizzes

Written Assignment: Written Assessment

Formal Examination: Examination


Contact hours

Semester 1 - 2024 - Callaghan

Computer Lab-1
  • Face to Face On Campus 2 hour(s) per week(s) for 13 week(s) starting in week 1
Lecture-1
  • Face to Face On Campus 2 hour(s) per week(s) for 13 week(s) starting in week 1
Tutorial-1
  • Face to Face On Campus 2 hour(s) per week(s) for 13 week(s) starting in week 1

Course outline