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Unit of Study MATH3003 - Computational Analysis (2025)

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Unit Snapshot

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Unit description

This unit introduces students to essential data management skills for statistical analyses and computational methods for problem-solving. Students will learn how to effectively manage data for basic statistical analyses and apply computational techniques using computer applications. They will gain proficiency in implementing numerical algorithms to solve problems such as linear and nonlinear equations, numerical differentiation, and integration. Additionally, students will develop the ability to formulate and solve mathematical problems, critically evaluating the results obtained.

Unit content

Module 1:  Mathematical programming

Module 2:  Further programming techniques
 
Module 3:  Numerical integration and differentiation
 
Module 4:  Introduction to probability
 
Module 5:  Tests of the mean
 
Module 6:  Regression

 

Availabilities

Location Domestic International
Gold Coast
Term4
Term4
Lismore
Term4
Term4
Online
Term4
N/A

Learning outcomes

Unit Learning Outcomes express learning achievement in terms of what a student should know, understand and be able to do on completion of a unit. These outcomes are aligned with the graduate attributes. The unit learning outcomes and graduate attributes are also the basis of evaluating prior learning.

On completion of this unit, students should be able to:

formulate and solve mathematical programming and statistical problems and critically evaluate the results

implement numerical algorithms for computing solutions of various problems incorporating numerical differentiation or integration

apply and evaluate basic statistical analyses

Identify and apply the appropriate method and accurately communicate the results using mathematical and statistical techniques

evaluate a real-world problem by formulating a mathematical model demonstrating the model feasibility and its' simulation

evaluate a real-world problem by utilising techniques including data-visualisation, measures of location and spread, hypothesis tests of the mean, analysis of variance and regression.

Prescribed learning resources

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