# Mathematics for Software and Electronic Engineering 3

## Description

This module will:

- Equip students with the mathematical techniques to formulate and solve problems in differential equations.

- Introduce probability distributions and  statistical inference through the concepts of estimation and hypothesis testing and apply these concepts to engineering problems.

- Introduce the student to the fundamentals of algorithm analysis.

## Learning Outcomes

1. Formulate and solve first-order separable, linear differential equations and solve second order linear constant coefficient differential equations and
appreciate their role in the modelling of electrical circuits.

2. Calculate confidence probability distributions and intervals for the parameters of a distribution and use confidence intervals to reflect on the reliability of data, and use this information to structure decision-making engineering problems

3. Formulate a linear regression model and analyse the results.

4. Determine the computational complexity of common algorithms.

5. Outline the purpose of complexity analysis and understand its impact on programming.

Credits
05
% Coursework 40%
% Final Exam 60%