Mathematics 3

Description

This module will:

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

- Introduce 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 and linear differential equations arising from applied problems and analyse solutions.

  2. Recognise and solve second order linear constant coefficient differential equations and
    appreciate their role in the modelling of electrical circuits.

  3. Calculate confidence intervals for the parameters of a distribution and use confidence intervals to reflect on the reliability of data.

  4. Structure decision-making engineering problems as hypothesis tests; select and implement the appropriate statistical procedure and interpret the results of these hypothesis tests.

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

  6. Determine the computational complexity of common algorithms.

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

  8. Apply computational software to solve mathematical problems and to visualize solutions.

Credits
05
% Coursework 50%
% Final Exam 50%