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Building mathematical knowledge in the context of sustainability and understanding challenges related to sustainability in a quantitative way is the core of this module. This module provides a foundation for basic mathematics and statistics, making sure that all first-year students have a good understanding of the mathematical and/or statistical concepts required for subsequent modules. The module provides in-depth knowledge of mathematics (e.g. calculus, vector spaces, matrices, linear algebra) and statistics (e.g. probability, descriptive statistics, continuous/discrete random variables, hypothesis testing). The content is designed to develop data analysis skills using the statistical concepts mentioned above and understand linear algebra and calculus to represent and manipulate data. Solid foundations of the mathematical concepts necessary to succeed are introduced via real-world case studies. This module will also introduce Excel/Matlab and Python (open-source statistical packages). It provides transferable skills underpinning the evidence-oriented sustainability programme.

The aims of the module are to:

• DevelopÌýan understanding of the mathematical concepts that underpin the study of engineering systems.
• Introduce students to using newly acquired skills to solve practical engineering and socioeconomic problems by developing mathematical models, and use software tools (e.g. Python and MATLAB) to test and analyse these models.

By the end of the module students should be able to:

• Recognize the connections between mathematics/statistics and engineering.
• Demonstrate how mathematical concepts are used in engineering contexts.
• Identify and draw upon a range of mathematical concepts, including Calculus, Linear Algebra, and Differential Equations, to analyse specific problems and identify the appropriate mathematics to realise a solution.
• Employ appropriate computer tools/modelling techniques and statistical analysis to efficiently solve and evaluate engineering problems.
• Present and interpret mathematical results in effective and appropriate ways to varied audiences, including non-mathematical engineering audiences.