Module Catalogue 2026/27

Pre Requisite Comment

ENG1001 Engineering Mathematics I.
English Language to IELTS 6.0 or Pearsons 54 or equivalent.
Satisfactory progression or admissions requirement for entry to Stage 2 of engineering undergraduate programme. Basic knowledge of statistics from A level mathematics or equivalent.

Co Requisite Comment

N/A

Aims

Mathematics: to extend students' knowledge, understanding and application of modelling methods used in Engineering.
Statistics: to provide students with a fundamental understanding of the basic statistical techniques (summary statistics, probability distributions, interval estimation and regression analysis) routinely used in the engineering industries.

Outline Of Syllabus

Mathematics:
A series of modelling case studies are presented utilising simple mathematics, with an emphasis on the formulation and interpretation of mathematics rather than methods.

Statistics:
Introduction: Descriptive statistics.
Probability: probability theory; probability distributions (continuous and discrete); normal distribution; Statistical Inference and hypothesis testing: Sampling distributions and confidence intervals – One sample problems (mean, standard deviation, paired comparisons).

Regression analysis: method of least squares.

Intended Knowledge Outcomes

Mathematics: techniques for mathematical modelling in engineering, using a range of simple solution methods (emphasis is on skills rather than knowledge).

The students will be able to recall and understand basic statistical terminology.
The students will be able to understand fundamental probability and statistical theory and techniques.

The students will be able to understand the assumptions behind statistical inference and regression techniques used and their limitations.
The students will be able to understand the difference between related concepts, such as discrete distribution and continuous distribution; probability density function and cumulative distribution function; z-test and t-test (AHEP4 C1, C2).

Intended Skill Outcomes

Mathematical Modelling:
To acquire competence to
-       analyse and formulate a problem mathematically
-       devise an appropriate strategy to solve the problem
-       identify and implement a suitable solution method (using computing aids as appropriate)
-       interpret and communicate results effectively and draw appropriate conclusions within the context of standard mathematical methods for engineers.

Statistics:
The students will be able to present, describe and interpret data in an appropriate and statistically robust manner in an industrial context using the knowledge on statistical theory and techniques acquired (AHEP4 C1, C2).
The students will be able to apply the appropriate assumptions when performing statistical inference, hypothesis testing and regression.
The students will be able to use appropriate software for simple statistical analysis through custom or in-build functions (MS Excel) (AHEP4 C1, C2).

Teaching Rationale And Relationship

Mathematical Modelling: The emphasis is on formulation and application, so ‘lectures’ will be interactive. Tutorial and on-line support will be to encourage students’ own initiatives in developing and using models.

Statistics: In-person lectures convey the statistical concepts and theory and their application in process engineering. Tutorial questions will be supplied for students' to work through each week. Drop-in tutorials will be used to address student queries and aid understanding. Short video walkthroughs of Excel will help demonstrate how to use software to carry out data analysis.

Assessment Rationale And Relationship

The modelling case study report in Semester 2 permits a more open-ended assessment appropriate for developing and communicating ideas.

The examination enables the assessment of whether the students have understood the methodologies and whether they are sufficiently conversant with the application of the techniques to real world scenarios.
Assessment incorporates AHEP4 learning outcomes C1 and C2.

General Notes

N/A