ENG2031 : Mathematical Modelling & Statistical Methods For Engineering
- Offered for Year: 2026/27
- Module Leader(s): Dr Paul Branch
- Lecturer: Dr Aleksandra Svalova
- Owning School: Mathematics, Statistics and Physics
- Teaching Location: Newcastle City Campus
Semesters
Your programme is made up of credits, the total differs on programme to programme.
| Semester 2 Credit Value: | 10 |
| ECTS Credits: | 5.0 |
| European Credit Transfer System | |
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.
Teaching Methods
Teaching Activities
| Category | Activity | Number | Length | Student Hours | Comment |
|---|---|---|---|---|---|
| Structured Guided Learning | Lecture materials | 5 | 1:00 | 5:00 | Case study support material (Mathematical Modelling) |
| Guided Independent Study | Assessment preparation and completion | 1 | 1:30 | 1:30 | Exam (Statistics) |
| Scheduled Learning And Teaching Activities | Lecture | 11 | 1:00 | 11:00 | Lectures (Statistics) |
| Guided Independent Study | Assessment preparation and completion | 1 | 10:00 | 10:00 | Exam revision (Statistics) |
| Scheduled Learning And Teaching Activities | Lecture | 10 | 1:00 | 10:00 | In person lectures (Mathematical Modelling) |
| Guided Independent Study | Assessment preparation and completion | 1 | 10:00 | 10:00 | Case study report (Mathematical Modelling) |
| Structured Guided Learning | Academic skills activities | 1 | 7:00 | 7:00 | Tutorial questions (Statistics) |
| Structured Guided Learning | Academic skills activities | 1 | 1:00 | 1:00 | Online computer practical (statistics) |
| Structured Guided Learning | Academic skills activities | 1 | 1:00 | 1:00 | Excel walkthrough videos (Statistics) |
| Scheduled Learning And Teaching Activities | Drop-in/surgery | 5 | 1:00 | 5:00 | Drop-in tutorials (Statistics) |
| Guided Independent Study | Independent study | 1 | 25:00 | 25:00 | Case study research (Mathematical Modelling) |
| Guided Independent Study | Independent study | 1 | 13:30 | 13:30 | Review course material (Statistics) |
| Total | 100:00 |
Jointly Taught With
| Code | Title |
|---|---|
| CME1027 | Data Analysis in Process Industries |
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 Methods
The format of resits will be determined by the Board of Examiners
Exams
| Description | Length | Semester | When Set | Percentage | Comment |
|---|---|---|---|---|---|
| Digital Examination | 90 | 2 | A | 45 | NUMBAS Statistics exam, in person |
Exam Pairings
| Module Code | Module Title | Semester | Comment |
|---|---|---|---|
| Data Analysis in Process Industries | 2 | N/A |
Other Assessment
| Description | Semester | When Set | Percentage | Comment |
|---|---|---|---|---|
| Case study | 2 | M | 50 | modelling report |
| Prob solv exercises | 2 | M | 5 | Statistics in-course NUMBAS assessment |
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.
Reading Lists
Timetable
- Timetable Website: www.ncl.ac.uk/timetable/
- ENG2031's Timetable