ENG2031 : Mathematical Modelling & Statistical Methods For Engineering
- Offered for Year: 2024/25
- Module Leader(s): Dr David Swailes
- Lecturer: Dr John Appleby, Dr Otti Croze, Dr Magda Carr, 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: continuous distributions, normal distribution
Statistical interference: sampling distributions and confidence intervals - one sample problems (mean, standard deviation, paired comparisons) and Regression analysis
Teaching Methods
Teaching Activities
| Category | Activity | Number | Length | Student Hours | Comment |
|---|---|---|---|---|---|
| Guided Independent Study | Assessment preparation and completion | 1 | 10:00 | 10:00 | Case study report (Mathematical Modelling) |
| 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) |
| 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) |
| Scheduled Learning And Teaching Activities | Lecture | 11 | 1:00 | 11:00 | In person lectures (Statistics) |
| Structured Guided Learning | Academic skills activities | 1 | 1:00 | 1:00 | Excel walkthrough videos (Statistics) |
| Structured Guided Learning | Academic skills activities | 1 | 7:00 | 7:00 | Tutorial questions (Statistics) |
| Scheduled Learning And Teaching Activities | Practical | 1 | 1:00 | 1:00 | In-person computer practical (Statistics) |
| Scheduled Learning And Teaching Activities | Small group teaching | 5 | 1:00 | 5:00 | In-person 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 engineering. Tutorial questions will be supplied for students' self-study. Drop-in tutorials will be used to address student queries and aid understanding.
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 written statistics assessment in Semester 2 is appropriate for presenting data-intensive questions and testing the application of statistical techniques on these.
Reading Lists
Timetable
- Timetable Website: www.ncl.ac.uk/timetable/
- ENG2031's Timetable