ENG2031 : Mathematical Modelling & Statistical Methods For Engineering
- Offered for Year: 2023/24
- Module Leader(s): Dr David Swailes
- Lecturer: Dr Magda Carr, Dr Aleksandra Svalova, Dr John Appleby, Dr Otti Croze
- 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 two sample problems (comparison of means, ratio of variances) Regression analysis
Teaching Methods
Teaching Activities
Category | Activity | Number | Length | Student Hours | Comment |
---|---|---|---|---|---|
Structured Guided Learning | Lecture materials | 10 | 1:00 | 10:00 | Reviewing lecture notes (Statistics) |
Guided Independent Study | Assessment preparation and completion | 11 | 1:00 | 11:00 | Statistics exam |
Guided Independent Study | Assessment preparation and completion | 10 | 1:00 | 10:00 | case study report |
Scheduled Learning And Teaching Activities | Lecture | 10 | 1:00 | 10:00 | In person lectures (Modelling) |
Structured Guided Learning | Lecture materials | 4 | 5:00 | 20:00 | case study support material (Modelling) |
Scheduled Learning And Teaching Activities | Lecture | 10 | 1:00 | 10:00 | In person lectures (Statistics) |
Guided Independent Study | Skills practice | 10 | 1:00 | 10:00 | Problem sheet exercises (statistics) |
Scheduled Learning And Teaching Activities | Drop-in/surgery | 5 | 1:00 | 5:00 | In-person drop-in tutorials (Statistics) |
Guided Independent Study | Independent study | 10 | 1:00 | 10:00 | Case study research (Modelling) |
Scheduled Learning And Teaching Activities | Scheduled on-line contact time | 4 | 1:00 | 4:00 | Synchronous tutorials |
Total | 100:00 |
Teaching Rationale And Relationship
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 |
---|---|---|---|---|---|
Written Examination | 90 | 2 | A | 50 | Statistics exam |
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 |
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