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Module

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 LearningLecture materials101:0010:00Reviewing lecture notes (Statistics)
Guided Independent StudyAssessment preparation and completion111:0011:00Statistics exam
Guided Independent StudyAssessment preparation and completion101:0010:00case study report
Scheduled Learning And Teaching ActivitiesLecture101:0010:00In person lectures (Modelling)
Structured Guided LearningLecture materials45:0020:00case study support material (Modelling)
Scheduled Learning And Teaching ActivitiesLecture101:0010:00In person lectures (Statistics)
Guided Independent StudySkills practice101:0010:00Problem sheet exercises (statistics)
Scheduled Learning And Teaching ActivitiesDrop-in/surgery51:005:00In-person drop-in tutorials (Statistics)
Guided Independent StudyIndependent study101:0010:00Case study research (Modelling)
Scheduled Learning And Teaching ActivitiesScheduled on-line contact time41:004:00Synchronous tutorials
Total100:00
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 Examination902A50Statistics exam
Exam Pairings
Module Code Module Title Semester Comment
Data Analysis in Process Industries2N/A
Other Assessment
Description Semester When Set Percentage Comment
Case study2M50modelling 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