ENG2012 : Engineering Mathematics II and Statistical Data Analysis
- Offered for Year: 2019/20
- Module Leader(s): Professor Yuri Sergeev
- Lecturer: Dr Wenting Hu, Dr John Appleby, Dr David Swailes
- Owning School: Mathematics, Statistics and Physics
- Teaching Location: Newcastle City Campus
Semester 1 Credit Value:
Semester 2 Credit Value:
Mathematics: to extend students' knowledge, understanding and application of analytical methods required in Mechanical Engineering. The course covers methods for solving differential equations, theory and applications of vector analysis and various infinite series.
To develop students' ability to solve mechanical engineering problems.
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
Differential Equations and Series:
- the Laplace transform and its application to solving ordinary differential equations
- Fourier series
- partial differential equations with applications
- vector methods and their applications
- scalar and vector fields - grad, div, curl and potential fields
- surface and volume integrals
- divergence theorem and applications to transport processes
- application to fluid mechanics: material derivative, continuity and Euler's equations
Mathematical modelling: for solving mechanical engineering problems
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)
|Guided Independent Study||Assessment preparation and completion||1||38:00||38:00||Target non-timetable hours to complete coursework assignment submissions|
|Scheduled Learning And Teaching Activities||Lecture||44||1:00||44:00||Structured presentation of syllabus may include skills demonstration, formative feedback etc|
|Guided Independent Study||Assessment preparation and completion||36||0:30||18:00||Recommended revision for exams, assuming prior regular independent study throughout teaching|
|Guided Independent Study||Assessment preparation and completion||1||1:30||1:30||Semester 2 examination|
|Guided Independent Study||Assessment preparation and completion||1||2:00||2:00||Semester 1 examination|
|Scheduled Learning And Teaching Activities||Small group teaching||19||1:00||19:00||Problems classes ("tutorials") to support independent study and reinforce skills practice|
|Guided Independent Study||Independent study||1||77:30||77:30||Recommended regular personal study throughout teaching period to follow up taught classes|
Jointly Taught With
|ENG2008||Analytic Methods in Marine Technology|
|ENG2011||Engineering Mathematics II|
|CME1027||Data Analysis in Process Industries|
Teaching Rationale And Relationship
Lectures are used to present the mathematical theory and techniques and demonstrate their use in solving a range of problems in the subject area.
Tutorials provide support and individual guidance to underpin students' self-study and problem solving skills, and provide a forum for further discussion to aid understanding.
Practical classes support the learning introduced in lectures through the students having the opportunity to apply the concepts to a number of problems varying in terms of complexity. The practical classes allow the completion of assignment work.
The format of resits will be determined by the Board of Examiners
|ENG2011||Engineering Mathematics II||1||N/A|
|CME1027||Data Analysis in Process Industries||2||N/A|
|Report||1||M||5||Assignment on Vectors and differential equations (max 15 h)|
|Report||2||M||25||Comprises attendance 7.5%, assignment 1 5% and assignment 2 12.5% (max 15 hrs)|
Assessment Rationale And Relationship
The written examinations provide an appropriate means to assess knowledge and understanding, and the ability to apply theory and techniques to problem solving.
The coursework provides the opportunity for tackling extended problems, assessing understanding of key ideas and principles and competence in applying these.
The mathematical modelling and statistical assignments assess the ability to formulate as well as solve associated engineering problems.
To meet the accreditation requirements of professional bodies, a passing mark for this module (40%) can be achieved only if a minimum mark of 30% is achieved for the assessed work (exam and coursework) in each semester. If a mark of at least 30% is not achieved in either semester, then the overall result will be restricted to 35%. If a resit is required then any individually passed component will be carried forward.