CEG2002 : Statistics and Numerical Methods for Civil Engineers
CEG2002 : Statistics and Numerical Methods for Civil Engineers
- Offered for Year: 2024/25
- Module Leader(s): Dr David Swailes
- Lecturer: Dr David Walshaw
- 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 | |
Pre-requisite
Modules you must have done previously to study this module
Code | Title |
---|---|
ENG1001 | Engineering Mathematics I |
Pre Requisite Comment
N/A
Co-Requisite
Modules you need to take at the same time
Co Requisite Comment
N/A
Aims
The aims of the module are:-
1. To introduce a basic understanding of statistical methods and data analysis in the context of Civil Engineering.
2. To introduce the statistical analysis program Minitab.
3. To extend students' knowledge, understanding and use of differential equations.
4. To impart a basic working knowledge of a range of widely used numerical techniques with some of the underpinning theoretical ideas.
Outline Of Syllabus
Probability, Sampling, descriptive statistics, discrete and continuous probability, distributions (binomial, Poisson, uniform, normal, exponential), linear combination of variables, central limit theorem, confidence intervals for mean hypothesis testing and goodness of fit, regression, introduction to Minitab.
Basic decision theory (statistical games, decision criteria, the theory in practice).
Numerical methods for large systems of linear equations; decomposition and iterative techniques.
Numerical methods for first-order ordinary differential equations:
Single and multi-step schemes. Error and stability analysis using Taylor series. Numerical treatment of higher-order differential equations and first-
order systems.
Numerical methods for linear partial differential equations:
Finite difference methods, explicit and implicit schemes and stability.
Engineering applications of numerical techniques; including structural vibrations, heat and flow dynamics and dispersion.
Learning Outcomes
Intended Knowledge Outcomes
At the end of this module students will understand:
1. The importance of statistical analysis in engineering and other fields.
2. The nature of uncertainty and the concept of probability.
3. Numerical techniques for solving ordinary and partial differential equations and large systems of linear algebraic equations
4. The student should recognize and understand the methodologies of various numerical techniques and associated error estimation analyses.
5. A range of engineering applications of the methods introduced
Intended Skill Outcomes
At the end of this module students should be able to indentify and apply appropriate numerical and statistical techniques to support critical analysis of engineering problems. They should be able to assess and comment constructively on the limitations and implications of the results obtained from their analyses.
Teaching Methods
Teaching Activities
Category | Activity | Number | Length | Student Hours | Comment |
---|---|---|---|---|---|
Structured Guided Learning | Lecture materials | 18 | 2:00 | 36:00 | Lecture Notes/Supplementary Recorded Lectures |
Scheduled Learning And Teaching Activities | Lecture | 20 | 1:00 | 20:00 | Lectures |
Guided Independent Study | Assessment preparation and completion | 15 | 1:00 | 15:00 | Alternative Assessment |
Guided Independent Study | Assessment preparation and completion | 1 | 5:00 | 5:00 | Statistical Coursework |
Guided Independent Study | Assessment preparation and completion | 1 | 5:00 | 5:00 | Numerical Methods Coursework |
Scheduled Learning And Teaching Activities | Small group teaching | 9 | 1:00 | 9:00 | Tutorials |
Guided Independent Study | Skills practice | 5 | 2:00 | 10:00 | Problem Sheet Exercises |
Total | 100:00 |
Teaching Rationale And Relationship
Lectures will complement the prepared lectured notes and problem sheets, reinforcing and expanding on the essential points introduced each week.
The problem sheets provide practice material and the tutorial sessions will be used to discuss both these problems and others raised by the students, as well as to provide feedback to students on assessed work.
Reading Lists
Assessment Methods
The format of resits will be determined by the Board of Examiners
Exams
Description | Length | Semester | When Set | Percentage | Comment |
---|---|---|---|---|---|
Written Examination | 120 | 2 | A | 80 | N/A |
Other Assessment
Description | Semester | When Set | Percentage | Comment |
---|---|---|---|---|
Prob solv exercises | 2 | M | 10 | Numerical Methods |
Prob solv exercises | 2 | M | 10 | Statistical Methods |
Assessment Rationale And Relationship
The assessment provides an appropriate way to assess both theoretical understanding and practical problem solving skills. The in-course assessment enables more detailed engineering problems to be considered in greater depth and software use skills to be employed.
Timetable
- Timetable Website: www.ncl.ac.uk/timetable/
- CEG2002's Timetable
Past Exam Papers
- Exam Papers Online : www.ncl.ac.uk/exam.papers/
- CEG2002's past Exam Papers
General Notes
N/A
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Disclaimer
The information contained within the Module Catalogue relates to the 2024 academic year.
In accordance with University Terms and Conditions, the University makes all reasonable efforts to deliver the modules as described.
Modules may be amended on an annual basis to take account of changing staff expertise, developments in the discipline, the requirements of external bodies and partners, and student feedback. Module information for the 2025/26 entry will be published here in early-April 2025. Queries about information in the Module Catalogue should in the first instance be addressed to your School Office.