CEG2703 : Observation Processing and Analysis (Inactive)
- Inactive for Year: 2022/23
- Available to incoming Study Abroad and Exchange students
- Module Leader(s): Dr Ciprian Spatar
- Owning School: Engineering
- Teaching Location: Newcastle City Campus
Semesters
Semester 1 Credit Value: | 10 |
ECTS Credits: | 5.0 |
Aims
The module aims to develop the essential mathematical skills for understanding and undertaking observation processing and analysis. Students will be provided with an in-depth understanding of the reasons for inaccuracy in survey measurements and shown how to achieve and guarantee survey results adequate for their purpose by processes of pre-analysis, estimation and post-analysis. Knowledge of the basic concepts will be related to the computation of 1D, 2D and 3D survey control schemes but the universality of methods for the handling of measurement data will be emphasised with several case studies.
Outline Of Syllabus
Maths for observation processing (linearisation using Taylor series, partial differentiation, matrix algebra); measurement errors and their propagation; least squares using observation equations; network analysis; covariance analysis; pre- and post-adjustment analysis.
Teaching Methods
Teaching Activities
Category | Activity | Number | Length | Student Hours | Comment |
---|---|---|---|---|---|
Scheduled Learning And Teaching Activities | Lecture | 18 | 0:20 | 6:00 | Synchronous online lectures. |
Structured Guided Learning | Lecture materials | 18 | 0:30 | 9:00 | Reading and understanding of lecture notes. |
Guided Independent Study | Assessment preparation and completion | 3 | 5:00 | 15:00 | Report writing and submission |
Scheduled Learning And Teaching Activities | Practical | 3 | 3:00 | 9:00 | Computer-based practical sessions delivered in person (6 hours) and online (3 hours) |
Guided Independent Study | Independent study | 1 | 56:30 | 56:30 | Includes background reading and revision of lecture materials |
Scheduled Learning And Teaching Activities | Scheduled on-line contact time | 9 | 0:30 | 4:30 | Weekly online drop-in Q&A sessions. |
Total | 100:00 |
Teaching Rationale And Relationship
Early lectures introduce essential mathematical concepts for the statistical analysis of measurement data. Later lectures discuss least squares estimation and post-analysis. The theoretical concepts presented in lectures are demonstrated through case studies. Practical sessions allow students to apply the underlying theory with the aid of both a spreadsheet application and a specialised software package. Extensive time is allocated to independent study, which includes background reading.
Alternatives will be offered to students unable to be present-in-person due to the prevailing C-19 circumstances.
Student’s should consult their individual timetable for up-to-date delivery information.
Assessment Methods
The format of resits will be determined by the Board of Examiners
Other Assessment
Description | Semester | When Set | Percentage | Comment |
---|---|---|---|---|
Practical/lab report | 1 | M | 100 | Least Squares Computations |
Assessment Rationale And Relationship
Assessment exercises assesses students' computational accuracy and presentation of detailed computations.
Reading Lists
Timetable
- Timetable Website: www.ncl.ac.uk/timetable/
- CEG2703's Timetable