Subject
Computational Data Analysis for Geophysicists and Ocean Scientists
General details of the subject
- Mode
- Face-to-face degree course
- Language
- English
Description and contextualization of the subject
This module will present a variety of different types of geophysical, oceanographic and remote sensing data and will explore methods for processing, analysing and modelling using MATLAB.Teaching staff
Name | Institution | Category | Doctor | Teaching profile | Area | |
---|---|---|---|---|---|---|
MARIGOMEZ ALLENDE, JUAN ANTONIO | University of the Basque Country | Profesorado Catedratico De Universidad | Doctor | Bilingual | Cellular Biology | ionan.marigomez@ehu.eus |
SOTO LOPEZ, MANUEL | University of the Basque Country | Profesorado Catedratico De Universidad | Doctor | Bilingual | Cellular Biology | manu.soto@ehu.eus |
Competencies
Name | Weight |
---|---|
Programming skills. | 33.0 % |
Report writing. | 33.0 % |
Data manipulation including the identification of noise and filtering. | 33.0 % |
Study types
Type | Face-to-face hours | Non face-to-face hours | Total hours |
---|---|---|---|
Lecture-based | 24.5 | 35.5 | 60 |
Applied classroom-based groups | 4.5 | 7.5 | 12 |
Applied fieldwork groups | 46 | 69.5 | 115.5 |
Training activities
Name | Hours | Percentage of classroom teaching |
---|---|---|
Exercises | 51.5 | 13 % |
Expositive classes | 44.0 | 50 % |
Student's personal work | 92.0 | 50 % |
Assessment systems
Name | Minimum weighting | Maximum weighting |
---|---|---|
Practical tasks | 30.0 % | 50.0 % |
Written examination (problems) | 50.0 % | 70.0 % |
Learning outcomes of the subject
At the end of the Unit, the student should be able to:1. Analyse data using a variety of statistical and processing techniques, with an understanding of the relative merits of each technique, when and where to apply them, and any potential pitfalls in their use.
2. Implement mathematical algorithms in MATLAB programs.
3. Produce a quantifiable interpretation of data and present it in an informative manner.
Temary
The module will introduce statistical analysis, curve fitting and the interpolation of data. The analysis of data in the frequency domain using the Fourier Transform will be covered with applications to filtering in 1-D and 2-D. The fundamentals of computer programming will be taught in practical sessions using MATLAB and will involve implementing the techniques covered in the lectures. The course will include optimal methods for the display of data.Practical sessions: will exemplify the theory. Practical sessions will be computer-based exercises used to illustrate the concepts covered in the formal lectures. Computer practical sessions will use the software package MATLAB.
Bibliography
Basic bibliography
Blackboard: The lecture material is summarized at blackboard.soton.ac.uk. Instructions for accessing this material will be given during the course. Illustrated handout materials will complement most lectures. Where relevant, lecturers' own research experience in the appropriate fields is brought into the lecturing sessions. References to the applicable chapter of course text and/or relevant journal articles are provided to complement some of the lectures.
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