 | | |
| OCEA0045-1 | Statistical methods of analysis of oceanographic data
|
|
| Duration : | 20h Th, 10h Pr |
|
| Number of credits : |
|
|
| Lecturer : | Aïda Alvera Azcarate |
|
Language(s) of instruction :
|
| French language |
|
Organisation and examination :
|
| Teaching in the first semester, review in January |
|
Course contents :
|
| Oceanographic data, in-situ or satellite based, cover a wide time-space spectrum of processes, contain errors specific to each measurement system and require specific data analysis methods in function of the use one wants to make of them. |
|
Learning outcomes of the course :
|
| The lecture aims at describing the different measurement techniques used in hte marine environment and to introduce the different type of data analysis tools adapted to each type of data.
1.Statistical methods and error estimates :
- probability, distributions, confidence intervals, regressions (linear, multivariate, correlation)
- degrees of freedom, hypothesis testing
- Obvious errors, rounding errors
- interpolation
- covariance
2. Spatial analysis
- Objective analysis
- Principal component analysis
- Inverse methods
3. Temporal analysis
- correlation function
- Harmonic analysis
- spectral analysis (FFT)
- Wavelets
- digital filters
Data acquisition and presentation will be also discussed during the lessons. |
|
Prerequisites and co-requisites/ Recommended optional programme components :
|
| A solid mathematical background and basic knowledge in ocean sciences |
|
Planned learning activities and teaching methods :
|
| Exercises will use real data sets from a CD-ROM. Matlab will be used for most exercises. |
|
Mode of delivery (face-to-face ; distance-learning) :
|
| Face-to-face learning |
|
Recommended or required readings :
|
| The main reference is
"Data analysis methods in physical oceanography", William J. Emery and Richard E. Thomson.
Other materials are available as well (see "on-line notes" section) |
|
Assessment methods and criteria :
|
| Skills will be assessed during exercise sessions using real inter-disciplinary data sets, taking into account the complexity and quality of methodology, processing, presentation, interpretation and synthesis. |
|
Work placement(s) :
|
| None |
|
Organizational remarks :
|
| Lectures will be given once per week, with sessions of 3-4 hours.
Interested students should contact me to establish the timetable of this lecture. |
|
Contacts :
|
| Aida Alvera Azcárate
AGO-GHER
Université de Liège
Allée du 6 Août, 17, Bât. B5
4000 Liège, Belgium
A.Alvera@ulg.ac.be
Tel.: +32 (0)4 366 3664
Fax.: +32 (0)4 366 9729 |
|
|
| Items online : |
|
| Lecture materials |
| Lecture notes and other materials can be found here: |
|
|
