Statistical Methods in Marine Sciences (250567) – Course 2025/26 PDF
Syllabus
Learning Objectives
In this subject, statistical methods that allow explaining correlations and dependencies of natural and anthropogenic processes in the sea will be presented, emphasizing fundamental aspects of exploratory statistics such as descriptive analysis of multivariate data, bi-variated distribution, extreme models, principal component analysis, regression models, grouping and classification methods and introduction to Bayesian statistics. 1.- Critically analyze a multivariate database (be it of real, positive, directional or compositional scale) using exploratory (e.g. biplot) and descriptive (e.g. PCAs) techniques. 2.- Establish multiple regression models and simple generalizations of them (e.g. ANOVA). Interpret the diagnoses about the models, as well as critically analyze their predictive uses. 3.- Classify and discriminate large capacity multivariate databases with supervised and unsupervised classification methods, for later analysis and critical interpretation. This is where students are expected to obtain a vision of real environmental problems in the marine environment from a perspective that combines, on the one hand, chemistry and biology, as well as the mathematical techniques to address these problems (Marine Ecology, Ecosystems and Productive Processes) and, on the other, the tools of chemistry, biology and physics (Marine Pollution, Origin, Transport and Impacts), which are needed to solve common problems in coastal and platform waters. This subject also includes applied techniques in the visualization, interpretation and resolution of the problems addressed in this same subject.
Competencies
Especific
To know and apply the lexicon and concepts of the Marine Sciences and Technologies and other related fields.
Establish a good practice in the integration of common numerical, laboratory and field techniques in the analysis of any problem related to the marine environment.
Address the most relevant processes and their interactions related to their physical / chemical / biological / geological components, applying technical and scientific knowledge and criteria.
Develop a conceptual framework to address the sustainability of the marine environment and the related socio-economic activities at different scales, explaining the effects of climate change.
Carry out calculations, assessments, surveys and inspections in coastal and marine environments, as well as the corresponding technical documents.
Apply the necessary tools to analyze the economic and legal aspects of human actions and the related impacts on the marine environment, including technical advice and representation of companies and administrations.
Generic
Develop a professional activity in the field of Marine Sciences and Technologies.
Address in a comprehensive manner the analysis and preservation of the marine environment with sustainability criteria.
Total hours of student work
| Hours | Percentage | |||
|---|---|---|---|---|
| Supervised Learning | Large group | 30h | 50.00 % | |
| Medium group | 30h | 50.00 % | ||
| Self Study | 90h | |||
Teaching Methodology
The course consists of 2 hours per week of classroom activity. Two hours are devoted to theoretical lectures, in which the teacher presents the basic concepts and topics of the subject, shows examples and solves exercises.
Grading Rules
The evaluation calendar and grading rules will be approved before the start of the course.
The grade for the course will consist of: - Activities (NA). - Two exams (NE1 and NE2). 1. Activities (NA) will include, among others, the resolution of problems and the participation in class. 2. The contents of the NE1 and NE2 exams will be in accordance with all the subject taught from the beginning of the course. - The NE1 exam will be taken approximately halfway through the semester and the subjects taught so far will enter. - The NE2 exam will be a final exam, where the complete subject taught throughout the course will enter. The note of the exams will be calculated as: NE = max (0.3 * NE1 + 0.7 * NE2, NE2) The final grade for the course will be: Final Note = 0.2 * NA + 0.8 * NE
Office Hours
Face-to-face: to be agreed with the student. You must make an appointment in advance. Non-contact: by e-mail whenever the student wants to use it.
Bibliography
Basic
- Kottegoda, N.T.; Rosso, R. Applied statistics for civil and environmental engineers. Second Edition. Oxford: Wiley-Blackwell, 2008. ISBN 978-1-4051-7917-1.
- Ang, A.H-S.; Tang, W.H. Probability concepts in engineering: emphasis on applications in civil & environmental engineering. 2nd ed. New York: Wiley, 2007. ISBN 9780471720645.
- Chatterjee, S.; Hadi, A.S. Regression analysis by example. 5th ed. Hoboken, New Jersey: Wiley, 2012. ISBN 9780470905845.
- Dobson, Annette J G. Barnett. An introduction to generalized linear models. 4th. Boca Raton, FL: Chapman & Hall/CRC Taylor & Francis Group, 2018. ISBN 9781138741515.
- Peter K. Dunn Gordon K. Smyth. Generalized Linear Models With Examples in R. New York, NY: Springer, 2018. ISBN 9781441901187.
- Brockwell, P. J.; Davis, R. A. Introduction to time series and forecasting. 2nd ed. New York: Springer, 2002. ISBN 9780387953519.
Complementary
- Maindonald, J.; Braun, J. Data analysis and graphics using R: an example-based approach. 3rd ed. Cambridge: Cambridge University, 2010. ISBN 9780521762939.
- Castillo, E. [et al.]. Extreme value and related models with applications in engineering and science. Hoboken, New Jersey: John Wiley & Sons, 2005. ISBN 047167172X.