nireEHU 
Subject
Data analysis in environmental science
General details of the subject
- Mode
- Face-to-face degree course
- Language
- English
Description and contextualization of the subject
This teaching re-introduces the fundamentals of statistical analysis applied to environmental sciences. Its five major sections address probability distributions, estimation and hypothesis testing, analysis of variance, Regression and correlation, multivariate analysis methods and time series analysis methods. For most of the statistical techniques, concrete applications are investigated through practical sessions using the free software R.ccccccccccTeaching staff
| Name | Institution | Category | Doctor | Teaching profile | Area | |
|---|---|---|---|---|---|---|
| ORTIZ ZARRAGOITIA, MAREN | University of the Basque Country | Profesorado Agregado | Doctor | Bilingual | Cellular Biology | maren.ortiz@ehu.eus |
Competencies
| Name | Weight |
|---|---|
| Que el estudiante adquiera destreza básica en técnicas específicas. | 33.0 % |
| Que el estudiante sea capaz de diseñar y elaborar modelos numéricos, estadísticos y computacionales en lo referente a los ciclos biogeoquímicos de los contaminantes químicos ambientales, sus efectos sobre los seres vivos y los procedimientos de evaluación de riesgo e impacto. | 33.0 % |
| Que el estudiante sea capaz de recolectar, registrar y analizar (tratamiento y computerización) datos sobre contaminación y toxicidad (de campo y de laboratorio) mediante técnicas y equipamiento de última generación. | 33.0 % |
Study types
| Type | Face-to-face hours | Non face-to-face hours | Total hours |
|---|---|---|---|
| Lecture-based | 26 | 39 | 65 |
| Applied laboratory-based groups | 20 | 30 | 50 |
| Workshop | 14 | 21 | 35 |
Training activities
| Name | Hours | Percentage of classroom teaching |
|---|---|---|
| Classroom/Seminar/Workshop | 35.0 | 50 % |
| Laboratory/Field | 50.0 | 45 % |
| Lectures | 65.0 | 40 % |
Assessment systems
| Name | Minimum weighting | Maximum weighting |
|---|---|---|
| Practical tasks | 50.0 % | 50.0 % |
| Written examination | 50.0 % | 50.0 % |
Learning outcomes of the subject
At the end of the Unit, you should be able to:1. use the potential of R to conduct a data analysis
2. provide a detailed and critical analysis of the results
Temary
Discrete and continuous random variablesSample and population: statistical inference
Regression and correlation
Multivariate analysis
Time series analysis
Bibliography
Basic bibliography
R.E. Thomson and W.J. Emery 2014. Data Analysis Methods in Physical Oceanography, Third Edition, Elsevier.W.W. Daniel and C.L. Cross 2013, Biostatistics: A Foundation for Analysis in the Health Sciences, 10th Edition.