Learning objectives
1°- Knowledge and understanding
At the end of the lessons the student will know the methods of data treatment and spatial analysis. He will understand the technical terminology in the field.
2°- Applying knowledge and understanding
The student will be able to assess the quality of data, perform spatial estimation.
3°- Making judgments
The student will acquire the ability to solve data analysis and estimation problems.
4°- Communication skills
On passing the exam, the student should have acquired sufficient correct use of the language with regard to the topic specific terminology.
5°- Learning skills
The student should have acquired the basic knowledge of the discipline that will allow him to learn independently the future developments of the discipline.
Prerequisites
The course covers the basics of Maths and Statistics that the student acquired during the bachelor's degree.
Course unit content
The Environmental and data analysis and geostatistics course is oriented to the data elaboration. In the first part of the course we will recall concepts of statistics and probability, we will analyze the statistical distributions, the probability functions, the estimation of the parameters and the evaluation of goodness of fit. In the second part of the course we will introduce geostatistics and Kriging's methodology. During the lessons, case studies will be considered.
Full programme
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Bibliography
Recommended books:
Sheldon Ross, Probabilità e statistica per l'ingegneria e le scienze, Apogeo Education, ISBN: 8891609943. Posa, De Iaco, Geostatistica teoria e applicazioni, 2009, Giappichelli, ISBN 8834897447.
Zhihua Zhang, Environmental Data Analysis Methods and Applications, 2017, de Gruyter. Available online
Additional books:
Marco Taboga, Lectures on Probability Theory and Mathematical Statistics.
William Menke, Joshua Menke, Environmental Data Analysis with Matlab (Second Edition), Academic Press, 2016, ISBN 9780128044889, https://doi.org/10.1016/B978-0-12-804488-9.09996-1
Kitanidis, P. (1997). Introduction to Geostatistics: Applications in Hydrogeology. Cambridge: Cambridge University Press. doi:10.1017/CBO9780511626166
Linee guida per l'analisi e l'elaborazione statistica di base delle serie storiche di dati idrologici, ISPRA Manuali e linee guida, 84/2013, ISBN: 978-88-448-0584-5. Available online
All the books are available in the library.
Additional educational material: Lecture notes provided to the students.
Teaching methods
The course consists of a series of lectures and numerical exercises. The lessons will be carried out using Power Point presentations. The exercises are presented and carried out numerically in the classroom through spreadsheet and Matlab.
Assessment methods and criteria
The exam consists of an oral interview.
The evaluation of the oral examination will be weighted as 70% knowledge of the data treatment (knowledge and understanding), 30% correct use of the technical language (Communication skills).
Other information
