- Docente: Roberto Bruno
- Credits: 4
- Language: Italian
- Teaching Mode: In-person learning (entirely or partially)
- Campus: Bologna
- Corso: First cycle degree programme (L) in Environmental Engineering (cod. 0928)
Learning outcomes
The mission of the course is to provide a basic training for statistical and probabilistic processing of quantities measured in laboratory tests and of Regionalized Variables. In particular, the attention will be addressed to the relevant quantities characterizing the Environmental and Georesources Engineering from the chemical, physical and geometric standpoint (eg, strength and physical parameters; concentrations in soil / groundwater / air; porosity / permeability; depth / thickness of geological formations; time series of variables at measurement stations; ...).
The knowledge to be gained refer to the tools for the statistical processing of data (frequency distributions and moments, correlations) and the basic theoretical elements for the probabilistic characterization of space-time Regionalized Variables (spatial covariance, variogram) and to some application tools such as optimal estimators (kriging) to address many of the problems related to the environment and the georesources (mapping; optimization of sampling; assessment and selection of polluted/mineralized domains; …)
Learning outcomes refer to the utilization of statistical processing tools actually available in the Office platform (Microsoft, Sun), namely on the spreadsheet (Excel or similar); and to the programming of “macros”, in visual-basic, to execute elementary processing.
Course contents
Reminders in Probabilities and Statistics
· Elementary Statistics
· Frequency distributions
· Random Variables
· Correlation
· Regression
Introduction to the Regionalized Variables theory
· Regionalized Variables
· Random Functions
· Autocorrelation functions: spatial covariance and variogram
· Experimental and model variogram
· Regularized Variables
· Dispersion
Introduction to the Regionalized Variables estimation
· Linear estimation
· Ordinary Kriging
· Kriging of domains
· Mapping of estimated values and mapping precision
Introduzione alla selettività
1. La selettività e l'effetto supporto
2. La selettività e l'effetto informazione
- Selection
· Selection and support effect
· Selection and information effect
Readings/Bibliography
COURSE's TEXTS
· Bruno, Roberto CLASS NOTES (power point)
· Raspa, G. & Bruno, R. GEOSTATISTICS NOTES (pdf)
BIBLIOGRAPHY
· Bruno, R. and Raspa, G. (1994) - La pratica della geostatistica lineare: il trattamento dei dati spaziali - Edizioni Angelo Guerini ed Associati S.r.l., 170 pp.
· Chiles, J.P. & Delfiner, Pierre (1999) - Geostatistics - Wiley Series in Probability and Statistics, - John Wiley and sons, Inc., 687 pp.
Teaching methods
Each lecture is divided into two parts: the first presenting the theory and methods of statistical treatment of data, in the second these methodologies are operationally applied on the computer spreadsheet, both at elementary level through mathematical and statistical functions available on the spreadsheet or through dedicated macro programming.
The applications are generally based on real data and problems related to Environmental and Georesources Engineering.
Assessment methods
The student must write a short dissertation, consisting of a real-case study chosen by the students themselves, based on the collected related data. The dissertation must show that the student is able to statistically process such data, computing aimed to solve the specific problem at hand. The final examination is based on the short dissertation.
Teaching tools
Lectures are based on presentations made by projection of power point files, either on applications to the computer spreadsheet, always guided by projection.
The course is conducted at a teaching laboratory-informatics of the Faculty. In addition to Microsoft Office programs, can be used geostatistical sw freeware.
Links to further information
http://serwebdicma.ing.unibo.it/labingmin
Office hours
See the website of Roberto Bruno