Description and contextualization of the subject

This course is an introduction to the application of statistic and chemometric tools to the analysis of data obtained mainly, but not only, after chemical analysis of a large variety of environmental samples. Descriptive and inference statistics are briefly reviewed, and the most important multivariate techniques for pattern recognition, classification and regression are also deeply investigated. Rather than on the mathematical detail, the course focuses on understanding the basic concepts behind each technique, and on selecting the most appropriate tool in each specific situation. The theoretical basis of the techniques considered will be illustrated by the resolution of exercises and case studies.

Learning outcomes of the subject

The student should be able to interpret correctly large series of data coming from the analysis of environmental samples, making use of the appropriate statistical and chemometric techniques and methods in each specific case.

Ordinary call: orientations and renunciation

The evaluation of this course will be of a mixed type. The final score will be obtained as the weighted average of the following sections: i) Lecture attendance (10%), bibliographic survey (20%), iii) practical tasks (30%) and iv) written examination (40%). A minimum score of 5.0 in each section will be required to pass the course. If the student waives the call, she/he will be graded as not presented.

Extraordinary call: orientations and renunciation

The extraordinary examination will be carried out in similar conditions than the ordinary one. If the student passed with a minimum grade of 5.0 any activity of the course that was already evaluated in the ordinary call, those activities will be taken into account in the extraordinary one. If the student waives the call, she/he will be graded as not presented.

Temary

1.- Introduction: statistics, chemometrics, environmental analysis, multivariate data analysis

2.- Basic statistics: descriptive and inference statistics

3.- Exploratory analysis

4.- Pattern recognition

5.- Classification

6.- Calibration and regression

Bibliography

Compulsory materials

Personal computer

Basic bibliography

1.- M. Otto, Chemometrics, Statistics and Computer Application in Analytical Chemistry, Wiley, Weinheim, 1999

2.- D. A. Skoog, D. M. West, F. J. Holler, S. R. Crouch, Fundamentals of Analytical Chemistry, 8th edition, Thomson Brooks-Cole, Belmont, 2004

3.- J. N. Miller, J. C. Miller, Estatistics and Chemometrics for Analytical Chemistry, 4th edition, Pearson Education, Essex, 2000

4.- G. Ramis, M. C. García, Quimiometría, Síntesis, Madrid, 2001

5.- K. H. Esbensen, Multivariate Data Analysis – in Practice, 5th edition, CAMO Process AS, 2004

In-depth bibliography

1.- B. Kendall, C. Costello, Data Analysis for Environmental Science and Management, (http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.115.4159&rep=rep1&type=pdf)



2.- G. Hanrahan, Environmental Chemometrics: Principles and Modern Applications, CRC Press, Boca Ratón, 2009



3.- J. W. Einax, H. W. Zwanziger, S. Geiss, Chemometrics in Environmental Analysis, VCH, Hamburg, 1997

Journals

Chemometrics and Intelligent Laboratory systems



Journal of Chemometrics



Environmentrics

Links

https://www.youtube.com/user/QualityAndTechnology/videos?view=0



https://www.statisticshowto.com/probability-and-statistics/multivariate-analysis/