Course Syllabus (PDF)

Course Syllabus

Synopsis

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.

Aims

Provide students with an overview of the most important chemometric tools available for processing environmental data, enabling them to select the most appropriate tool for each specific case.

Objectives

At the end of this Unit, you should:

  1. select the most appropriate statistical/chemometric tool that allows you to obtain the maximum information from your data in each specific case.
  2. correctly interpret environmental outcomes from large data sets

Key skills acquired

At the end of this Unit, you should be ableto select and apply the most appropriate multivariate approach for a correct interpretation of your environmental data.

Syllabus

Topics covered include:

  • Basic statistics (descriptive and inference)
  • Pattern recognition, Principal component analysis
  • Classification techniques, Discriminant analysis, SIMCA.
  • Regression techniques, PCR, PLS

Learning & Teaching

  • Lectures: 20 hr
  • Computer work: 15 hr
  • Seminars and tutorials: 5 hr

Teaching Staff: Alberto de Diego (Coord.), Juan Manuel Madariaga; Mireia Irazola

Semester: 2

Timetable slot: To be advised

ECTS: 4    

Level: Optional

Bibliography

Basic

  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

Detailed

  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

Assessment

  • Written theory examination (40%)
  • Computer work and report (30%)
  • Bibliographic survey and oral presentation (20%)
  • Lecture attendance (10%)

Course Evaluation

By completion of University Unit Evaluation Questionnaire by students, annual assessment by Unit Coordinator.

Course Syllabus (PDF)