INTRODUCTION TO STATISTICAL DATA ANALYSIS FOR THE PHYSICAL AND LIFE SCIENCES
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- Versione italiana
- Academic year
- 2015/2016
- Teacher
- ATTILA FELINGER
- Credits
- 6
- Didactic period
- Secondo Semestre
- SSD
- CHIM/01
Training objectives
- At the end of this class, students will possess the basic knowledge of the mathematical and statistical background needed for the processing of the chemical analysis data, design of experiments. The aim of the course is to give to students a fundamental understanding of the possibilities for treating experimental data obtained in laboratory measurements. After this class, students will be able to independently recognize the various types of problems and mathematical tools for data handling. With publicly available software and with professional packages they will be able to critically evaluate the goodness or confidence of measurement data. They will be able to extract seemingly hidden information from numerical data.
Prerequisites
- Basic knowledge of Analytical Chemistry and, possibly, concepts of Instrumental Analysis. Basics of calculus.
Course programme
- The class is made of 6 ECTS (European University Credits), 4 of which are theoretical lessons and the remaining 2 are practical calculations. The main subjects covered in this course are: characterization of analytical chemical measurements, measuring systems, instruments. Brief introduction to the fundamentals of probability theory, distributions, statistical moments. Random and systematic errors, their characterization and treatment, error propagation, parametric and nonparametric hypothesis tests (t-tests, F-test, variance analysis, etc). Correlation, linear regression, univariate calibration, multivariate calibration. Design of experiments, simplex optimization. Principal component analysis, classification, cluster analysis. Characterization of analog and digital signals.
Didactic methods
- The course comprises both theory and practical training. During the lectures the basis of the data treatments will be discussed. Then with the use of personal computers, the students can exercise with individual calculations, and data evaluation. Various public-domain software packages will also be used for the analysis of experimental data.
Learning assessment procedures
- The exam consists of a written examination where students will be asked to solve 2/4 exercises focusing on the main topics discussed in class. Personal computers, books and class notes are allowed during the test.
Reference texts
- 1) P. R. Bevongton, Data Reduction and Error Analysis for the Physical Sciences
2) J. N. Miller, J. C. Miller, Statistics and Chemometrics for Analytical Chemistry
3) P. C. Meier,R. E. Zünd, Statistical Methods in Analytical Chemistry
