INTRODUCTION TO STATISTICAL DATA ANALYSIS FOR THE PHYSICAL AND LIFE SCIENCES
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- Versione italiana
- Academic year
- 2022/2023
- Teacher
- CHIARA DE LUCA
- Credits
- 6
- Didactic period
- Primo Semestre
- SSD
- CHIM/01
Training objectives
- The main aim of this course is to teach how to approach real laboratory data correctly, from a statistical point of view. The fundamentals of mathematics and statistics, necessary to process the experimental analysis data and to plan experiments according to the design of experiments, will be provided.
At the end of the course, students will be able to treat and to evaluate data obtained in laboratory measurements, to face different types of statistical problems and to handle experimental analytical data. Also, they will be able to choose a statistical model to be applied to real-case results and to establish its goodness. Prerequisites
- Basic knowledge of Analytical Chemistry, Algebra and Mathematical analysis is required.
Course programme
- The class is made of 6 ECTS (European University Credits), for a total of 36 hours.
The main subjects covered in this course are the following:
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.
Use of softwares for statistical data analysis (Excel, basics of Matlab).
Practical applications of statistical models to real-case results (exercises). Didactic methods
- The course comprises both theory and exercises. During the lectures the basis of the data treatments will be discussed. Then with the use of personal computers, the students will be guided to solve statistical problems applied to real data. 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 exercises 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.
Further reading:
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
