Advanced Data Analysis for Research and Engineering Practice
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The book describes the theoretical principles of nonstatistical methods of data analysis but without going deep into complex mathematics. The emphasis is laid on presentation of solved examples of real data either from authors' laboratories or from open literature. The examples cover wide range of applications such as quality assurance and quality control, critical analysis of experimental data, comparison of data samples from various sources, robust linear and nonlinear regression as well as various tasks from financial analysis. The examples are useful primarily for chemical engineers including analytical/quality laboratories in industry, designers of chemical and biological processes.
- Exclusive title on Mathematical Gnostics with multidisciplinary applications, and specific focus on chemical engineering.
- Clarifies the role of data space metrics including the right way of aggregation of uncertain data.
- Brings a new look on the data probability, information, entropy and thermodynamics of data uncertainty.
- Enables design of probability distributions for all real data samples including smaller ones.
- Includes data for examples with solutions with exercises in R or Python.
The book is aimed for Senior Undergraduate Students, Researchers, and Professionals in Chemical/Process Engineering, Engineering Physics, Stats, Mathematics, Materials, Geotechnical, Civil Engineering, Mining, Sales, Marketing and Service, and Finance.
Table of Contents
1. Introductory Kindergarten. 2. Axioms. 3. Introduction to Non-Standard Thought. 4. Quantification. 5. Estimation and Ideal Gnostic Cycle. 6. Geometry. 7. Aggregation. 8. Thermodynamics of Uncertain Data. 9. Kernel estimation. 10. Probability Distribution Functions. 11. Applications of Local Distributions. 12. On the Notion of Normality. 13. Applications of Global Distribution Functions. 14. Data Censoring. 15. Gnostic Thermodynamic Analysis of Data Uncertainty. 16. Robust Estimation of a Constant. 17. Measuring the Data Uncertainty. 18. Homo- or Heteroscedastic Data. 19. Gnostic Multidimensional Regression Models. 20. Data Filtering. 21. Decision Making in Mathematical Gnostics. 22. Comparisons. 23. Advanced Production Quality Control. 24. Robust Correlation. 25. General Relations.
Pavel Kovanic (Born 1928) 1950-1955: Studied high voltage technology on the Technical University in Sverdlovsk (recently Ekaterinburg, Russia). 1956-1970: Researcher, head of a scientific department at the Nuclear Research Institute of the Czechoslovak Academy of Sciences. 1970-1995: Scientist at the Institute of the Automation and Theory of Information of the Czech Academy of Sciences. 1995-2018: As a retired scientist participated as a scientific consultant on several research projects including grants of European Union.
Zdenek Wagner born in 1957 in Prague, Czech Republic (formerly Czechoslovakia). He obtained master degree in physical chemistry from the Institute of Chemical Technology in Prague. The topic of his work was related to experimental determination of enthalpies of vaporization as well as theoretical modelling. After completion in 1981 he continued with PhD study in the Institute of Chemical Process Fundamentals of the CAS. He dealt with measurement of vapour-liquid equilibria at high pressure in systems related to supercritical fluid extraction. He finished PhD in 1985 and continues to work at the same institute. Later he extended his research activities to liquid-liquid equilibria and thermochemical properties of liquids. He deals mainly with nonstatistical methods of data analysis including reliable critical evaluation not only in thermodynamics but also in chemistry and physics of atmosphere. He is also active as a programmer of databases and measuring systems communicating over a public network. This serves to him as a strong motivation for development of reliable methods of data analysis working automatically without human interaction.
Magdalena Bendova graduated in physical chemistry at the University of Chemistry and Technology in Prague. After obtaining her PhD at the same university, she joined the Institute of Chemical Process Fundamentals of the Czech Academy of Sciences where she currently leads the research group of Thermodynamics of Task-Specific Materials. Her research interests include phase behaviour of pure compounds and multicomponent mixtures, thermodynamic properties of ionic liquids, and a comprehensive approach towards material characterization, particularly with respect to thermal energy storage.
Jan Rotrekl born 1986 in Prague. He obtained master degree in physical chemistry at the University of Chemistry and Technology in Prague. Since 2013 he continues with PhD study at the Institute of Chemical Process Fundamentals of the Czech Academy of Sciences as a member of group of Thermodynamics of Task-Specific Materials. His research interests are focused on measurement of phase equilibria and physio-chemical characterization of pure substances and mixtures.