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Il volume contiene in forma compatta il programma svolto negli insegnamenti introduttivi di statistica e tratta alcuni argomenti indispensabili per l'attività di ricerca, come ad esempio i metodi di simulazione Monte Carlo, le procedure di minimizzazione e le tecniche di analisi dei dati di laboratorio. Gli argomenti vengono sviluppati partendo dai fondamenti, evidenziandone gli aspetti applicativi, fino alla descrizione dettagliata di molti casi di particolare rilevanza in ambito scientifico e tecnico. Numerosi esempi ed esercizi risolti valorizzano l'opera ed aiutano il lettore nella comprensione dei punti più difficili ed importanti. Come ulteriore supporto, questa seconda edizione contiene molti programmi applicativi scritti col software libero Scilab, scaricabili dal sito web creato dagli autori. Il testo è rivolto agli studenti universitari dei corsi ad indirizzo scientifico e a tutti quei ricercatori che devono risolvere problemi concreti che coinvolgono aspetti statistici e  di simulazione. Per i programmi in Scilab e per il materiale ausiliario si veda: http://www.mi.imati.cnr.it/~marco/springer/index.html 

Statistical physics --- Engineering sciences. Technology --- statistische kwaliteitscontrole --- industriële statistieken

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Industrial statistics. --- 311:338.45 --- statistique --- nijverheid --- ocde --- Industriële statistieken --- statistiek --- industrie --- oeso --- 311:338.45 Industriële statistieken

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This is a textbook which gradually introduces the student to the statistical mechanical study of the different phases of matter and to the phase transitions between them. Throughout, only simple models of both ordinary and soft matter are used but these are studied in full detail. The subject is developed in a pedagogical manner, starting from the basics, going from the simple ideal systems to the interacting systems, and ending with the more modern topics. The latter include the renormalisation group approach to critical phenomena, the density functional theory of interfaces, the topological defects of nematic liquid crystals and the kinematic aspects of the phase transformation process. This textbook provides the student with a complete overview, intentionally at an introductory level, of the theory of phase transitions. References include suggestions for more detailed treatments and four appendices supply overviews of the mathematical tools employed in the text.

Fluid mechanics --- Statistical physics --- Thermodynamics --- thermodynamica --- materie (fysica) --- statistische kwaliteitscontrole --- industriële statistieken --- statistiek --- fysica --- vloeistoffen

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No statistical model is "true" or "false," "right" or "wrong"; the models just have varying performance, which can be assessed. The main theme in this book is to teach modeling based on the principle that the objective is to extract the information from data that can be learned with suggested classes of probability models. The intuitive and fundamental concepts of complexity, learnable information, and noise are formalized, which provides a firm information theoretic foundation for statistical modeling. Inspired by Kolmogorov's structure function in the algorithmic theory of complexity, this is accomplished by finding the shortest code length, called the stochastic complexity, with which the data can be encoded when advantage is taken of the models in a suggested class, which amounts to the MDL (Minimum Description Length) principle. The complexity, in turn, breaks up into the shortest code length for the optimal model in a set of models that can be optimally distinguished from the given data and the rest, which defines "noise" as the incompressible part in the data without useful information. Such a view of the modeling problem permits a unified treatment of any type of parameters, their number, and even their structure. Since only optimally distinguished models are worthy of testing, we get a logically sound and straightforward treatment of hypothesis testing, in which for the first time the confidence in the test result can be assessed. Although the prerequisites include only basic probability calculus and statistics, a moderate level of mathematical proficiency would be beneficial. The different and logically unassailable view of statistical modelling should provide excellent grounds for further research and suggest topics for graduate students in all fields of modern engineering, including and not restricted to signal and image processing, bioinformatics, pattern recognition, and machine learning to mention just a few. The author is an Honorary Doctor and Professor Emeritus of the Technical University of Tampere, Finland, a Fellow of Helsinki Institute for Information Technology, and visiting Professor in the Computer Learning Research Center of University of London, Holloway, England. He is also a Foreign Member of Finland's Academy of Science and Letters, an Associate Editor of IMA Journal of Mathematical Control and Information and of EURASIP Journal on Bioinformatics and Systems Biology. He is also a former Associate Editor of Source Coding of IEEE Transactions on Information Theory. The author is the recipient of the IEEE Information Theory Society's 1993 Richard W. Hamming medal for fundamental contributions to information theory, statistical inference, control theory, and the theory of complexity; the Information Theory Society's Golden Jubilee Award in 1998 for Technological Innovation for inventing Arithmetic Coding; and the 2006 Kolmogorov medal by University of London. He has also received an IBM Corporate Award for the MDL and PMDL Principles in 1991, and two best paper awards.

Ergodic theory. Information theory --- Statistical physics --- Engineering sciences. Technology --- statistische kwaliteitscontrole --- coderen --- industriële statistieken --- informatietheorie

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This book includes the keynote lecture and fourteen selected papers that - scribe a general guideline and supporting concepts and tools for conceiving technology development as a grammar. Recent advances in scienti?c and - gineering ?elds call for new disciplines, tools, and concepts. For example, advances in computer simulation require new approaches to statistical te- niques to utilize computer simulation e?ciently for technology development. Thepaperscollectedinthisbookfocusonsuchnewapproachesbasedonthese practicalrequirements.Theeditorsarecon?dentthiscollectionwillcontribute to the acceleration of technology development through the application of the grammar of technology presented here. The title of this book is in?uenced by Karl Pearson's book The Grammar of Science, published in 1892, which brought him recognition as a giant and pioneer of statistics. His book introduced a grammar of science with a - scription of the roles of statistical treatments. While science at times has been misunderstood as not being amenable to a standardized approach, one of the contributions of Pearson's book was that it o?ered a standardized - proach to science. As his book demonstrated, behind the great innovations of science, there exists a universal approach.

Statistical physics --- Engineering sciences. Technology --- statistische kwaliteitscontrole --- analyse (wiskunde) --- industriële statistieken --- ingenieurswetenschappen