Statistical Physics

An Advanced Approach with Applications Web-enhanced with Problems and Solutions

Josef Honerkamp

PDF
ca. 89,86
Amazon iTunes Thalia.de Hugendubel Bücher.de ebook.de kobo Osiander Google Books Barnes&Noble bol.com Legimi yourbook.shop Kulturkaufhaus ebooks-center.de
* Affiliatelinks/Werbelinks
Hinweis: Affiliatelinks/Werbelinks
Links auf reinlesen.de sind sogenannte Affiliate-Links. Wenn du auf so einen Affiliate-Link klickst und über diesen Link einkaufst, bekommt reinlesen.de von dem betreffenden Online-Shop oder Anbieter eine Provision. Für dich verändert sich der Preis nicht.

Springer Berlin Heidelberg img Link Publisher

Naturwissenschaften, Medizin, Informatik, Technik / Naturwissenschaften allgemein

Beschreibung

The application of statistical methods to physics is essen- tial. This unique book on statistical physics offers an advanced approach with numerous applications to the modern problems students are confronted with. Therefore the text contains more concepts and methods in statistics than the student would need for statistical mechanics alone. Methods from mathematical statistics and stochastics for the analy- sis of data are discussed as well. The book is divided into two parts, focusing first on the modeling of statistical systems and then on the analysis of these systems. Problems with hints for solution help the students to deepen their knowledge. The second edition has been updated and enlarged with new material on estimators based on a probability dis- tribution for the parameters, identification of stochastic models from observations, and statistical tests and classi- fication methods (Chaps. 10-12). Moreover, a customized set of set of problems with solutions is accessible on the Web.

Weitere Titel in dieser Kategorie
Cover Astrobiology
Andrew May
Cover Living Matter
Alexander Levine
Cover Untitled
Christian Davenport
Cover Unequal
Eugenia Cheng
Cover Life's Devices
Steven Vogel
Cover Nature's Genius
David Farrier
Cover Sex Is a Spectrum
Agustín Fuentes

Kundenbewertungen