A Treatise on Probability

A Treatise on Probability
Author: John Maynard Keynes
Publisher: Courier Corporation
Total Pages: 484
Release: 2013-09-02
Genre: Mathematics
ISBN: 0486159647

Originally published in 1921, this mathematical work represents a significant contribution to the logical probability of propositions. Keynes effectively dismantled the classical theory, launching the "logical-relationist" theory of probability.

André-Louis Cholesky

André-Louis Cholesky
Author: Claude Brezinski
Publisher: Springer
Total Pages: 340
Release: 2014-08-06
Genre: Mathematics
ISBN: 3319081357

This book traces the life of Cholesky (1875-1918), and gives his family history. After an introduction to topography, an English translation of an unpublished paper by him where he explained his method for linear systems is given, studied and replaced in its historical context. His other works, including two books, are also described as well as his involvement in teaching at a superior school by correspondence. The story of this school and its founder, Léon Eyrolles, are addressed. Then, an important unpublished book of Cholesky on graphical calculation is analyzed in detail and compared to similar contemporary publications. The biography of Ernest Benoit, who wrote the first paper where Cholesky ́s method is explained, is provided. Various documents, highlighting the life and the personality of Cholesky, end the book.

Publisher and Bookseller

Publisher and Bookseller
Author:
Publisher:
Total Pages: 962
Release: 1868
Genre: Bibliography
ISBN:

Vols. for 1871-76, 1913-14 include an extra number, The Christmas bookseller, separately paged and not included in the consecutive numbering of the regular series.

Methods of Microarray Data Analysis III

Methods of Microarray Data Analysis III
Author: Kimberly F. Johnson
Publisher: Springer Science & Business Media
Total Pages: 247
Release: 2007-05-08
Genre: Science
ISBN: 0306483548

As microarray technology has matured, data analysis methods have advanced as well. Methods Of Microarray Data Analysis III is the third book in this pioneering series dedicated to the existing new field of microarrays. While initial techniques focused on classification exercises (volume I of this series), and later on pattern extraction (volume II of this series), this volume focuses on data quality issues. Problems such as background noise determination, analysis of variance, and errors in data handling are highlighted. Three tutorial papers are presented to assist with a basic understanding of underlying principles in microarray data analysis, and twelve new papers are highlighted analyzing the same CAMDA'02 datasets: the Project Normal data set or the Affymetrix Latin Square data set. A comparative study of these analytical methodologies brings to light problems, solutions and new ideas. This book is an excellent reference for academic and industrial researchers who want to keep abreast of the state of art of microarray data analysis.