Applied Data Mining for Business and Industry,2 ed
The increasing availability of data in our current, information overloaded society has led to the need for valid tools for its modelling and analysis. Data mining and applied statistical methods are the appropriate tools to extract knowledge from such data. This book pres an accessible introduction to data mining methods in a consistent and application oriented statistical framework, using case studies drawn from real industry projects and highlighting the use of data mining methods in a variety of business applications.
Written by a renowned statistician, this book presents the basic ideas behind the statistical methods commonly used in studies of human subjects. It is an ideal guide for advanced undergraduates who are beginning to do their own research. It presents the basic principles in a non-mathematical way and is accessible to a wide audience with little background in statistics.
The Akaike information criterion (AIC) derived as an estimator of the Kullback-Leibler information discrepancy provides a useful tool for evaluating statistical models, and numerous successful applications of the AIC have been reported in various fields of natural sciences, social sciences and engineering.
Statistical Mechanics and Stability of Macromolecules: Application to Bond Disruption, Base Pair Separation, Melting, and Drug Dissociation of the DNAApplication to Bond Disruption, Base Pair Separation, Melting, and Drug Dissociation of the DNA
This book develops a statistical mechanical analysis of the stability of biological macromolecules. The author's approach is valid both for the long time-scale needed for DNA bond disruption, and also for highly cooperative transitions needed to explain helix melting.
Statistical Methods in Genetic Epidemiology By Duncan C. Thomas
* Number Of Pages: 464 * Publication Date: 2004-01-29
Product Description: Univ. of Southern California, Los Angeles. Focuses on methods of identifying the joint effects of genes and environment on disease patterns. Features the study designs and statistical analysis techniques for determining whether a trait runs in families, estimating the parameters of genetic model, or whether a genetic tendency is due to genetic or environmental factors.
