When scientists formulate their theories, expectations, and hypotheses, they often use statements like: ``I expect mean A to be bigger than means B and C"; ``I expect that the relation between Y and both X1 and X2 is positive"; and ``I expect the relation between Y and X1 to be stronger than the relation between Y and X2". Stated otherwise, they formulate their expectations in terms of inequality constraints among the parameters in which they are interested, that is, they formulate Informative Hypotheses. There is currently a sound theoretical foundation for the evaluation of informative hypotheses using Bayes factors, p-values and the generalized order restricted information criterion. Furthermore, software that is often free is available to enable researchers to evaluate the informative hypotheses using their own data. The road is open to challenge the dominance of the null hypothesis for contemporary research in behavioral, social, and other sciences.

This book provides an overview of the developments in the area of Bayesian evaluation of informative hypotheses that took place since the publication of the ?rst paper on this topic in 2001 [Hoijtink, H. Con?rmatory latent class analysis, model selection using Bayes factors and (pseudo) likelihood ratio statistics. Multivariate Behavioral Research, 36, 563–588]. The current state of a?airs was presented and discussed by the authors of this book during a workshop in Utrecht in June 2007. Here we would like to thank all authors for their participation, ideas, and contributions. We would also like to thank Sophie van der Zee for her editorial e?orts during the construction of this book. Another word of thanks is due to John Kimmel of Springer for his con?dence in the editors and authors. Finally, we would like to thank the Netherlands Organization for Scienti?c Research (NWO) whose VICI grant (453-05-002) awarded to the ?rst author enabled the organization of the workshop, the writing of this book, and continuation of the research with respect to Bayesian evaluation of informative hypotheses.

This book provides an overview of the developments in the area of Bayesian evaluation of informative hypotheses that took place since the publication of the ?rst paper on this topic in 2001 [Hoijtink, H. Con?rmatory latent class analysis, model selection using Bayes factors and (pseudo) likelihood ratio statistics. Multivariate Behavioral Research, 36, 563–588]. The current state of a?airs was presented and discussed by the authors of this book during a workshop in Utrecht in June 2007. Here we would like to thank all authors for their participation, ideas, and contributions. We would also like to thank Sophie van der Zee for her editorial e?orts during the construction of this book. Another word of thanks is due to John Kimmel of Springer for his con?dence in the editors and authors. Finally, we would like to thank the Netherlands Organization for Scienti?c Research (NWO) whose VICI grant (453-05-002) awarded to the ?rst author enabled the organization of the workshop, the writing of this book, and continuation of the research with respect to Bayesian evaluation of informative hypotheses.

This monograph briefly formulates fundamental notions and results of Shannon theory on reliable transmission via coding and gives a survey of results obtained in last two-three decades by the authors.

Information theory and inference, taught together in this exciting textbook, lie at the heart of many important areas of modern technology - communication, signal processing, data mining, machine learning, pattern recognition, computational neuroscience, bioinformatics and cryptography. The book introduces theory in tandem with applications. Information theory is taught alongside practical communication systems such as arithmetic coding for data compression and sparse-graph codes for error-correction. Inference techniques, including message-passing algorithms, Monte Carlo methods and variational approximations, are developed alongside applications to clustering, convolutional codes, independent component analysis, and neural networks. Uniquely, the book covers state-of-the-art error-correcting codes, including low-density-parity-check codes, turbo codes, and digital fountain codes - the twenty-first-century standards for satellite communications, disk drives, and data broadcast. Richly illustrated, filled with worked examples and over 400 exercises, some with detailed solutions, the book is ideal for self-learning, and for undergraduate or graduate courses. It also provides an unparalleled entry point for professionals in areas as diverse as computational biology, financial engineering and machine learning.

"Biophilia" is the term coined by Edward O. Wilson to describe what he believes is humanity's innate affinity for the natural world. In his landmark book Biophilia, he examined how our tendency to focus on life and lifelike processes might be a biologically based need, integral to our development as individuals and as a species. That idea has caught the imagination of diverse thinkers. The Biophilia Hypothesis brings together the views of some of the most creative scientists of our time, each attempting to amplify and refine the concept of biophilia. The variety of perspectives -- psychological, biological, cultural, symbolic, and aesthetic -- frame the theoretical issues by presenting empirical evidence that supports or refutes the hypothesis. Numerous examples illustrate the idea that biophilia and its converse, biophobia, have a genetic component: fear, and even full-blown phobias of snakes and spiders are quick to develop with very little negative reinforcement, while more threatening modern artifacts -- knives, guns, automobiles -- rarely elicit such a response people find trees that are climbable and have a broad, umbrella-like canopy more attractive than trees without these characteristics people would rather look at water, green vegetation, or flowers than built structures of glass and concrete The biophilia hypothesis, if substantiated, provides a powerful argument for the conservation of biological diversity. More important, it implies serious consequences for our well-being as society becomes further estranged from the natural world. Relentless environmental destruction could have a significant impact on our quality of life, not just materially but psychologically and even spiritually.

Everything you need to pass Level II of the CMT Program CMT Level II 2016: Theory and Analysis fully prepares you to demonstrate competency applying the principles covered in Level I, as well as the ability to apply more complex analytical techniques. Covered topics address theory and history, market indicators, construction, confirmation, cycles, selection and decision, system testing, statistical analysis, and ethics. The Level II exam emphasizes trend, chart, and pattern analysis, as well as risk management concepts. This cornerstone guidebook of the Chartered Market Technician® Program will provide every advantage to passing Level II.