Bayesian inference provides a simple and unified approach to data analysis, allowing experimenters to assign probabilities to competing hypotheses of interest, on the basis of the current state of knowledge. By incorporating relevant prior information, it can sometimes improve model parameter estimates by many orders of magnitude. This book provides a clear exposition of the underlying concepts with many worked examples and problem sets. It also discusses implementation, including an introduction to Markov chain Monte-Carlo integration and linear and nonlinear model fitting. Particularly extensive coverage of spectral analysis (detecting and measuring periodic signals) includes a self-contained introduction to Fourier and discrete Fourier methods. There is a chapter devoted to Bayesian inference with Poisson sampling, and three chapters on frequentist methods help to bridge the gap between the frequentist and Bayesian approaches. Supporting Mathematica® notebooks with solutions to selected problems, additional worked examples, and a Mathematica tutorial are available at www.cambridge.org/9780521150125.
Information Theory and Statistics: A Tutorial Information Theory and Statistics: A Tutorial is concerned with applications of information theory concepts in statistics, in the finite alphabet setting. The topics covered include large deviations, hypothesis testing, maximum likelihood estimation in exponential families, analysis of contingency tables, and iterative algorithms with an... Calculus I with Precalculus (Textbooks Available with Cengage Youbook)
CALCULUS I WITH PRECALCULUS, brings you up to speed algebraically within precalculus and transition into calculus. The Larson Calculus program has been widely praised by a generation of students and professors for its solid and effective pedagogy that addresses the needs of a broad range of teaching and learning styles and environments. Each...
Level Up Your Web Apps With Go: Performance, Concurrency, Scalability
Go is an open-source language from Google that's a bit like C. Designed for programmer productivity, it's got a clean syntax, and emphasizes concurrency.
This book gives you all you need to use Go in your web applications. You'll learn the basic concepts - language structures, the standard library, and Go...
Analytics: The Agile Way (Wiley and SAS Business Series)
For decades now, companies big and small have embraced Agile software development methods. The rationale here is straightforward:
Why take one or two years to fully deploy a system, app, or website when so many things can and do go wrong?
Why try to cook one big batch and boil the ocean?