Publilius Syrus, Moral Sayings We've been very fortunate to receive fantastic feedback from our readers during the last four years, since the first edition of How to Solve It: Modern Heuristics was published in 1999. It's heartening to know that so many people appreciated the book and, even more importantly, were using the book to help them solve their problems. One professor, who published a review of the book, said that his students had given the best course reviews he'd seen in 15 years when using our text. There can be hardly any better praise, except to add that one of the book reviews published in a SIAM journal received the best review award as well. We greatly appreciate your kind words and personal comments that you sent, including the few cases where you found some typographical or other errors. Thank you all for this wonderful support.

    This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree- based methods, support vector machines, clustering, and more. Color graphics and real-world examples are used to illustrate the methods presented. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform. Two of the authors co-wrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers. An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra.

    John Taylor has brought to his new book, Classical Mechanics, all of the clarity and insight that made his introduction to Error Analysis a best-selling text.

    Information is provided on the fundamental concepts of table and graph design, the numbers and knowledge most suitable for display in a graphic form, the best tabular means to communicate certain ideas, and the component-level aspects of design. Analysts, technicians, and managers will appreciate the solid theory behind this outline for ensuring that tables and graphs present quantitative business information in a truthful, attractive format that facilitates better decision making.

    

    At the very heart of responsibility is industry and commerce, with everyone now racing to create their 'environmental' business strategy. In line with this awareness, there is much discussion about the 'green marketing opportunity' as a means of jumping on this bandwagon.We need to find a sustainable marketing that actually delivers on green objectives, not green theming. Marketers need to give up the many strategies and approaches that made sense in pure commercial terms but which are unsustainable. True green marketing must go beyond the ad models where everything is another excuse to make a brand "look" good; we need a green marketing that "does" good."The Green Marketing Manifesto" provides a roadmap on how to organize green marketing effectively and sustainably. It offers a fresh start for green marketing, one that provides a practical and ingenious approach. The book offers many examples from companies and brands who are making headway in this difficult arena, such as Marks & Spencer, Sky, Virgin, Toyota, Tesco, O2 to give an indication of the potential of this route. John Grant creates a 'Green Matrix' as a tool for examining current practice and the practice that the future needs to embrace. This book is intended to assist marketers, by means of clear and practical guidance, through a complex transition towards meaningful green marketing. Includes a foreword by Jonathon Porritt.

    From a life of luxury in the opulent city of Dubai to promised ruination, Jaubert tells a tale of espionage and escape that rivals any best selling novel on the market. Immersed in a luxury submarine business, Jaubert was hired as CEO by Dubai World to develop and design miniature subs for the wealthy. Once problems developed within the business, Herve Jaubert became the scapegoat of government officials and found himself ensnared in a web of police threats, extortion, human rights abuses and coercion. With no chance to make it through their biased legal system, Jaubert planned the escape of his life.

    Stories from the colonial era will both entertain and enthral readers. The author is very well-known in the Himachal as a prolific and an entertaining writer. About the Book: More Ghost Stories of Shimla Hills A collection of sixteen stories about the supernatural, originating from Shimla folklore and the days of the Raj. The haunted foothills of Himalayas present the perfect setting for the dark and sinister world of phantoms and apparitions. Many spirits wander about these hills-the English nurse, the theatre manager, the English lord and his sister, even a family of local ghosts Many of these are real encounters narrated by the inhabitants. With thrilling twists and turns, each story recreates the horror of the victims and the fear of the unknown. Get ready to be spooked! About the Author: Minakshi Chaudhry Minakshi Chaudhry, an author and former journalist, lives in Shimla with her husband. She is a keen observer of people, cultures, lifestyles, and loves trekking and travelling. Minakshi has authored several books-Sunshine: My Encounter with Cancer, Love Stories of Shimla Hills, Whispering Deodars: Writings from Shimla Hills, Destination Himachal: 132 Offbeat and 12 Popular Getaways, Ghost Stories of Shimla Hills, 65 Treks and Over 100 Destinations: A Guide to Trekking in Himachal, and Exploring Pangi Himalaya: A World Beyond Civilization. She is currently working on her next book and can be contacted at minakshi_kanwar@yahoo.com

    This is the currently used textbook for "Probabilistic Systems Analysis," an introductory probability course at the Massachusetts Institute of Technology, attended by a large number of undergraduate and graduate students. The book covers the fundamentals of probability theory (probabilistic models, discrete and continuous random variables, multiple random variables, and limit theorems), which are typically part of a first course on the subject. It also contains, a number of more advanced topics, from which an instructor can choose to match the goals of a particular course. These topics include transforms, sums of random variables, least squares estimation, the bivariate normal distribution, and a fairly detailed introduction to Bernoulli, Poisson, and Markov processes. The book strikes a balance between simplicity in exposition and sophistication in analytical reasoning. Some of the more mathematically rigorous analysis has been just intuitively explained in the text, but is developed in detail (at the level of advanced calculus) in the numerous solved theoretical problems. The book has been widely adopted for classroom use in introductory probability courses within the USA and abroad.

    In this collection, you will find images and poems that relate to life, love, loss, gain, realisation and the final thing called Moksha. The poems may sound philosophical, intellectual and emotional from time to time. You will also find a surprise at the end of this wonderful poetry collection if you read everything carefully. And, like the previous poetry collection by Alok Mishra, this book will also not take more than 15 minutes from your daily routine. However, you may want to read the book at least twice or maybe thrice to understand what do the poems mean. Alok has devised a style of his own to communicate his thoughts to the readers of Indian English poetry. A 4-3-6 style has perfectly settled with this collection having 14 wonderful poems. Here are some reviews for Moving for Moksha:The collection of poems takes us on a journey to ponder the truth and fallacies of life that come our way. The poems are mostly mystic in nature, having more than what it seems to be... you will certainly love it if you have a taste for English poetry.by: Amit Mishra (founder of The Indian Authors & Indian Book Lovers)...beauty, truth, eternity.... a very close observation of life, these poems sneak into nothing but the philosophy of life that people confront during life-span.by: Ravi Kumar, Research Scholar with expertise in Indian English Literature, a writer for many online literary platformsThe poems reflect disillusion, rejection, realisation and answer to the final call – Moksha, as called in Indian philosophy. The innovative form with a 4-3-6 pattern looks very apt for the emotional and intellectual and also cryptic nature of the poems in this collection.The Last Critic

    This connectedness is found in many incarnations: in the rapid growth of the Internet, in the ease with which global communication takes place, and in the ability of news and information as well as epidemics and financial crises to spread with surprising speed and intensity. These are phenomena that involve networks, incentives, and the aggregate behavior of groups of people; they are based on the links that connect us and the ways in which our decisions can have subtle consequences for others. This introductory undergraduate textbook takes an interdisciplinary look at economics, sociology, computing and information science, and applied mathematics to understand networks and behavior. It describes the emerging field of study that is growing at the interface of these areas, addressing fundamental questions about how the social, economic, and technological worlds are connected.

    However, these activities can be viewed as two facets of the same field, and together they have undergone substantial development over the past ten years. In particular, Bayesian methods have grown from a specialist niche to become mainstream, while graphical models have emerged as a general framework for describing and applying probabilistic models. Also, the practical applicability of Bayesian methods has been greatly enhanced through the development of a range of approximate inference algorithms such as variational Bayes and expectation propagation. Similarly, new models based on kernels have had a significant impact on both algorithms and applications. This new textbook reflects these recent developments while providing a comprehensive introduction to the fields of pattern recognition and machine learning. It is aimed at advanced undergraduates or first-year PhD students, as well as researchers and practitioners, and assumes no previous knowledge of pattern recognition or machine learning concepts. Knowledge of multivariate calculus and basic linear algebra is required, and some familiarity with probabilities would be helpful though not essential as the book includes a self-contained introduction to basic probability theory.

    This book gives you a solid understanding of statistics without being too simple, yet without the numbing complexity of most college texts. You get a firm grasp of the fundamentals and a hands-on understanding of how to apply them before moving on to the more advanced material that follows. Each chapter presents you with easy-to-follow descriptions illustrated by graphics, formulas, and plenty of solved examples. Before you know it, you'll learn to apply statistical reasoning and statistical techniques, from basic concepts of probability and hypothesis testing to multivariate analysis. Organized into four distinct sections, Statistics in a Nutshell offers you:Introductory material: Different ways to think about statistics Basic concepts of measurement and probability theoryData management for statistical analysis Research design and experimental design How to critique statistics presented by others Basic inferential statistics: Basic concepts of inferential statistics The concept of correlation, when it is and is not an appropriate measure of association Dichotomous and categorical data The distinction between parametric and nonparametric statistics Advanced inferential techniques: The General Linear Model Analysis of Variance (ANOVA) and MANOVA Multiple linear regression Specialized techniques: Business and quality improvement statistics Medical and public health statistics Educational and psychological statistics Unlike many introductory books on the subject, Statistics in a Nutshell doesn't omit important material in an effort to dumb it down. And this book is far more practical than most college texts, which tend to over-emphasize calculation without teaching you when and how to apply different statistical tests. With Statistics in a Nutshell, you learn how to perform most common statistical analyses, and understand statistical techniques presented in research articles. If you need to know how to use a wide range of statistical techniques without getting in over your head, this is the book you want.

    Republished in book form shortly thereafter, it has since gone through four hardcover and sixteen paperback printings. It is a revolutionary work, astounding in its foresight and contemporaneity. The University of Illinois Press is pleased and honored to issue this commemorative reprinting of a classic.

    Reflecting the need for even minor programming in today's model-based statistics, the book pushes readers to perform step-by-step calculations that are usually automated. This unique computational approach ensures that readers understand enough of the details to make reasonable choices and interpretations in their own modeling work.The text presents generalized linear multilevel models from a Bayesian perspective, relying on a simple logical interpretation of Bayesian probability and maximum entropy. It covers from the basics of regression to multilevel models. The author also discusses measurement error, missing data, and Gaussian process models for spatial and network autocorrelation.By using complete R code examples throughout, this book provides a practical foundation for performing statistical inference. Designed for both PhD students and seasoned professionals in the natural and social sciences, it prepares them for more advanced or specialized statistical modeling.Web ResourceThe book is accompanied by an R package (rethinking) that is available on the author's website and GitHub. The two core functions (map and map2stan) of this package allow a variety of statistical models to be constructed from standard model formulas.