You will use it from high school to college and beyond. The full version is absolutely FREE. Features Conversion of over 1,000 units. Metric, English, and US customary systems. Length, Area, Volume, Speed, Force, Energy, Electricity, Viscosity, Temperature, and more. List of powers of 10 prefixes. Explanation of SI writing style. Approximate conversion of units. Clear and concise explanations. Difficult concepts are explained in simple terms. Navigate from Table of Contents or search for words or phrases. Add bookmarks and annotation. Access the guide anytime, anywhere - at home, on the train, in the subway. Use your down time to prepare for an exam. Always have the guide available for a quick reference. Indispensable resource for technical and life science students. The full version is absolutely FREE. FREE updates. Table of Contents Conversion of units: Length: Definition | Conversion Area: Definition | 2-D Formulae | 3-D Formulae | Conversion Volume: Definition | Formulae | Conversion Angle: Definition | Conversion Mass: Definition | Conversion Time: Definition | Conversion Speed: Definition | Conversion Acceleration: Definition | Conversion Force: Definition | Conversion Pressure or mechanical stress: Definition | Conversion Energy, work, or heat: Definition | Conversion Power: Definition | Conversion Angular momentum: Definition | Conversion Electricity: Current | Charge | Resistance | Voltage | Formulae | Conversion Viscosity: Definition | Conversion Information entropy: Definition | Conversion Temperature: Definition | Conversion Approximate conversion of units History: Systems of measurement | History of measurement Metric system (SI): Definition | SI writing style | Powers of 10 prefixes Other Systems: English system | Imperial unit | United States customary units | Comparison of the Imperial and U.S. customary systems

    The presentation is never awkward or dry, as it sometimes is in other "modern" textbooks; it is as unconventional as one has come to expect from the author. The book contains about 350 well placed and instructive problems, which cover a considerable part of the subject. All in all, this is an excellent work, of equally high value for both student and teacher." Zentralblatt f�r Mathematik

    Individual chapters discuss the representativeness and availability heuristics, problems in judging covariation and control, overconfidence, multistage inference, social perception, medical diagnosis, risk perception, and methods for correcting and improving judgments under uncertainty. About half of the chapters are edited versions of classic articles; the remaining chapters are newly written for this book. Most review multiple studies or entire subareas of research and application rather than describing single experimental studies. This book will be useful to a wide range of students and researchers, as well as to decision makers seeking to gain insight into their judgments and to improve them.

    Each sketch contains Questions and Projects to help you learn more about its topic and to see how its main ideas fit into the bigger picture of history. The 25 short stories are preceded by a 56-page bird's-eye overview of the entire panorama of mathematical history, a whirlwind tour of the most important people, events, and trends that shaped the mathematics we know today. Reading suggestions after each sketch provide starting points for readers who want to pursue a topic further."

    The science of complexity studies how single elements, such as a species or a stock, spontaneously organize into complicated structures like ecosystems and economies; stars become galaxies, and snowflakes avalanches almost as if these systems were obeying a hidden yearning for order. Drawing from diverse fields, scientific luminaries such as Nobel Laureates Murray Gell-Mann and Kenneth Arrow are studying complexity at a think tank called The Santa Fe Institute. The revolutionary new discoveries researchers have made there could change the face of every science from biology to cosmology to economics. M. Mitchell Waldrop's groundbreaking bestseller takes readers into the hearts and minds of these scientists to tell the story behind this scientific revolution as it unfolds.

    The rise of the Internet and the wide availability of inexpensive computers have made it possible to gather and analyze network data on a large scale, and the development of a variety of new theoretical tools has allowed us to extract new knowledge from many different kinds of networks.The study of networks is broadly interdisciplinary and important developments have occurred in many fields, including mathematics, physics, computer and information sciences, biology, and the social sciences. This book brings together for the first time the most important breakthroughs in each of these fields and presents them in a coherent fashion, highlighting the strong interconnections between work in different areas.Subjects covered include the measurement and structure of networks in many branches of science, methods for analyzing network data, including methods developed in physics, statistics, and sociology, the fundamentals of graph theory, computer algorithms, and spectral methods, mathematical models of networks, including random graph models and generative models, and theories of dynamical processes taking place on networks.

    Why did it take so long for him to win the Nobel Prize? What kind of a father was Einstein to his boys? How did his marriages affect his work? What motivated him? And most importantly; what unlocked his mind to grapple with the most profound ideas of all time? Inside you will read about... ✓ Einstein

    if you want to understand how the concept of life is changing, read this' Professor Andrew Briggs, University of OxfordWhen Darwin set out to explain the origin of species, he made no attempt to answer the deeper question: what is life? For generations, scientists have struggled to make sense of this fundamental question. Life really does look like magic: even a humble bacterium accomplishes things so dazzling that no human engineer can match it. And yet, huge advances in molecular biology over the past few decades have served only to deepen the mystery. So can life be explained by known physics and chemistry, or do we need something fundamentally new?In this penetrating and wide-ranging new analysis, world-renowned physicist and science communicator Paul Davies searches for answers in a field so new and fast-moving that it lacks a name, a domain where computing, chemistry, quantum physics and nanotechnology intersect. At the heart of these diverse fields, Davies explains, is the concept of information: a quantity with the power to unify biology with physics, transform technology and medicine, and even to illuminate the age-old question of whether we are alone in the universe.From life's murky origins to the microscopic engines that run the cells of our bodies, The Demon in the Machine is a breath-taking journey across the landscape of physics, biology, logic and computing. Weaving together cancer and consciousness, two-headed worms and bird navigation, Davies reveals how biological organisms garner and process information to conjure order out of chaos, opening a window on the secret of life itself.

    Gamow, physicist and gifted writer, has sketched an intriguing portrait of the scientists and clashing ideas that made the quantum revolution…”—Christian Science MonitorIn 1900, German physicist Max Planck postulated that light, or radiant energy can exist only in the form of discrete packages or quanta. This profound insight, along with Einstein's equally momentous theories of relativity, completely revolutionized man's view of matter, energy, and the nature of physics itself.In this lucid layman's introduction to quantum theory, an eminent physicist and noted popularizer of science traces the development of quantum theory from the turn of the century to about 1930—from Planck's seminal concept (still developing) to anti-particles, mesons and Enrico Fermi's nuclear research. Gamow was not just a spectator at the theoretical breakthroughs which fundamentally altered our view of the universe, he was an active participant who made important contributions of his own. This “insider's” vantage point lends special validity to his careful, accessible explanation of Heisenberg's Uncertainty Principle, Neils Bohr's model of the atom, the pilot waves of Louis de Broglie and other path-breaking ideas.In addition, Gamow recounts a wealth of revealing personal anecdotes which give a warm human dimension to many giants of 20th-century physics. He end the book with the Blegdamsvej Faust, a delightful play written in 1932 by Niels Bohr's students and colleagues to satirize the epochal developments that were revolutionizing physics. This celebrated play is available only in this volume.Written in a clear, lively style, and enhanced by 12 photographs (including candid shots of Rutherford, Bohr, Pauli, Heisenberg, Fermi and other notables), Thirty Years that Shook Physics offers both scientists and laymen a highly readable introduction to the brilliant conception that helped unlock many secrets of energy and matter and laid the groundwork for future discoveries.(Back Cover)

    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 is a fascinating and accessible summary of Roger Penrose's current thinking on those areas of physics in which he feels there are major unresolved problems. It is also a stimulating introduction to the radically new concepts that he believes will be fruitful in understanding the workings of the brain and the nature of the human mind.

    In his own words: "Dare to be naive... It is one of our most exciting discoveries that local discovery leads to a complex of further discoveries."

    This work represents the views of a mathematician on the analogies between computing machines and the living human brain.

    Readerswill find information on frequency distributions; mean, median, and mode; range, variance, and standard deviation;probability; and more.-Emphasizes Microsoft Excel for number-crunching and computationsDownload a sample chapter.

    Such systems--whether political parties, stock markets, or ant colonies--present some of the most intriguing theoretical and practical challenges confronting the social sciences. Engagingly written, and balancing technical detail with intuitive explanations, Complex Adaptive Systems focuses on the key tools and ideas that have emerged in the field since the mid-1990s, as well as the techniques needed to investigate such systems. It provides a detailed introduction to concepts such as emergence, self-organized criticality, automata, networks, diversity, adaptation, and feedback. It also demonstrates how complex adaptive systems can be explored using methods ranging from mathematics to computational models of adaptive agents. John Miller and Scott Page show how to combine ideas from economics, political science, biology, physics, and computer science to illuminate topics in organization, adaptation, decentralization, and robustness. They also demonstrate how the usual extremes used in modeling can be fruitfully transcended.