How can it be possible that the world we see is not objective reality? And how can our senses be useful if they are not communicating the truth? Hoffman grapples with these questions and more over the course of this eye-opening work.Ever since Homo sapiens has walked the earth, natural selection has favored perception that hides the truth and guides us toward useful action, shaping our senses to keep us alive and reproducing. We observe a speeding car and do not walk in front of it; we see mold growing on bread and do not eat it. These impressions, though, are not objective reality. Just like a file icon on a desktop screen is a useful symbol rather than a genuine representation of what a computer file looks like, the objects we see every day are merely icons, allowing us to navigate the world safely and with ease.The real-world implications for this discovery are huge. From examining why fashion designers create clothes that give the illusion of a more “attractive” body shape to studying how companies use color to elicit specific emotions in consumers, and even dismantling the very notion that spacetime is objective reality, The Case Against Reality dares us to question everything we thought we knew about the world we see.

    Widely praised and much-discussed, this classic book explores how cooperation can emerge in a world of self-seeking egoists—whether superpowers, businesses, or individuals—when there is no central authority to police their actions. The problem of cooperation is central to many different fields. Robert Axelrod recounts the famous computer tournaments in which the “cooperative” program Tit for Tat recorded its stunning victories, explains its application to a broad spectrum of subjects, and suggests how readers can both apply cooperative principles to their own lives and teach cooperative principles to others.

    It explains how it was a premeditated, orchestrated deception, using science to impose a political agenda. It fooled a majority including most scientists. They assumed that other scientists would not produce science for a political agenda. German Physicist and meteorologist Klaus-Eckart Puls finally decided to look for himself. Here is what he discovered. Ten years ago I simply parroted what the IPCC told us. One day I started checking the facts and data—first I started with a sense of doubt but then I became outraged when I discovered that much of what the IPCC and the media were telling us was sheer nonsense and was not even supported by any scientific facts and measurements. To this day I still feel shame that as a scientist I made presentations of their science without first checking it.…scientifically it is sheer absurdity to think we can get a nice climate by turning a CO2 adjustment knob. This book uses the same approach used in investigative journalism. It examines the Who, What, Where, When, Why, and How.

    Michael Guillen, known to millions as the science editor of ABC's Good Morning America, tells the fascinating stories behind five mathematical equations. As a regular contributor to daytime's most popular morning news show and an instructor at Harvard University, Dr. Michael Guillen has earned the respect of millions as a clear and entertaining guide to the exhilarating world of science and mathematics. Now Dr. Guillen unravels the equations that have led to the inventions and events that characterize the modern world, one of which -- Albert Einstein's famous energy equation, E=mc2 -- enabled the creation of the nuclear bomb. Also revealed are the mathematical foundations for the moon landing, airplane travel, the electric generator -- and even life itself. Praised by Publishers Weekly as "a wholly accessible, beautifully written exploration of the potent mathematical imagination," and named a Best Nonfiction Book of 1995, the stories behind The Five Equations That Changed the World, as told by Dr. Guillen, are not only chronicles of science, but also gripping dramas of jealousy, fame, war, and discovery. Dr. Michael Guillen is Instructor of Physics and Mathematics in the Core Curriculum Program at Harvard University.

    

    However, most discussions of Bayesian inference rely on intensely complex mathematical analyses and artificial examples, making it inaccessible to anyone without a strong mathematical background. Now, though, Cameron Davidson-Pilon introduces Bayesian inference from a computational perspective, bridging theory to practice-freeing you to get results using computing power. Bayesian Methods for Hackers illuminates Bayesian inference through probabilistic programming with the powerful PyMC language and the closely related Python tools NumPy, SciPy, and Matplotlib. Using this approach, you can reach effective solutions in small increments, without extensive mathematical intervention. Davidson-Pilon begins by introducing the concepts underlying Bayesian inference, comparing it with other techniques and guiding you through building and training your first Bayesian model. Next, he introduces PyMC through a series of detailed examples and intuitive explanations that have been refined after extensive user feedback. You'll learn how to use the Markov Chain Monte Carlo algorithm, choose appropriate sample sizes and priors, work with loss functions, and apply Bayesian inference in domains ranging from finance to marketing. Once you've mastered these techniques, you'll constantly turn to this guide for the working PyMC code you need to jumpstart future projects. Coverage includes - Learning the Bayesian "state of mind" and its practical implications - Understanding how computers perform Bayesian inference - Using the PyMC Python library to program Bayesian analyses - Building and debugging models with PyMC - Testing your model's "goodness of fit" - Opening the "black box" of the Markov Chain Monte Carlo algorithm to see how and why it works - Leveraging the power of the "Law of Large Numbers" - Mastering key concepts, such as clustering, convergence, autocorrelation, and thinning - Using loss functions to measure an estimate's weaknesses based on your goals and desired outcomes - Selecting appropriate priors and understanding how their influence changes with dataset size - Overcoming the "exploration versus exploitation" dilemma: deciding when "pretty good" is good enough - Using Bayesian inference to improve A/B testing - Solving data science problems when only small amounts of data are available Cameron Davidson-Pilon has worked in many areas of applied mathematics, from the evolutionary dynamics of genes and diseases to stochastic modeling of financial prices. His contributions to the open source community include lifelines, an implementation of survival analysis in Python. Educated at the University of Waterloo and at the Independent University of Moscow, he currently works with the online commerce leader Shopify.

    This book picks you up at the very beginning and guides you through the foundations of algebra using lots of examples and no-nonsense explanations. Each chapter contains well-chosen exercises as well as all the solutions. No prior knowledge is required. Topics include: Exponents, Brackets, Linear Equations and Quadratic Equations. For a more detailed table of contents, use the "Look Inside" feature. From the author of "Great Formulas Explained" and "Physics! In Quantities and Examples".

    Understand the essentials of stock investing, how to get started, and how to pick winners.

    This book covers relevant geometric principles and how to represent objects algebraically so they can be computed and applied. Recent major developments in the theory and practice of scene reconstruction are described in detail in a unified framework. Richard Hartley and Andrew Zisserman provide comprehensive background material and explain how to apply the methods and implement the algorithms. First Edition HB (2000): 0-521-62304-9

    With sixteen pages of photographs, and vivid vignettes of scientists and their inventions, Crump guides readers through early attempts to measure time and space—from astronomical charts and calendars to Arabic numerals and algebraic notation—before he examines the birth of an essentially modern technology in the 1600s. With Galileo's telescopic exploration of the skies at the beginning of the seventeenth century and Newton's experiments with the prism and light at its end, the optical instruments fundamental to all scientific research had been invented. Crump then proceeds to electromagnets, cathode tubes, thermometers, vacuum pumps, X rays, accelerators, semiconductors, microprocessors, and instruments currently being designed to operate in subzero temperatures. Here, then, in an accessible, succinctly narrated volume, is the enduring human quest for knowledge through technology. Here, too, is the proof that what is knowable is, and has always been, far more compelling than what is known. "[Crump] provides lively summaries of the progress in different fields, and succeeds in breathing new life into familiar stories."—The Economist "Fascinating reading."—Publishers Weekly

    From the Space Shuttle training toilet to a crash test of NASA’s new space capsule, Mary Roach takes us on the surreally entertaining trip into the science of life in space and space on Earth.

    No other telescope combines instant name recognition with the production of consistently spectacular images. Yet few people outside of the astronomy community realize that Hubble is now at the apex of its imaging capabilities. A collection of stunningly detailed pictures, made possible by the new Wide Field Camera 3, has yet to be incorporated into a popular-level book. Until now. Hubble's Universe will be the premier venue for the Hubble Telescope's most recent visual splendors. Bestselling astronomy writer Terence Dickinson showcases extraordinary late-breaking pictures, many of which have yet to receive wide distribution as news stories or in publications outside scientific papers, and presents a breathtaking portfolio drawn from an archive of over 500,000 existing Hubble images.The accompanying text balances accuracy with accessibility, Dickinson's hallmark. And thanks to the author's familiarity with Hubble's history and discoveries and his access to top Hubble scientists for insight and accuracy, the text includes facts and tidbits not found in any other book. Combined with hundreds of brilliant images, the clear, succinct and illuminating narrative brings to life the fascinating forces at work in the universe.

    In the four main sections of the book, Stein tells the stories of the mathematical thinkers who discerned some of the most fundamental aspects of our universe. From their successes and failures, delusions, and even duels, the trajectories of their innovations—and their impact on society—are traced in this fascinating narrative. Quantum mechanics, space-time, chaos theory and the workings of complex systems, and the impossibility of a "perfect" democracy are all here. Stein's book is both mind-bending and practical, as he explains the best way for a salesman to plan a trip, examines why any thought you could have is imbedded in the number π , and—perhaps most importantly—answers one of the modern world's toughest questions: why the garage can never get your car repaired on time.Friendly, entertaining, and fun, How Math Explains the World is the first book by one of California's most popular math teachers, a veteran of both "math for poets" and Princeton's Institute for Advanced Studies. And it's perfect for any reader wanting to know how math makes both science and the world tick.

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