These vignettes serve as springboards to many telling perspectives: simple arithmetic puts life-long habits in a dubious new light; higher dimensional geometry helps us see that we're all rather peculiar; nonlinear dynamics explains the narcissism of small differences cascading into very different siblings; logarithms and exponentials yield insight on why we tend to become bored and jaded as we age; and there are tricks and jokes, probability and coincidences, and much more.For fans of Paulos or newcomers to his work, this witty commentary on his life--and yours--is fascinating reading.From the Trade Paperback edition.

     This book is perfect for history lovers. Author James Weber did the research and compiled this huge list of events that changed the course of history forever. Some of them include: - The first civilization in Mesopotamia in 3,000 B.C. - The Norman Invasion of England in 1066 - The invention of the printing press by Johannes Guttenberg around 1450 - The French Revolution in 1789 - The first motorized airplane flight in 1903 - The Moonlanding in 1969 and many many more The book includes pictures and explanations to every event, making this the perfect resource for students and anyone wanting to broaden their knowledge in histoy. Download your copy now! Tags: history, world history, history books, history of the world, human history, world history textbook, history books for kids, earth history, geographic history, earth history kindle, human history, history books for kids age 9 12, history of the world part 1, a little history of the world, history books for kids age 7-9, history books for young readers, history books for children, history books for kindle,

    There are equally many advanced textbooks which delve into the far reaches of statistical theory, while bypassing practical applications. But between these two approaches is an unfilled gap, in which theory and practice merge at an intermediate level. Professor M. G. Bulmer's Principles of Statistics, originally published in 1965, was created to fill that need. The new, corrected Dover edition of Principles of Statistics makes this invaluable mid-level text available once again for the classroom or for self-study.Principles of Statistics was created primarily for the student of natural sciences, the social scientist, the undergraduate mathematics student, or anyone familiar with the basics of mathematical language. It assumes no previous knowledge of statistics or probability; nor is extensive mathematical knowledge necessary beyond a familiarity with the fundamentals of differential and integral calculus. (The calculus is used primarily for ease of notation; skill in the techniques of integration is not necessary in order to understand the text.)Professor Bulmer devotes the first chapters to a concise, admirably clear description of basic terminology and fundamental statistical theory: abstract concepts of probability and their applications in dice games, Mendelian heredity, etc.; definitions and examples of discrete and continuous random variables; multivariate distributions and the descriptive tools used to delineate them; expected values; etc. The book then moves quickly to more advanced levels, as Professor Bulmer describes important distributions (binomial, Poisson, exponential, normal, etc.), tests of significance, statistical inference, point estimation, regression, and correlation. Dozens of exercises and problems appear at the end of various chapters, with answers provided at the back of the book. Also included are a number of statistical tables and selected references.

    Its big-picture, calculus-based approach makes it an especially authoriatative reference for engineering and science majors. Now thoroughly update, this second edition includes vital new coverage of order statistics, best critical regions, likelihood ratio tests, and other key topics.

    Written by two of the best-known names in categorical logic, Conceptual Mathematics is the first book to apply categories to the most elementary mathematics. It thus serves two purposes: first, to provide a key to mathematics for the general reader or beginning student; and second, to furnish an easy introduction to categories for computer scientists, logicians, physicists, and linguists who want to gain some familiarity with the categorical method without initially committing themselves to extended study.

    This book is designed to give the reader insight into the power and beauty that accrues from a rich interplay between different areas of mathematics. The book carefully develops the theory of different algebraic structures, beginning from basic definitions to some in-depth results, using numerous examples and exercises to aid the reader's understanding. In this way, readers gain an appreciation for how mathematical structures and their interplay lead to powerful results and insights in a number of different settings. * The emphasis throughout has been to motivate the introduction and development of important algebraic concepts using as many examples as possible.

    The book includes charts with the recipes, instructions on keeping diets simple and balanced, guidelines on preparation, suggestions for finding ingredients, and how much to feed a dog by body weight. There are recipes for healthy adult dogs, as well as guidelines for puppies, senior dogs, and dogs with health conditions including pancreatitis, renal problems, gastric issues, allergies, heart disease, liver disease, and cancer.Tracing the history of feeding dogs, the author shows when commercial dog food rose and took hold of the market. She discusses canine nutritional needs and provides research on how home-prepared foods can meet pets' needs better than commercial, processed dog food. Written with thorough information for the seasoned raw feeder, this guide can also be easily followed by any newcomer to home-feeding.This revised edition includes new information on special care and feeding of pregnant, newborn, performance, and toy breed dogs as well as senior dog considerations and the safety of the raw food diet for dogs.From the Trade Paperback edition.

    The book's careful account is a contemporary balance between theory, application, and historical development, providing it's readers with an insight into how mathematics progresses and is in turn influenced by the natural world.

    In his first two books, Dr. Dale Bredesen outlined the revolutionary treatments that are changing what had previously seemed like the inevitable outcome of cognitive decline and dementia. And in these moving narratives, you can hear directly from the first survivors of Alzheimer's themselves--their own amazing stories of hope told in their own words. These first person accounts honestly detail the fear, struggle, and ultimate victory of each patient's journey. They vividly describe what it is like to have Alzheimer's. They also drill down on how each of these patients made the program work for them--the challenges, the workarounds, the encouraging results that are so motivating. Dr. Bredesen includes commentary following each story to help point readers to the tips and tricks that might help them as well.Dr. Bredesen's patients have not just survived; they have thrived to rediscover fulfilling lives, rewarding relationships, and meaningful work. This book will give unprecedented hope to patients and their families.

     From Dr. Frankenstein to Dr. Jekyll, the image of the mad scientist surrounded by glass vials, copper coils, and electrical apparatus remains a popular fixture. In films and fiction, he's comically misguided, tragically misunderstood, or pathologically evil. But the origins of this stereotype can be found in the sometimes-eccentric real life men and women who challenged our view of the world and broke new scientific frontiers. They Called Me Mad recounts the amazing true stories of such historical luminaries as Archimedes, the calculator of pi and creator of the world's first death ray; Isaac Newton, the world's first great scientist and the last great alchemist; Nikola Tesla, who built the precursors of robots, fluorescent lighting, and particle beam weapons before the turn of the twentieth century-and more.

    Without machine learning, fraud detection, web search results, real-time ads on web pages, credit scoring, automation, and email spam filtering wouldn't be possible, and this is only showcasing just a few of its capabilities. Written by two data science experts, Machine Learning For Dummies offers a much-needed entry point for anyone looking to use machine learning to accomplish practical tasks.Covering the entry-level topics needed to get you familiar with the basic concepts of machine learning, this guide quickly helps you make sense of the programming languages and tools you need to turn machine learning-based tasks into a reality. Whether you're maddened by the math behind machine learning, apprehensive about AI, perplexed by preprocessing data--or anything in between--this guide makes it easier to understand and implement machine learning seamlessly.Grasp how day-to-day activities are powered by machine learning Learn to 'speak' certain languages, such as Python and R, to teach machines to perform pattern-oriented tasks and data analysis Learn to code in R using R Studio Find out how to code in Python using Anaconda Dive into this complete beginner's guide so you are armed with all you need to know about machine learning!

    Estranged from Ada’s father, who was infamously “mad, bad, and dangerous to know,” Ada’s mathematician mother is determined to save her only child from her perilous Byron heritage. Banishing fairy tales and make-believe from the nursery, Ada’s mother provides her daughter with a rigorous education grounded in mathematics and science. Any troubling spark of imagination—or worse yet, passion or poetry—is promptly extinguished. Or so her mother believes.When Ada is introduced into London society as a highly eligible young heiress, she at last discovers the intellectual and social circles she has craved all her life. Little does she realize that her delightful new friendship with inventor Charles Babbage—brilliant, charming, and occasionally curmudgeonly—will shape her destiny. Intrigued by the prototype of his first calculating machine, the Difference Engine, and enthralled by the plans for his even more advanced Analytical Engine, Ada resolves to help Babbage realize his extraordinary vision, unique in her understanding of how his invention could transform the world. All the while, she passionately studies mathematics—ignoring skeptics who consider it an unusual, even unhealthy pursuit for a woman—falls in love, discovers the shocking secrets behind her parents’ estrangement, and comes to terms with the unquenchable fire of her imagination.

    But in spirit, the title is apt, as the book does cover a much broader range of topics than a typical introductory book on mathematical statistics. This book is for people who want to learn probability and statistics quickly. It is suitable for graduate or advanced undergraduate students in computer science, mathematics, statistics, and related disciplines. The book includes modern topics like nonparametric curve estimation, bootstrapping, and clas- sification, topics that are usually relegated to follow-up courses. The reader is presumed to know calculus and a little linear algebra. No previous knowledge of probability and statistics is required. Statistics, data mining, and machine learning are all concerned with collecting and analyzing data. For some time, statistics research was con- ducted in statistics departments while data mining and machine learning re- search was conducted in computer science departments. Statisticians thought that computer scientists were reinventing the wheel. Computer scientists thought that statistical theory didn't apply to their problems. Things are changing. Statisticians now recognize that computer scientists are making novel contributions while computer scientists now recognize the generality of statistical theory and methodology. Clever data mining algo- rithms are more scalable than statisticians ever thought possible. Formal sta- tistical theory is more pervasive than computer scientists had realized.

    Of course, it’s not all cooking; we’ll also run the New York and Chicago marathons, pay visits to Cinderella and Lewis Carroll, and even get to the bottom of a tomato’s identity as a vegetable. This is not the math of our high school classes: mathematics, Cheng shows us, is less about numbers and formulas and more about how we know, believe, and understand anything, including whether our brother took too much cake.At the heart of How to Bake Pi is Cheng’s work on category theory—a cutting-edge “mathematics of mathematics.” Cheng combines her theory work with her enthusiasm for cooking both to shed new light on the fundamentals of mathematics and to give readers a tour of a vast territory no popular book on math has explored before. Lively, funny, and clear, How to Bake Pi will dazzle the initiated while amusing and enlightening even the most hardened math-phobe.

    'Big data', 'data science', and 'machine learning' have become familiar terms in the news, as statistical methods are brought to bear upon the enormous data sets of modern science and commerce. How did we get here? And where are we going? This book takes us on an exhilarating journey through the revolution in data analysis following the introduction of electronic computation in the 1950s. Beginning with classical inferential theories - Bayesian, frequentist, Fisherian - individual chapters take up a series of influential topics: survival analysis, logistic regression, empirical Bayes, the jackknife and bootstrap, random forests, neural networks, Markov chain Monte Carlo, inference after model selection, and dozens more. The distinctly modern approach integrates methodology and algorithms with statistical inference. The book ends with speculation on the future direction of statistics and data science.