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.

    Eric C. Westman join forces again to explain the powerful therapeutic effects of a ketogenic diet—one that combines a customized carbohydrate restriction, moderation of protein intake, and real food-based fats—which is emerging in the scientific literature as a means for improving a wide range of diseases, from Type 2 diabetes to Alzheimer’s and more. Simply eating a low-carb diet alone isn’t enough, and Moore and Westman tell you why.Have you looked at a low-carb diet simply as a means to lose weight? What if you learned that combining a low-carb nutritional approach with a high fat intake produces a powerful therapeutic effect on a wide variety of health conditions that most people think requires medication to control? That’s what Keto Clarity is all about. Jimmy Moore, the world’s leading low-carb diet blogger and podcaster, has reunited with his Cholesterol Clarity coauthor Dr. Eric C. Westman, a practicing internist and low-carb diet researcher, to bring you the crystal-clear information you need to understand what a ketogenic diet is all about and why it may be the missing element in your pursuit of optimal health. This book includes exclusive interviews from twenty of the world’s foremost authorities from various fields bringing their depth of expertise and experience using this nutritional approach. Moore and Westman clearly explain why ketosis is normal, how this nutritional approach is being used therapeutically by many medical professionals, a step-by-step guide to help you produce more ketones and track your progress, real life success stories of people using a ketogenic diet, and more. The solid evidence for nutritional ketosis in dealing with many of the chronic health problems of our day is presented, including: epilepsy, Type 2 diabetes, obesity, cardiovascular disease, metabolic syndrome, polycystic ovarian syndrome (PCOS), irritable bowel syndrome (IBS), heartburn (GERD), nonalcoholic fatty liver disease (NAFLD). The good evidence for ketogenic diets is also shared in dealing with Alzheimer’s Disease (AD), Parkinson’s Disease, dementia, mental illness, schizophrenia, bipolar, depression, narcolepsy, and sleep disorders. Plus, you’ll get the details on the emerging science that is showing great promise in treating cancer, autism, migraines, chronic pain, brain injury, stroke, kidney disease and so much more. Keto Clarity is your definitive guide to the benefits of a low-carb, high-fat diet. Full details on Jimmy Moore’s yearlong n=1 scientific experiment of nutritional ketosis, in which he used sophisticated blood testing technology to track and monitor his production of ketones and blood sugar to achieve rather remarkable effects on his weight and health, is also presented as well as food shopping lists, 25+ low-carb, high-fat recipes, and a 21-day meal plan to get you going on your ketogenic lifestyle change. Keto Clarity gives you a whole new perspective on the work that the late, great Dr. Robert C. Atkins started in earnest with his promotion of the low-carb approach beginning in the 1960s. That revolution continues boldly in this book designed to shift your paradigm on diet and health forever!

    Its world-class authors provide guidance on all aspects of Bayesian data analysis and include examples of real statistical analyses, based on their own research, that demonstrate how to solve complicated problems. Changes in the new edition include:Stronger focus on MCMC Revision of the computational advice in Part III New chapters on nonlinear models and decision analysis Several additional applied examples from the authors' recent research Additional chapters on current models for Bayesian data analysis such as nonlinear models, generalized linear mixed models, and more Reorganization of chapters 6 and 7 on model checking and data collectionBayesian computation is currently at a stage where there are many reasonable ways to compute any given posterior distribution. However, the best approach is not always clear ahead of time. Reflecting this, the new edition offers a more pluralistic presentation, giving advice on performing computations from many perspectives while making clear the importance of being aware that there are different ways to implement any given iterative simulation computation. The new approach, additional examples, and updated information make Bayesian Data Analysis an excellent introductory text and a reference that working scientists will use throughout their professional life.

    Plus, it helps you identify areas of weakness so you can focus your study time. Sample problems and step-by-step examples with explanations in the math and physics sections show you how to work through each problem so you understand the steps it takes to complete the equation. Practice tests with answer keys for each topic - located in the appendices for quick access - help you assess your understanding of each topic and familiarize you with the types of questions you're likely to encounter on the actual exam. HESI Hints boxes offer valuable test-taking tips, as well as rationales, suggestions, examples, and reminders for specific topics.End-of-chapter review questions help you gauge your understanding of chapter content.A full-color layout and more illustrations in the life science chapters visually reinforce key concepts for better understanding.Expanded and updated content in each chapter ensures you're studying the most current content.Basic algebra review in the math section offers additional review and practice.Color-coded chapters help you quickly find specific topic sections.Helpful organizational features in each chapter include an introduction, key terms, chapter outline, and a bulleted chapter summary to help you focus your study.A glossary at the end of the text offers quick access to key terms and their definitions.

    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.

     into their ideal job   Each year tens of thousands of students will, after years of hard work and enormous amounts of money, earn their Ph.D. And each year only a small percentage of them will land a job that justifies and rewards their investment. For every comfortably tenured professor or well-paid former academic, there are countless underpaid and overworked adjuncts, and many more who simply give up in frustration.   Those who do make it share an important asset that separates them from the pack: they have a plan. They understand exactly what they need to do to set themselves up for success.  They know what really moves the needle in academic job searches, how to avoid the all-too-common mistakes that sink so many of their peers, and how to decide when to point their Ph.D. toward other, non-academic options.   Karen Kelsky has made it her mission to help readers join the select few who get the most out of their Ph.D. As a former tenured professor and department head who oversaw numerous academic job searches, she knows from experience exactly what gets an academic applicant a job. And as the creator of the popular and widely respected advice site The Professor is In, she has helped countless Ph.D.’s turn themselves into stronger applicants and land their dream careers.   Now, for the first time ever, Karen has poured all her best advice into a single handy guide that addresses the most important issues facing any Ph.D., including:   -When, where, and what to publish -Writing a foolproof grant application -Cultivating references and crafting the perfect CV -Acing the job talk and campus interview -Avoiding the adjunct trap -Making the leap to nonacademic work, when the time is right  The Professor Is In addresses all of these issues, and many more.

    You can use these ideas and methods as-is, or better yet, tweak them and create your own enticing educational meals. The message the authors share is that, with imagination and preparation, every teacher can be a Classroom Chef.

    The unique on-line grading services instantly grades solutions to hundred of computer exercises. It is specially devised to be used by philosophy instructors in a way that is useful to undergraduates of philosophy, computer science, mathematics, and linguistics.The book is a completely rewritten and much improved version of The Language of First-order Logic. Introductory material is presented in a more systematic and accessible fashion. Advanced chapters include proofs of soundness and completeness for propositional and predicate logic, as well as an accessible sketch of Godel's first incompleteness theorem. The book is appropriate for a wide range of courses, from first logic courses for undergraduates (philosophy, mathematics, and computer science) to a first graduate logic course.The package includes four pieces of software:Tarski's World 5.0, a new version of the popular program that teaches the basic first-order language and its semantics; Fitch, a natural deduction proof environment for giving and checking first-order proofs;Boole, a program that facilitates the construction and checking of truth tables and related notions (tautology, tautological consequence, etc.);Submit, a program that allows students to submit exercises done with the above programs to the Grade Grinder, the automatic grading service.Grade reports are returned to the student and, if requested, to the student's instructor, eliminating the need for tedious checking of homework. All programs are available for Windows, Macintosh and Linux systems.Instructors do not need to use the programs themselves in order to be able to take advantage of their pedagogical value. More about the software can be found at lpl.stanford.edu.The price of a new text/software package includes one Registration ID, which must be used each time work is submitted to the grading service. Once activated, the Registration ID is not transferable.

    The gold standard for attaining security is cryptography because it provides the most reliable tools for storing or transmitting digital information. Written by Niels Ferguson, lead cryptographer for Counterpane, Bruce Schneier's security company, and Bruce Schneier himself, this is the much anticipated follow-up book to Schneier's seminal encyclopedic reference, Applied Cryptography, Second Edition (0-471-11709-9), which has sold more than 150,000 copies. Niels Ferguson (Amsterdam, Netherlands) is a cryptographic engineer and consultant at Counterpane Internet Security. He has extensive experience in the creation and design of security algorithms, protocols, and multinational security infrastructures. Previously, Ferguson was a cryptographer for DigiCash and CWI. At CWI he developed the first generation of off-line payment protocols. He has published numerous scientific papers. Bruce Schneier (Minneapolis, MN) is Founder and Chief Technical Officer at Counterpane Internet Security, a managed-security monitoring company. He is also the author of Secrets and Lies: Digital Security in a Networked World (0-471-25311-1).

    Completely rewritten to reflect the major changes Microsoft has made to Office, this reference includes information on creating and editing worksheets, formatting cells, entering formulas, creating and editing charts, inserting graphs, designing database forms, adding database records, using seek-and-find options, adding hyperlinks to worksheets, and more.

    Courses and books on basic statistics rarely cover the topic from a data science perspective. This practical guide explains how to apply various statistical methods to data science, tells you how to avoid their misuse, and gives you advice on what's important and what's not.Many data science resources incorporate statistical methods but lack a deeper statistical perspective. If you're familiar with the R programming language, and have some exposure to statistics, this quick reference bridges the gap in an accessible, readable format.With this book, you'll learn:Why exploratory data analysis is a key preliminary step in data scienceHow random sampling can reduce bias and yield a higher quality dataset, even with big dataHow the principles of experimental design yield definitive answers to questionsHow to use regression to estimate outcomes and detect anomaliesKey classification techniques for predicting which categories a record belongs toStatistical machine learning methods that "learn" from dataUnsupervised learning methods for extracting meaning from unlabeled data

    This supplement will cater to the requirements of students by covering all important topics of Laplace transformation, Matrices, Numerical Methods. Further enhanced is its usability by inclusion of chapter end questions in sync with student needs. Table of contents: 1. Basic Concepts 2. An Introduction to Modeling and Qualitative Methods 3. Classification of First-Order Differential Equations 4. Separable First-Order Differential Equations 5. Exact First-order Differential Equations 6. Linear First-Order Differential Equations 7. Applications of First-Order Differential Equations 8. Linear Differential Equations: Theory of Solutions 9. Second-Order Linear Homogeneous Differential Equations with Constant Coefficients 10. nth-Order Linear Homogeneous Differential Equations with Constant Coefficients 11. The Method of Undetermined Coefficients 12. Variation of Parameters 13. Initial-Value Problems for Linear Differential Equations 14. Applications of Second-Order Linear Differential Equations 15. Matrices 16. eAt 17. Reduction of Linear Differential Equations to a System of First-Order Equations 18. Existence and Uniqueness of Solutions 19. Graphical and Numerical Methods for Solving First-Order Differential Equations 20. Further Numerical Methods for Solving First-Order Differential Equations 21. Numerical Methods for Solving Second-Order Differential Equations Via Systems 22. The Laplace Transform 23. Inverse Laplace Transforms 24. Convolutions and the Unit Step Function 25. Solutions of Linear Differential Equations with Constant Coefficients by Laplace Transforms 26. Solutions of Linear?Systems by Laplace Transforms 27. Solutions of Linear Differential Equations with Constant Coefficients by Matrix Methods 28. Power Series Solutions of Linear Differential Equations with Variable Coefficients 29. Special Functions 30. Series Solutions N

    With the stroke of a pen the Jesuit fathers banned the doctrine of infinitesimals, announcing that it could never be taught or even mentioned. The concept was deemed dangerous and subversive, a threat to the belief that the world was an orderly place, governed by a strict and unchanging set of rules. If infinitesimals were ever accepted, the Jesuits feared, the entire world would be plunged into chaos.In Infinitesimal, the award-winning historian Amir Alexander exposes the deep-seated reasons behind the rulings of the Jesuits and shows how the doctrine persisted, becoming the foundation of calculus and much of modern mathematics and technology. Indeed, not everyone agreed with the Jesuits. Philosophers, scientists, and mathematicians across Europe embraced infinitesimals as the key to scientific progress, freedom of thought, and a more tolerant society. As Alexander reveals, it wasn't long before the two camps set off on a war that pitted Europe's forces of hierarchy and order against those of pluralism and change.The story takes us from the bloody battlefields of Europe's religious wars and the English Civil War and into the lives of the greatest mathematicians and philosophers of the day, including Galileo and Isaac Newton, Cardinal Bellarmine and Thomas Hobbes, and Christopher Clavius and John Wallis. In Italy, the defeat of the infinitely small signaled an end to that land's reign as the cultural heart of Europe, and in England, the triumph of infinitesimals helped launch the island nation on a course that would make it the world's first modern state.From the imperial cities of Germany to the green hills of Surrey, from the papal palace in Rome to the halls of the Royal Society of London, Alexander demonstrates how a disagreement over a mathematical concept became a contest over the heavens and the earth. The legitimacy of popes and kings, as well as our beliefs in human liberty and progressive science, were at stake-the soul of the modern world hinged on the infinitesimal.

    Remarkable for his range of thought and his mastery of treatment, Archimedes addressed such topics as the famous problems of the ratio of the areas of a cylinder and an inscribed sphere; the measurement of a circle; the properties of conoids, spheroids, and spirals; and the quadrature of the parabola. This edition offers an informative introduction with many valuable insights into the ancient mathematician's life and thought as well as the views of his contemporaries. Modern mathematicians, physicists, science historians, and logicians will find this volume a source of timeless fascination.

    By presenting actual experiences and analyzing them as they are described, the author conveys the developmental thought processes employed and shows a style of thinking that leads to successful results is something that can be learned. Along with spectacular successes, the author also conveys how failures contributed to shaping the thought processes. Provides the reader with a style of thinking that will enhance a person's ability to function as a problem-solver of complex technical issues. Consists of a collection of stories about the author's participation in significant discoveries, relating how those discoveries came about and, most importantly, provides analysis about the thought processes and reasoning that took place as the author and his associates progressed through engineering problems.