It shows how causality has grown from a nebulous concept into a mathematical theory with significant applications in the fields of statistics, artificial intelligence, philosophy, cognitive science, and the health and social sciences. Pearl presents a unified account of the probabilistic, manipulative, counterfactual and structural approaches to causation, and devises simple mathematical tools for analyzing the relationships between causal connections, statistical associations, actions and observations. The book will open the way for including causal analysis in the standard curriculum of statistics, artifical intelligence, business, epidemiology, social science and economics. Students in these areas will find natural models, simple identification procedures, and precise mathematical definitions of causal concepts that traditional texts have tended to evade or make unduly complicated. This book will be of interest to professionals and students in a wide variety of fields. Anyone who wishes to elucidate meaningful relationships from data, predict effects of actions and policies, assess explanations of reported events, or form theories of causal understanding and causal speech will find this book stimulating and invaluable. Professor of Computer Science at the UCLA, Judea Pearl is the winner of the 2008 Benjamin Franklin Award in Computers and Cognitive Science.

    The information presented includes: definitions, names, historical background, coordinates, classifications, physical descriptions, maps, charts, sketches, and observing guides. All told in an engaging manner.The series became an instant success with amateur astronomers, and remained so for decades. While it is now dated, it is still a popular source of information.Volume One lists the constellations from Andromeda to Cetus.

    Polya, How to Solve It will show anyone in any field how to think straight. In lucid and appealing prose, Polya reveals how the mathematical method of demonstrating a proof or finding an unknown can be of help in attacking any problem that can be reasoned out--from building a bridge to winning a game of anagrams. Generations of readers have relished Polya's deft--indeed, brilliant--instructions on stripping away irrelevancies and going straight to the heart of the problem.

    This book will offer students a broad outline of essential mathematics and will help to fill in the gaps in their knowledge. The author explains the basic points and a few key results of all the most important undergraduate topics in mathematics, emphasizing the intuitions behind the subject. The topics include linear algebra, vector calculus, differential and analytical geometry, real analysis, point-set topology, probability, complex analysis, set theory, algorithms, and more. An annotated bibliography offers a guide to further reading and to more rigorous foundations.

    It has been widely praised by a generation of users for its solid and effective pedagogy that addresses the needs of a broad range of teaching and learning styles and environments. Each title is just one component in a comprehensive calculus course program that carefully integrates and coordinates print, media, and technology products for successful teaching and learning.

    This book contains student-friendly Study Tips, Clinical View boxes, and progressive question sets to motivate students to internalize and apply what they've learned.

    The applications and computations in operations research are emphasized. Significantly revised, this text streamlines the coverage of the theory, applications, and computations of operations research. Numerical examples are effectively used to explain complex mathematical concepts. A separate chapter of fully analyzed applications aptly demonstrates the diverse use of OR. The popular commercial and tutorial software AMPL, Excel, Excel Solver, and Tora are used throughout the book to solve practical problems and to test theoretical concepts. New materials include Markov chains, TSP heuristics, new LP models, and a totally new simplex-based approach to LP sensitivity analysis.

    Although it presents the main ideas of quantum theory essentially in nonmathematical terms, it follows these with a broad range of specific applications that are worked out in considerable mathematical detail. Addressed primarily to advanced undergraduate students, the text begins with a study of the physical formulation of the quantum theory, from its origin and early development through an analysis of wave vs. particle properties of matter. In Part II, Professor Bohm addresses the mathematical formulation of the quantum theory, examining wave functions, operators, Schrödinger's equation, fluctuations, correlations, and eigenfunctions.Part III takes up applications to simple systems and further extensions of quantum theory formulation, including matrix formulation and spin and angular momentum. Parts IV and V explore the methods of approximate solution of Schrödinger's equation and the theory of scattering. In Part VI, the process of measurement is examined along with the relationship between quantum and classical concepts.Throughout the text, Professor Bohm places strong emphasis on showing how the quantum theory can be developed in a natural way, starting from the previously existing classical theory and going step by step through the experimental facts and theoretical lines of reasoning which led to replacement of the classical theory by the quantum theory.

    We are living in an age where data comes in abundance, and thanks to the self-learning algorithms from the field of machine learning, we can turn this data into knowledge. Automated speech recognition on our smart phones, web search engines, e-mail spam filters, the recommendation systems of our favorite movie streaming services – machine learning makes it all possible.Thanks to the many powerful open-source libraries that have been developed in recent years, machine learning is now right at our fingertips. Python provides the perfect environment to build machine learning systems productively.This book will teach you the fundamentals of machine learning and how to utilize these in real-world applications using Python. Step-by-step, you will expand your skill set with the best practices for transforming raw data into useful information, developing learning algorithms efficiently, and evaluating results.You will discover the different problem categories that machine learning can solve and explore how to classify objects, predict continuous outcomes with regression analysis, and find hidden structures in data via clustering. You will build your own machine learning system for sentiment analysis and finally, learn how to embed your model into a web app to share with the world

    Updated with the latest advances in the field, Jerry FitzGerald and Alan Dennis' 10th Edition of Business Data Communications and Networking continues to provide the fundamental concepts and cutting-edge coverage applications that students need to succeed in this fast-moving field.Authors FitzGerald and Dennis have developed a foundation and balanced presentation from which new technologies and applications can be easily understood, evaluated, and compared.

    By emphasizing the relationship between structure and function, the authors provide a framework for understanding mechanisms and reactions. Stressing the importance of synthetic strategies and biological and industrial applications, the text introduces students to real chemistry as it is actually practised. This fourth edition offers significant updates in coverage and learning tools and enhanced media support at the book's companion website.

    Author Manuel Velasquez combines clear prose and primary source readings to take you on a meaningful exploration of a range of philosophical topics, such as human nature, feminist theory, diversity, and aesthetics. Plus, the text's carefully crafted built-in learning aids will help you succeed in your course.

    Its organization and thoroughness are unsurpassed, putting it above similar review books. Students who thoroughly read this book should have no trouble successfully completing their psychiatry clerkship and passing the shelf exam. As course director for the core psychiatry clerkship at my institution, I will recommend this book to students."--Doody's Review Service"First Aid for the Psychiatry Clerkship" gives you the core information needed to impress on the wards and pass the psychiatry clerkship exam. Written by students who know what it takes to succeed, and based on the national guidelines for the psychiatry clerkship, the book is filled with mnemonics, ward and exam tips, tables, clinical images, algorithms, and newly added mini-cases.Features Completely revised based on the psychiatry clerkship's core competencies Written by medical students who passed and reviewed by faculty for accuracy NEW integrated mini-cases illustrate classic patient presentations and/or commonly tested scenarios NEW illustrations and management algorithms Updated throughout with enhanced sections on medications, depression/anxiety, and child psychiatry Helps students hone in on the most important concepts for the clerkship and the examThe content you need to ace the clerkship: Section I: How to Succeed in the Psychiatry Clerkship Section II: High-Yield Facts; Examination and Diagnosis; Psychotic Disorders; Mood Disorders; Anxiety and Adjustment Disorders; Personality Disorders; Substance-Related Disorders; Cognitive Disorders; Geriatric Disorders; Psychiatric Disorders in Children; Dissociative Disorders; Somataform and Factitious Disorders; Impulse Control Disorders; Eating Disordes; Disorders; Sleep Disorders; Sexual Disorders; Psychtherapies; Psychopharmacology; Legal Issues; Section III: Awards and Opportunities.

    The book is non-theoretical, explaining concepts intuitively and teaching problem solving through worked examples and step-by-step instructions. This edition places more emphasis on conceptual understanding and understanding results. This edition also features increased emphasis on Excel, MINITAB, and the TI-83 Plus and TI 84-Plus graphing calculators, computing technologies commonly used in such courses.