Kuby Immunology


Judy A. Owen - 2012
    The new edition is thoroughly updated, including most notably a new chapter on innate immunity, a capstone chapter on immune responses in time and space, and many new focus boxes drawing attention to exciting clinical, evolutionary, or experimental connections that help bring the material to life.See what's in the LaunchPad

Organizational Behavior: Emerging Realities for the Workplace Revolution


Steven L. McShane - 1999
    Acclaimed for its readability and presentation of current knowledge, this textbook's philosophy is that OB knowledge is for everyone, not just traditional managers. The new reality is that everyone - sales representatives, production employees, physicians - needs OB knowledge to successfully work in and around organizations. Organizational Behavior is unparalleled in its ability to engage students by bringing cutting edge OB concepts closer to reality through the 'theory-practice link' approach. McShane and Von Glinow help readers connect OB theories to emerging workplace realities through hundreds of fascinating real-life stories from across the United States and around the world. be the source of the hottest topics, such as: employee engagement, resilience, four-drive theory, blogs and wikis, psychological harassment, learning orientation, Schwartz's values model, separating socioemotional from constructive conflict, and much, much, more.

The Elements of Data Analytic Style


Jeffrey Leek - 2015
    This book is focused on the details of data analysis that sometimes fall through the cracks in traditional statistics classes and textbooks. It is based in part on the authors blog posts, lecture materials, and tutorials. The author is one of the co-developers of the Johns Hopkins Specialization in Data Science the largest data science program in the world that has enrolled more than 1.76 million people. The book is useful as a companion to introductory courses in data science or data analysis. It is also a useful reference tool for people tasked with reading and critiquing data analyses. It is based on the authors popular open-source guides available through his Github account (https://github.com/jtleek). The paper is also available through Leanpub (https://leanpub.com/datastyle), if the book is purchased on that platform you are entitled to lifetime free updates.

Advances in Financial Machine Learning


Marcos López de Prado - 2018
    Today, ML algorithms accomplish tasks that - until recently - only expert humans could perform. And finance is ripe for disruptive innovations that will transform how the following generations understand money and invest.In the book, readers will learn how to:Structure big data in a way that is amenable to ML algorithms Conduct research with ML algorithms on big data Use supercomputing methods and back test their discoveries while avoiding false positives Advances in Financial Machine Learning addresses real life problems faced by practitioners every day, and explains scientifically sound solutions using math, supported by code and examples. Readers become active users who can test the proposed solutions in their individual setting.Written by a recognized expert and portfolio manager, this book will equip investment professionals with the groundbreaking tools needed to succeed in modern finance.

International Business: The Challenge of Global Competition [With Access Code]


Donald A. Ball - 1990
    Enriched with maps, photos, and the most up-to-date world data, this text boasts the collective expertise of four authors with firsthand international business experience, specializing in international management, finance, law, global strategy, and marketing - a claim no other text can make. In addition, each new copy of International Business, 12e includes access to CESIM - an interactive IB simulation developed for industry professionals. Ball, et. al. is the only textbook on the market which features access to CESIM. Only Ball, Geringer, Minor and McNett can offer a complete view of International Business as diverse as the backgrounds of business students.

Introductory Circuit Analysis


Robert L. Boylestad - 1968
    Features exceptionally clear explanations and descriptions, step-by-step examples, more than 50 practical applications, over 2000 easy-to-challenging practice problems, and comprehensive coverage of essentials. PSpice, OrCAd version 9.2 Lite Edition, Multisims 2001 version of Electronics Workbench, and MathCad software references and examples are used throughout. Computer programs (C++, BASIC and PSpice) are printed in color, as they run, at the point in the book where they are discussed. Current and Voltage. Resistance. Ohm's Law, Power, and Energy. Series Circuits. Parallel Circuits. Series-Parallel Networks. Methods of Analysis & Selected Topics. Network Theorems. Capacitors. Magnetic Circuits. Inductors. Sinusodial Alternating Waveforms. The Basic Elements and Phasors. Series and Parallel ac Circuits. Series-Parallel ac Networks. Methods of Analysis and Related Topics. Network Theorems (ac). Power (ac). Resonance. Transformers. Polyphase Systems. Decibels, Filters, and Bode Points. Pulse Waveforms and the R-C Response. Nonsinusodial Circuits. System Analysis: An Introduction. For those working in electronic technology.

Psychopharmacology: Drugs, the Brain, and Behavior


Jerrold S. Meyer - 2004
    Encompassing recent advances in molecular pharmacology and brain imaging, Drugs, The Brain and Behavior offers a unique breadth of coverage from historical accounts of drug use, through clinical and preclinical behavioural studies, to the latest research on drug effects in transgenic mouse models.

The Norton Anthology of English Literature, Vol. A: Middle Ages


M.H. Abrams - 1999
    Under the direction of Stephen Greenblatt, General Editor, the editors have reconsidered all aspects of the anthology to make it an even better teaching tool.

An Introduction To Quantum Field Theory


Michael E. Peskin - 1994
    The authors make these subjects accessible through carefully worked examples illustrating the technical aspects of the subject, and intuitive explanations of what is going on behind the mathematics. After presenting the basics of quantum electrodynamics, the authors discuss the theory of renormalization and its relation to statistical mechanics, and introduce the renormalization group. This discussion sets the stage for a discussion of the physical principles that underlie the fundamental interactions of elementary particle physics and their description by gauge field theories.

The Economics of Microfinance


Jonathan Morduch - 2005
    This comprehensive survey of microfinance seeks to bridge the gap in the existing literature on microfinance between academic economists and practitioners. Both authors have pursued the subject not only in academia but in the field; Beatriz Armendariz de Aghion founded a microfinance bank in Chiapas, Mexico, and Jonathan Morduch has done fieldwork in Bangladesh, China, and Indonesia. The authors move beyond the usual theoretical focus in the microfinance literature and draw on new developments in theories of contracts and incentives. They challenge conventional assumptions about how poor households save and build assets and how institutions can overcome market failures. The book provides an overview of microfinance by addressing a range of issues, including lessons from informal markets, savings and insurance, the role of women, the place of subsidies, impact measurement, and management incentives. and Latin America and introducing ideas about asymmetric information, principal-agent theory, and household decision making in the context of microfinance. The Economics of Microfinance can be used by students in economics, public policy, and development studies. Mathematical notation is used to clarify some arguments, but the main points can be grasped without the math. Each chapter ends with analytically challenging exercises for advanced economics students.

R for Dummies


Joris Meys - 2012
    R is packed with powerful programming capabilities, but learning to use R in the real world can be overwhelming for even the most seasoned statisticians. This easy-to-follow guide explains how to use R for data processing and statistical analysis, and then, shows you how to present your data using compelling and informative graphics. You'll gain practical experience using R in a variety of settings and delve deeper into R's feature-rich toolset.Includes tips for the initial installation of RDemonstrates how to easily perform calculations on vectors, arrays, and lists of dataShows how to effectively visualize data using R's powerful graphics packagesGives pointers on how to find, install, and use add-on packages created by the R communityProvides tips on getting additional help from R mailing lists and websitesWhether you're just starting out with statistical analysis or are a procedural programming pro, "R For Dummies" is the book you need to get the most out of R.

Prediction Machines: The Simple Economics of Artificial Intelligence


Ajay Agrawal - 2018
    But facing the sea change that AI will bring can be paralyzing. How should companies set strategies, governments design policies, and people plan their lives for a world so different from what we know? In the face of such uncertainty, many analysts either cower in fear or predict an impossibly sunny future.But in Prediction Machines, three eminent economists recast the rise of AI as a drop in the cost of prediction. With this single, masterful stroke, they lift the curtain on the AI-is-magic hype and show how basic tools from economics provide clarity about the AI revolution and a basis for action by CEOs, managers, policy makers, investors, and entrepreneurs.When AI is framed as cheap prediction, its extraordinary potential becomes clear: Prediction is at the heart of making decisions under uncertainty. Our businesses and personal lives are riddled with such decisions. Prediction tools increase productivity--operating machines, handling documents, communicating with customers. Uncertainty constrains strategy. Better prediction creates opportunities for new business structures and strategies to compete. Penetrating, fun, and always insightful and practical, Prediction Machines follows its inescapable logic to explain how to navigate the changes on the horizon. The impact of AI will be profound, but the economic framework for understanding it is surprisingly simple.

Risk Savvy: How to Make Good Decisions


Gerd Gigerenzer - 2013
    But as risk expert Gerd Gigerenzer shows, the surprising truth is that in the real world, we often get better results by using simple rules and considering less information. In Risk Savvy, Gigerenzer reveals that most of us, including doctors, lawyers, financial advisers, and elected officials, misunderstand statistics much more often than we think, leaving us not only misinformed, but vulnerable to exploitation. Yet there is hope. Anyone can learn to make better decisions for their health, finances, family, and business without needing to consult an expert or a super computer, and Gigerenzer shows us how.Risk Savvy is an insightful and easy-to-understand remedy to our collective information overload and an essential guide to making smart, confident decisions in the face of uncertainty.

Simulation Modeling & Analysis


Averill M. Law - 1982
    The new edition includes the most up-to-date research developments and many more examples and problems.

Statistical Methods for Psychology


David C. Howell - 2001
    This book has two underlying themes that are more or less independent of the statistical hypothesis tests that are the main content of the book. The first theme is the importance of looking at the data before formulating a hypothesis. With this in mind, the author discusses, in detail, plotting data, looking for outliers, and checking assumptions (Graphical displays are used extensively). The second theme is the importance of the relationship between the statistical test to be employed and the theoretical questions being posed by the experiment. To emphasize this relationship, the author uses real examples to help the student understand the purpose behind the experiment and the predictions made by the theory. Although this book is designed for students at the intermediate level or above, it does not assume that students have had either a previous course in statistics or a course in math beyond high-school algebra.