Downs treats this differently than do other students of politics. His explanations are systematically related to, and deductible from, precisely stated assumptions about the motivations that attend the decisions of voters and parties and the environment in which they act. He is consciously concerned with the economy in explanation, that is, with attempting to account for phenomena in terms of a very limited number of facts and postulates. He is concerned also with the central features of party politics in any democratic state, not with that in the United State or any other single country. I. BASIC STRUCTURE OF THE MODEL. 1. Introduction. 2. Party Motivation and the Function of Government in Society. 3. The Basic Logic of Voting. 4. The Basic Logic of Government Decision-Making. II. THE GENERAL EFFECTS OF UNCERTAINTY. 5. The Meaning of Uncertainty. 6. How Uncertainty Affects Government Decision-Making. 7. The Development of Political Ideologies as Means of Getting Votes. 8. The Statics and Dynamics of Party Ideologies 9. Problems of Rationality Under Coalition Governments. 10. Government Vote-Maximizing and Individual marginal Equilibrium. III. SPECIFIC EFFECTS OF INFORMATION COSTS. 11. The Process of Becoming Informed. 12. How Rational Citizens Reduce Information Costs. 13. The Returns From Information and Their Diminution. 14. The Causes and Effects of Rational Abstention. IV. DERIVATIVE IMPLICATIONS AND HYPOTHESIS. 15. A Comment on Economic Theories of Government Behavior. 16. Testable Prepositions Derived from the Theory.

    In the modern experimentalist paradigm, these techniques address clear causal questions such as: Do smaller classes increase learning? Should wife batterers be arrested? How much does education raise wages? Mostly Harmless Econometrics shows how the basic tools of applied econometrics allow the data to speak.In addition to econometric essentials, Mostly Harmless Econometrics covers important new extensions--regression-discontinuity designs and quantile regression--as well as how to get standard errors right. Joshua Angrist and Jorn-Steffen Pischke explain why fancier econometric techniques are typically unnecessary and even dangerous. The applied econometric methods emphasized in this book are easy to use and relevant for many areas of contemporary social science.An irreverent review of econometric essentials A focus on tools that applied researchers use most Chapters on regression-discontinuity designs, quantile regression, and standard errors Many empirical examples A clear and concise resource with wide applications

    These topics lie at the heart of many exciting areas of contemporary science and engineering - communication, signal processing, data mining, machine learning, pattern recognition, computational neuroscience, bioinformatics, and cryptography. This textbook introduces theory in tandem with applications. Information theory is taught alongside practical communication systems, such as arithmetic coding for data compression and sparse-graph codes for error-correction. A toolbox of inference techniques, including message-passing algorithms, Monte Carlo methods, and variational approximations, are developed alongside applications of these tools to clustering, convolutional codes, independent component analysis, and neural networks. The final part of the book describes the state of the art in error-correcting codes, including low-density parity-check codes, turbo codes, and digital fountain codes -- the twenty-first century standards for satellite communications, disk drives, and data broadcast. Richly illustrated, filled with worked examples and over 400 exercises, some with detailed solutions, David MacKay's groundbreaking book is ideal for self-learning and for undergraduate or graduate courses. Interludes on crosswords, evolution, and sex provide entertainment along the way. In sum, this is a textbook on information, communication, and coding for a new generation of students, and an unparalleled entry point into these subjects for professionals in areas as diverse as computational biology, financial engineering, and machine learning.

    Intuitive Biostatistics covers all the topics typically found in an introductory statistics text, but with the emphasis on confidence intervals rather than P values, making it easier for students to understand both. Additionally, it introduces a broad range of topics left out of most other introductory texts but used frequently in biomedical publications, including survival curves. multiple comparisons, sensitivity and specificity of lab tests, Bayesian thinking, lod scores, and logistic, proportional hazards and nonlinear regression. By emphasizing interpretation rather than calculation, this text provides a clear and virtually painless introduction to statistical principles for those students who will need to use statistics constantly in their work. In addition, its practical approach enables readers to understand the statistical results published in biological and medical journals.

    

    Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning.The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models.Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors.

    Many designers and researchers view usability and design as qualitative activities, which do not require attention to formulas and numbers. However, usability practitioners and user researchers are increasingly expected to quantify the benefits of their efforts. The impact of good and bad designs can be quantified in terms of conversions, completion rates, completion times, perceived satisfaction, recommendations, and sales.The book discusses ways to quantify user research; summarize data and compute margins of error; determine appropriate samples sizes; standardize usability questionnaires; and settle controversies in measurement and statistics. Each chapter concludes with a list of key points and references. Most chapters also include a set of problems and answers that enable readers to test their understanding of the material. This book is a valuable resource for those engaged in measuring the behavior and attitudes of people during their interaction with interfaces.

    Employing a methodology that is primarily learning by example and “thinking with our eyes,” this manual features graphs and practical analytical techniques that can be applied to a broad range of data analysis tools—including the most commonly used Microsoft Excel. This approach is particularly valuable to those who need to make sense of quantitative business data by discerning meaningful patterns, trends, relationships, and exceptions that reveal business performance, potential problems and opportunities, and hints about the future. It provides practical skills that are useful to managers at all levels and to those interested in keeping a keen eye on their business.

    Mark Plaster takes readers beyond the ambulance bay doors into the stranger-than-fiction world of the Emergency Department. By turns heart-warming and gut-wrenching, "Night Shift" chronicles the ebb and flow of human life, in all of its unvarnished glory, as it passes through the doors of the ED.

    Showing how these political philosophies have all been decisively shaped by the core values of the Enlightenment, he demonstrates that each one contains useful insights that survive their failures as comprehensive doctrines and that should inform our thinking about political legitimacy. Shapiro then turns to the democratic tradition. Exploring the main arguments for and against democracy from Plato's time until our own, he argues that democracy offers the best resources for realizing the Enlightenment's promise and managing its internal tensions. As such, democracy supplies the most attractive available basis for political legitimacy.

    This idea--using computers to spy on people and groups perceived as a threat, both at home and abroad--drove ARPA to develop the internet in the 1960s, and continues to be at the heart of the modern internet we all know and use today. As Levine shows, surveillance wasn't something that suddenly appeared on the internet; it was woven into the fabric of the technology.But this isn't just a story about the NSA or other domestic programs run by the government. As the book spins forward in time, Levine examines the private surveillance business that powers tech-industry giants like Google, Facebook, and Amazon, revealing how these companies spy on their users for profit, all while doing double duty as military and intelligence contractors. Levine shows that the military and Silicon Valley are effectively inseparable: a military-digital complex that permeates everything connected to the internet, even coopting and weaponizing the antigovernment privacy movement that sprang up in the wake of Edward Snowden.With deep research, skilled storytelling, and provocative arguments, Surveillance Valley will change the way you think about the news--and the device on which you read it.

    They describe theories and research finding from the field of judgement and decision making in a non-technical manner, using anecdotes as a teaching device. Intended as an introductory textbook for advanced undergraduate and graduate students, the material not only is of scholarly interest but is practical as well.

    Starting from the basics of probability, the authors develop the theory of statistical inference using techniques, definitions, and concepts that are statistical and are natural extensions and consequences of previous concepts. This book can be used for readers who have a solid mathematics background. It can also be used in a way that stresses the more practical uses of statistical theory, being more concerned with understanding basic statistical concepts and deriving reasonable statistical procedures for a variety of situations, and less concerned with formal optimality investigations.

    Explains to outsiders the conflicts between the financial interests of the coal and land companies, and the moral rights of the vulnerable mountaineers.

    Merriam synthesizes twenty years of developments in qualitative research with clarity and acumen." ?Michael Quinn Patton, author, Qualitative Research and Evaluation Methods"Here is a qualitative research methods book that reinforces the connection between professional experience and qualitative inquiry." ?Robert Stake, author, The Art of Case Study Research and Multiple Case Study Analysis"In this new edition, Sharan Merriam once again presents the world of qualitative research in language engaging and accessible?for new and experienced readers alike. If you can have only one book about qualitative research, this is it!" ?Patricia M. Reeves, associate professor, School of Social Work, University of Georgia"Mystified by qualitative research? You couldn't ask for a better guide than Sharan Merriam, who introduces you to the fundamental concepts of this research method, explains its complex forms, and then shows you exactly how to do a high-quality qualitative study." ?M. Carolyn Clark, coeditor, The International Journal of Qualitative Studies in Education