The state also rises : the roots of contemporary state activism / Jonah D. Levy -- The transformation of the British state : from club government to state-administered high modernism / Michael Moran -- The forgotten center : state activism and corporatist adjustment in Holland and Germany / Anton C. Hemerijck and Mark I. Vail -- Exiting Etatisme? new directions in state policy in France and Japan / Jonah D. Levy, Mari Miura, and Gene Park -- The state and the reconstruction of industrial relations institutions after fordism : Britain and France compared / Chris Howell -- Building finance capitalism : the regulatory politics of corporate governance reform in the United States and Germany / John W. Cioffi -- From maternalism to "employment for all" : state politics to promote women's employment across the affluent democracies / Ann Shola Orloff -- The state in the digital economy / John Zysman and Abraham Newman -- Building global service markets : economic structure and state capacity / Peter Cowhey and John Richards -- The transformation of European trading states / Richard H. Steinberg -- The State and statism : from market direction to market support / Jonah D. Levy.

The end of the Cold War ushered in an age of American triumphalism best characterized by the "Washington Consensus:" the idea that free markets, democratic institutions, limitations on government involvement in the economy, and the rule of law were the foundations of prosperity and stability. The last fifteen years, starting with the Asian financial crisis, have seen the gradual erosion of that consensus. Many commentators have pointed to the emergence of a powerful new rival model: state capitalism. In state capitalist regimes, the government typically owns firms in strategic industries. Not beholden to private-sector shareholders, such firms are allowed to operate with razor-thin margins if the state deems them strategically important. China, soon to be the world's largest economy, is the best known state capitalist regime, but it is hardly the only one. In State Capitalism, Joshua Kurlantzick ranges across the world--China, Thailand, Brazil, Russia, South Africa, Turkey, and more--and argues that the increase in state capitalism across the globe has, on balance, contributed to a decline in democracy. He isolates some of the reasons for state capitalism's resurgence: the fact that globalization favors economies of scale in the most critical industries, and the widespread rejection of the Washington Consensus in the face of the problems that have plagued the world economy in recent years. That said, a number of democratic nations have embraced state capitalism, and in those regimes, state-backed firms like Brazil's Embraer have enjoyed considerable success. Kurlantzick highlights the mixed record and the evolving nature of the model, yet he is more concerned about the negative effects of state capitalism. When states control firms, whether in democratic or authoritarian regimes, the government increases its advantage over the rest of society. The combination of new technologies, the perceived failures of liberal economics and democracy in many developing nations, the rise of modern kinds of authoritarians, and the success of some of the best-known state capitalists have created an era ripe for state intervention. State Capitalism offers the sharpest analysis yet of what state capitalism's emergence means for democratic politics around the world.

Online Statistics: An Interactive Multimedia Course of Study is a resource for learning and teaching introductory statistics. It contains material presented in textbook format and as video presentations. This resource features interactive demonstrations and simulations, case studies, and an analysis lab.This print edition of the public domain textbook gives the student an opportunity to own a physical copy to help enhance their educational experience. This part I features the book Front Matter, Chapters 1-10, and the full Glossary. Chapters Include:: I. Introduction, II. Graphing Distributions, III. Summarizing Distributions, IV. Describing Bivariate Data, V. Probability, VI. Research Design, VII. Normal Distributions, VIII. Advanced Graphs, IX. Sampling Distributions, and X. Estimation. Online Statistics Education: A Multimedia Course of Study (http: //onlinestatbook.com/). Project Leader: David M. Lane, Rice University.

Introductory Statistics follows scope and sequence requirements of a one-semester introduction to statistics course and is geared toward students majoring in fields other than math or engineering. The text assumes some knowledge of intermediate algebra and focuses on statistics application over theory. Introductory Statistics includes innovative practical applications that make the text relevant and accessible, as well as collaborative exercises, technology integration problems, and statistics labs. Senior Contributing Authors Barbara Illowsky, De Anza College Susan Dean, De Anza College Contributing Authors Daniel Birmajer, Nazareth College Bryan Blount, Kentucky Wesleyan College Sheri Boyd, Rollins College Matthew Einsohn, Prescott College James Helmreich, Marist College Lynette Kenyon, Collin County Community College Sheldon Lee, Viterbo University Jeff Taub, Maine Maritime Academy

Leviathan is back The threat of statism has reemerged in force. The federal government has radically expanded its power—through bailouts, “stimulus” packages, a trillion-dollar health-care plan, “jobs bills,” massive expansions of the money supply, and much more. But such interventionism did not suddenly materialize with the recent economic collapse. The dangerous trends of government growth, debt increases, encroachments on individual liberty, and attacks on the free market began years earlier and continued no matter which political party was in power. This shift toward statism “will not end happily,” declares bestselling author Thomas E. Woods. In Back on the Road to Serfdom, Woods brings together ten top scholars to examine why the size and scope of government has exploded, and to reveal the devastating consequences of succumbing to the statist temptation. Spanning history, economics, politics, religion, and the arts, Back on the Road to Serfdom shows: · How government interventionism endangers America’s prosperity and the vital culture of entrepreneurship · The roots of statism: from the seminal conflict between Thomas Jefferson and Alexander Hamilton to the vast expansion of federal power in the twentieth century · Why the standard explanation for the recent economic crisis is so terribly wrong—and why the government’s frenzied responses to the downturn only exacerbate the problems · Why the European welfare state is not a model to aspire to but a disaster to be avoided · How an intrusive state not only harms the economy but also imperils individual liberty and undermines the role of civil society · The fatal flaws in the now-common arguments against free markets and free trade · How big business is helping government pave the road to serfdom · Why the Judeo-Christian tradition does not demand support for the welfare state, but in fact values the free market · How the arrogance of government power extends even to the cultural realm—and how central planning is just as inefficient and destructive there It’s been more than sixty-five years since F. A. Hayek published his seminal work The Road to Serfdom. Now this impeccably timed book provides another desperately needed warning about—and corrective to—the dangers of statism.

Algebraic statistics uses tools from algebraic geometry, commutative algebra, combinatorics, and their computational sides to address problems in statistics and its applications. The starting point for this connection is the observation that many statistical models are semialgebraic sets. The algebra/statistics connection is now over twenty years old, and this book presents the first broad introductory treatment of the subject. Along with background material in probability, algebra, and statistics, this book covers a range of topics in algebraic statistics including algebraic exponential families, likelihood inference, Fisher's exact test, bounds on entries of contingency tables, design of experiments, identifiability of hidden variable models, phylogenetic models, and model selection. With numerous examples, references, and over 150 exercises, this book is suitable for both classroom use and independent study.

An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance, marketing, and astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, deep learning, survival analysis, multiple testing, and more. Color graphics and real-world examples are used to illustrate the methods presented. This book is targeted at statisticians and non-statisticians alike, who wish to use cutting-edge statistical learning techniques to analyze their data. Four of the authors co-wrote An Introduction to Statistical Learning, With Applications in R (ISLR), which has become a mainstay of undergraduate and graduate classrooms worldwide, as well as an important reference book for data scientists. One of the keys to its success was that each chapter contains a tutorial on implementing the analyses and methods presented in the R scientific computing environment. However, in recent years Python has become a popular language for data science, and there has been increasing demand for a Python-based alternative to ISLR. Hence, this book (ISLP) covers the same materials as ISLR but with labs implemented in Python. These labs will be useful both for Python novices, as well as experienced users.

Scientific progress depends on good research, and good research needs good statistics. But statistical analysis is tricky to get right, even for the best and brightest of us. You'd be surprised how many scientists are doing it wrong. Statistics Done Wrong is a pithy, essential guide to statistical blunders in modern science that will show you how to keep your research blunder-free. You'll examine embarrassing errors and omissions in recent research, learn about the misconceptions and scientific politics that allow these mistakes to happen, and begin your quest to reform the way you and your peers do statistics. You'll find advice on: –Asking the right question, designing the right experiment, choosing the right statistical analysis, and sticking to the plan –How to think about p values, significance, insignificance, confidence intervals, and regression –Choosing the right sample size and avoiding false positives –Reporting your analysis and publishing your data and source code –Procedures to follow, precautions to take, and analytical software that can help Scientists: Read this concise, powerful guide to help you produce statistically sound research. Statisticians: Give this book to everyone you know. The first step toward statistics done right is Statistics Done Wrong.