Statistical Complexity

In Complexity Economics for Environmental Governance, Jean-François Mercure reframes environmental policy and provides a rigorous methodology necessary to tackle the complexity of environmental policy and the transition to sustainability. The book offers a detailed account of the deficiencies of environmental economics and then develops a theory of innovation and macroeconomics based on complexity theory. It also develops a new foundation for evidence-based policy-making using a Risk-Opportunity Analysis applied to the sustainability transition. This multidisciplinary work was developed in partnership with prominent natural scientists and economists as well as active policy-makers with the aim to revolutionize thinking in the face of the full complexity of the sustainability transition, and to show how it can best be governed to minimize its distributional impacts. The book should be read by academics and policy-makers seeking new ways to think about environmental policy-making.

A comprehensive introduction to the most commonly used statistical methods relevant in atmospheric, oceanic and climate sciences. Each method is described step-by-step using plain language, and illustrated with concrete examples, with relevant statistical and scientific concepts explained as needed. Particular attention is paid to nuances and pitfalls, with sufficient detail to enable the reader to write relevant code. Topics covered include hypothesis testing, time series analysis, linear regression, data assimilation, extreme value analysis, Principal Component Analysis, Canonical Correlation Analysis, Predictable Component Analysis, and Covariance Discriminant Analysis. The specific statistical challenges that arise in climate applications are also discussed, including model selection problems associated with Canonical Correlation Analysis, Predictable Component Analysis, and Covariance Discriminant Analysis. Requiring no previous background in statistics, this is a highly accessibl

The twenty-first century has seen a breathtaking expansion of statistical methodology, both in scope and influence. 'Data science' and 'machine learning' have become familiar terms in the news, as statistical methods are brought to bear upon the enormous data sets of modern science and commerce. How did we get here? And where are we going? How does it all fit together? Now in paperback and fortified with exercises, this book delivers a concentrated course in modern statistical thinking. Beginning with classical inferential theories - Bayesian, frequentist, Fisherian - individual chapters take up a series of influential topics: survival analysis, logistic regression, empirical Bayes, the jackknife and bootstrap, random forests, neural networks, Markov Chain Monte Carlo, inference after model selection, and dozens more. The distinctly modern approach integrates methodology and algorithms with statistical inference. Each chapter ends with class-tested exercises, and the book concludes wit

S-PLUS is the statistical software of choice for many applied researchers in disciplines ranging from finance to medicine. This book focuses on statistical techniques, applies them to one or more data

This cross-disciplinary volume provides an overview of how complexity theory and the tools of statistical mechanics can be applied to linguistic problems to help reveal language groups, and to model the evolution and competition of languages in space and time. Illustrated with a series of case studies and worked examples, it presents an interdisciplinary framework to enable researchers from the mathematical, physical and social sciences to collaborate on linguistic problems. It demonstrates the complexity of linguistic databases and provides a mathematical toolkit for analyzing and extracting useful information from them - helping to conceptualize empirical facts better than a mere ethnographic view. Providing an important bridge to facilitate collaboration between linguists and mathematical modelers, this book will stimulate new ideas and avenues for research, and will form a valuable resource for advanced students and academics working across complex systems, sociolinguistics, and la

This clear and pedagogical text delivers a concise overview of classical and quantum statistical physics. Essential Statistical Physics shows students how to relate the macroscopic properties of physical systems to their microscopic degrees of freedom, preparing them for graduate courses in areas such as biophysics, condensed matter physics, atomic physics and statistical mechanics. Topics covered include the microcanonical, canonical, and grand canonical ensembles, Liouville's Theorem, Kinetic Theory, non-interacting Fermi and Bose systems and phase transitions, and the Ising model. Detailed steps are given in mathematical derivations, allowing students to quickly develop a deep understanding of statistical techniques. End-of-chapter problems reinforce key concepts and introduce more advanced applications, and appendices provide a detailed review of thermodynamics and related mathematical results. This succinct book offers a fresh and intuitive approach to one of the most challenging

This pedagogical and self-contained text describes the modern mean field theory of simple structural glasses. The book begins with a thorough explanation of infinite-dimensional models in statistical physics, before reviewing the key elements of the thermodynamic theory of liquids and the dynamical properties of liquids and glasses. The central feature of the mean field theory of disordered systems, the existence of a large multiplicity of metastable states, is then introduced. The replica method is then covered, before the final chapters describe important, advanced topics such as Gardner transitions, complexity, packing spheres in large dimensions, the jamming transition, and the rheology of glass. Presenting the theory in a clear and pedagogical style, this is an excellent resource for researchers and graduate students working in condensed matter physics and statistical mechanics.

The fourth edition of Statistical Concepts for the Behavioral Sciences emphasizes contemporary research problems to better illustrate the relevance of statistical analysis in scientific research. All statistical methods are introduced in the context of a realistic problem, many of which are from contemporary published research. These studies are fully referenced so students can easily access the original research. The uses of statistics are then developed and presented in a conceptually logical progression for increased comprehension by using the accompanying workbook and the problem sets. Several forms of practice problems are available to students and presented in a manner that assists students in mastering component pieces before integrating them together to tackle more complicated, real-world problems.

Statistical Concepts-A Second Course presents the last 10 chapters from An Introduction to Statistical Concepts, Fourth Edition. Designed for second and upper-level statistics courses, this book highl

Statistical Programming in SAS Second Edition provides a foundation for programming to implement statistical solutions using SAS, a system that has been used to solve data analytic problems for more t

This book explores noun phrase (NP) complexity in English, showing that it is best accounted for both by a linear and a hierarchical parameter: its length and its type of postmodifier(s). The study is methodologically unique in that it combines univariate and multivariate analyses in an investigation of four different syntactic variables. Drawing on more than three billion words of British and American data, Eva Berlage shows that the length and the structure of the NPs, along with language-external factors such as the regional variety of English, work as powerful determinants of the variation. On a theoretical level, the book reveals that the structural complexity of NPs cannot be sufficiently captured by (phrasal) node counts but that we need to incorporate the degree to which NPs are sentential. The book is designed for researchers and students interested in syntax, language variation, sociolinguistics, structural complexity and the history of English.

Statistical Inference via Data Science: A ModernDive into R and the Tidyverse provides a pathway for learning about statistical inference using data science tools widely used in industry, academia, an

Doubt over the trustworthiness of published empirical results is not unwarranted and is often a result of statistical mis-specification: invalid probabilistic assumptions imposed on data. Now in its second edition, this bestselling textbook offers a comprehensive course in empirical research methods, teaching the probabilistic and statistical foundations that enable the specification and validation of statistical models, providing the basis for an informed implementation of statistical procedure to secure the trustworthiness of evidence. Each chapter has been thoroughly updated, accounting for developments in the field and the author's own research. The comprehensive scope of the textbook has been expanded by the addition of a new chapter on the Linear Regression and related statistical models. This new edition is now more accessible to students of disciplines beyond economics and includes more pedagogical features, with an increased number of examples as well as review questions and e

The Process of Research and Statistical Analysis in Psychology presents integrated coverage of psychological research methods and statistical analysis to illustrate how these two crucial processes wor

Doubt over the trustworthiness of published empirical results is not unwarranted and is often a result of statistical mis-specification: invalid probabilistic assumptions imposed on data. Now in its second edition, this bestselling textbook offers a comprehensive course in empirical research methods, teaching the probabilistic and statistical foundations that enable the specification and validation of statistical models, providing the basis for an informed implementation of statistical procedure to secure the trustworthiness of evidence. Each chapter has been thoroughly updated, accounting for developments in the field and the author's own research. The comprehensive scope of the textbook has been expanded by the addition of a new chapter on the Linear Regression and related statistical models. This new edition is now more accessible to students of disciplines beyond economics and includes more pedagogical features, with an increased number of examples as well as review questions and e

This book is a readable, digestible introduction to exponential families, encompassing statistical models based on the most useful distributions in statistical theory, including the normal, gamma, binomial, Poisson, and negative binomial. Strongly motivated by applications, it presents the essential theory and then demonstrates the theory's practical potential by connecting it with developments in areas like item response analysis, social network models, conditional independence and latent variable structures, and point process models. Extensions to incomplete data models and generalized linear models are also included. In addition, the author gives a concise account of the philosophy of Per Martin-Löf in order to connect statistical modelling with ideas in statistical physics, including Boltzmann's law. Written for graduate students and researchers with a background in basic statistical inference, the book includes a vast set of examples demonstrating models for applications and exerc

This book is a readable, digestible introduction to exponential families, encompassing statistical models based on the most useful distributions in statistical theory, including the normal, gamma, binomial, Poisson, and negative binomial. Strongly motivated by applications, it presents the essential theory and then demonstrates the theory's practical potential by connecting it with developments in areas like item response analysis, social network models, conditional independence and latent variable structures, and point process models. Extensions to incomplete data models and generalized linear models are also included. In addition, the author gives a concise account of the philosophy of Per Martin-Löf in order to connect statistical modelling with ideas in statistical physics, including Boltzmann's law. Written for graduate students and researchers with a background in basic statistical inference, the book includes a vast set of examples demonstrating models for applications and exerc

Statistical Concepts-A First Course presents the first 10 chapters from An Introduction to Statistical Concepts, Fourth Edition. Designed for first and lower-level statistics courses, this book commun

Proof complexity is a rich subject drawing on methods from logic, combinatorics, algebra and computer science. This self-contained book presents the basic concepts, classical results, current state of the art and possible future directions in the field. It stresses a view of proof complexity as a whole entity rather than a collection of various topics held together loosely by a few notions, and it favors more generalizable statements. Lower bounds for lengths of proofs, often regarded as the key issue in proof complexity, are of course covered in detail. However, upper bounds are not neglected: this book also explores the relations between bounded arithmetic theories and proof systems and how they can be used to prove upper bounds on lengths of proofs and simulations among proof systems. It goes on to discuss topics that transcend specific proof systems, allowing for deeper understanding of the fundamental problems of the subject.

Computational Complexity of Counting and Sampling provides readers with comprehensive and detailed coverage of the subject of computational complexity. It is primarily geared for researchers in enumer

Computational Complexity of Counting and Sampling provides readers with comprehensive and detailed coverage of the subject of computational complexity. It is primarily geared for researchers in enumer

This book develops in detail the statistical foundations of nonequilibrium thermodynamics, based on the mathematical theory of Brownian motion. Author Bernard H. Lavenda demonstrates that thermodynami

Comprehensively teaches the basics of testing statistical assumptions in research and the importance in doing so This book facilitates researchers in checking the assumptions of statistical tests used

This book presents and applies a framework for studying the complexity of algorithms. It is aimed at logicians, computer scientists, mathematicians and philosophers interested in the theory of computation and its foundations, and it is written at a level suitable for non-specialists. Part I provides an accessible introduction to abstract recursion theory and its connection with computability and complexity. This part is suitable for use as a textbook for an advanced undergraduate or graduate course: all the necessary elementary facts from logic, recursion theory, arithmetic and algebra are included. Part II develops and applies an extension of the homomorphism method due jointly to the author and Lou van den Dries for deriving lower complexity bounds for problems in number theory and algebra which (provably or plausibly) restrict all elementary algorithms from specified primitives. The book includes over 250 problems, from simple checks of the reader's understanding, to current open pr

This volume, Statistical Methods in Psychiatry Research and SPSS, now going into its second edition, has been helping psychiatrists expand their knowledge of statistical methods and fills the gaps in

The Statistical Abstract of the United States is the best known statistical reference. As a comprehensive collection of statistics on the social, political, and economic conditions of the country, it

This book stages a dialogue between international researchers from the broad fields of complexity science and narrative studies. It presents an edited collection of chapters on aspects of how narrativ

This book aims to cover a broad range of topics in statistical physics, including statistical mechanics (equilibrium and non-equilibrium), soft matter and fluid physics, for applications to biological

This book provides an accessible presentation of concepts from probability theory, statistical methods, the design of experiments and statistical quality control. It is shaped by the experience of the

This book introduces and discusses the analysis of interacting many-body complex systems exhibiting spontaneous synchronization from the perspective of nonequilibrium statistical physics. While such systems have been mostly studied using dynamical system theory, the book underlines the usefulness of the statistical physics approach to obtain insightful results in a number of representative dynamical settings. Although it is intractable to follow the dynamics of a particular initial condition, statistical physics allows to derive exact analytical results in the limit of an infinite number of interacting units. Chapter one discusses dynamical characterization of individual units of synchronizing systems as well as of their interaction and summarizes the relevant tools of statistical physics. The latter are then used in chapters two and three to discuss respectively synchronizing systems with either a first- or a second-order evolution in time. This book provides a timely introduction to

Expand your Python skills by working with data structures and algorithms in a refreshing context—through an eye-opening exploration of complexity science. Whether you’re an intermediate-le

Managing Complexity: Earth Systems and Strategies for the Future introduces and explores systems and complexity in relation to near-synchronous world and environmental problems. These relate to but ar

This collection of essays explores the different ways the insights from complexity theory can be applied to law. Complexity theory – a variant of systems theory – views law as an emergent, complex, se

Complexity lies at the heart of social work practice and this book is designed to help students and newly-qualified social workers plan for and manage complex cases in an increasingly complex environm

Complexity lies at the heart of social work practice and this book is designed to help students and newly-qualified social workers plan for and manage complex cases in an increasingly complex environm

Statistical Methods for Field and Laboratory Studies in Behavioral Ecology focuses on how statistical methods may be used to make sense of behavioral ecology and other data. It presents fundamental co

This edited book focuses on the latest developments in classification, statistical learning, data analysis and related areas of data science, including statistical analysis of large datasets, big data

A comprehensive guide to automated statistical data cleaning The production of clean data is a complex and time-consuming process that requires both technical know-how and statistical expertise.

This book presents an innovative unified approach to the statistical foundations of entropy and the fundamentals of equilibrium statistical mechanics. These intimately related subjects are often devel

This volume considers regional approaches to social complexity from a variety of perspectives and at a global scale.