For increasingly data-savvy clients, lawyers can no longer give "it depends" answers rooted in anecdata. Clients insist that their lawyers justify their reasoning, and with more than a limited set of war stories. The considered judgment of an experienced lawyer is unquestionably valuable. However, on balance, clients would rather have the considered judgment of an experienced lawyer informed by the most relevant information required to answer their questions. Data-Driven Law: Data Analytics and the New Legal Services helps legal professionals meet the challenges posed by a data-driven approach to delivering legal services. Its chapters are written by leading experts who cover such topics as: Mining legal data Computational law Uncovering bias through the use of Big Data Quantifying the quality of legal services Data mining and decision-making Contract analytics and contract standards In addition to providing clients with data-based insight, legal firms can track a matter with data from beginning to end, from the marketing spend through to the type of matter, hours spent, billed, and collected, including metrics on profitability and success. Firms can organize and collect documents after a matter and even automate them for reuse. Data on marketing related to a matter can be an amazing source of insight about which practice areas are most profitable. Data-driven decision-making requires firms to think differently about their workflow. Most firms warehouse their files, never to be seen again after the matter closes. Running a data-driven firm requires lawyers and their teams to treat information about the work as part of the service, and to collect, standardize, and analyze matter data from cradle to grave. More than anything, using data in a law practice requires a different mindset about the value of this information. This book helps legal professionals to develop this data-driven mindset.

Identifying factors which stimulate regional growth and international competitiveness and using them for forecasting are the aims of this book. Departing from the theory of comparative advantages and their impact, the author demonstrates that such an approach has to be based on a sound theoretical foundation and on appropriate, advanced econometric methods. He proposes the use of heuristic optimization techniques, Monte Carlo simulation experiments and Lasso-type estimators to avoid bias or misleading findings, which might be the result of applying standard regression methods when key assumptions are not satisfied. In addition, the author demonstrates how some heuristic optimization-based methods can be used to obtain forecasts of industrial production in Russia and Germany founded on past observations and some leading indicators.

Open government data (OGD) has developed rapidly in recent years due to various benefits that can be derived through transparency and public access. However, researchers emphasize a lack of use instead of lack of disclosure as a key problem in OGD's present development. Previous studies have approached this issue either from the supply-side, focusing on data quantity and quality, or from the demand-side, focusing on factors that affect users' acceptance of OGD, but seldom consider both sides at the same time. This unique study compares the supply and demand sides of OGD and explores possible directions for the future development of OGD portals based on the discovered mismatches between the two. The authors improve OGD utilization by balancing the supply-side and demand-side according to citizens' demands through OGD portals. Based on the concept of an OGD ecosystem, four connected studies are explored. The first study built an evaluation framework for understanding the development of the OGD supply-side. The second study focuses on a survey conducted to analyze the awareness and utilization of OGD portals by citizens, who are the primary users and major beneficiaries of OGD on the demand-side. A third study compares the supply and demand sides based on Diffusion of Innovation theory. A final study tests the proposed usability criteria for building an OGD portal by carrying out a between-subjects experiment including a virtual agent. Each case study examines a unique aspect of OGD in China, and also offers reflections on future directions for developing OGD. Providing a unique and enhanced theoretical and practical understanding of OGD and its usage, as well as proposing directions for OGD portals' future development in order to encourage citizens' OGD utilization, this is a must-read for researchers and policymakers examining the impact and possibilities of OGD.

This book comprises three studies on minority shareholder monitoring in Germany. Mandatory disclosure requirements have increased transparency. An analysis of the information that is publicly available is presented, regardless of the size of the target corporation. The second essay in the form of an event study pays special attention to the German supervisory board and its appointment for a fixed term. Capital markets perceive an activist effort as being more credible under certain circumstances. The study as a whole is empirical evidence for increased minority shareholder activity in Germany. The evidence presented supports the strong shareholder rights perspective. It conflicts with the weak shareholder rights view brought forward in the international literature.

This book introduces readers to a workload-aware methodology for large-scale graph algorithm optimization in graph-computing systems, and proposes several optimization techniques that can enable these systems to handle advanced graph algorithms efficiently. More concretely, it proposes a workload-aware cost model to guide the development of high-performance algorithms. On the basis of the cost model, the book subsequently presents a system-level optimization resulting in a partition-aware graph-computing engine, PAGE. In addition, it presents three efficient and scalable advanced graph algorithms - the subgraph enumeration, cohesive subgraph detection, and graph extraction algorithms. This book offers a valuable reference guide for junior researchers, covering the latest advances in large-scale graph analysis; and for senior researchers, sharing state-of-the-art solutions based on advanced graph algorithms. In addition, all readers will find a workload-aware methodology for designing efficient large-scale graph algorithms.

The SPSS Survival Manual throws a lifeline to students and researchers grappling with this powerful data analysis software. In her bestselling guide, Julie Pallant takes you through the entire research process, helping you choose the right data analysis technique for your project. This edition has been updated to include up to SPSS version 26. From the formulation of research questions, to the design of the study and analysis of data, to reporting the results, Julie discusses basic and advanced statistical techniques. She outlines each technique clearly, with step-by-step procedures for performing the analysis, a detailed guide to interpreting data output and an example of how to present the results in a report. For both beginners and experienced users in Psychology, Sociology, Health Sciences, Medicine, Education, Business and related disciplines, the SPSS Survival Manual is an essential text. It is illustrated throughout with screen grabs, examples of output and tips, and is also further supported by a website with sample data and guidelines on report writing. This seventh edition is fully revised and updated to accommodate changes to IBM SPSS procedures.

This book presents an accessible introduction to data-driven storytelling. Resulting from unique discussions between data visualization researchers and data journalists, it offers an integrated definition of the topic, presents vivid examples and patterns for data storytelling, and calls out key challenges and new opportunities for researchers and practitioners.

THE NEW BOOK FROM THE BESTSELLING AUTHOR OF EVERYBODY LIES 'Don't Trust Your Gut is a tour de force - an intoxicating blend of analysis, humor, and humanity' DANIEL H. PINK 'Seth Stephens-Davidowitz is an expert on data-driven thinking, and this engaging book is full of surprising, useful insights for using the information at your fingertips to make better decisions' ADAM GRANT Big decisions are hard. We might consult friends and family, read advice online or turn to self-help books for guidance, but in the end we usually just do what feels right. But what if our gut is wrong? As economist and former Google data scientist Seth Stephens-Davidowitz argues, our gut is actually not that reliable - and data can prove this. In Don't Trust Your Gut, he unearths the startling conclusions that the right data can teach us about who we are and what will make our lives better. Over the past decade, scholars have mined enormous datasets to find remarkable new approaches to life's biggest self-help puzzles, from the boring careers that produce the most wealth, to old-school, data-backed relationship advice. While we often think we know how to better ourselves, the numbers, it turns out, disagree. Telling fascinating stories through the latest big data research, Stephens-Davidowitz reveals just how wrong we really are when it comes to improving our lives, and offers a new way of tackling our most consequential choices.

A century of education and education reform, along with more than three decades of high-stakes testing and accountability, reveals a disturbing paradox: education has a steadfast commitment to testing and grading. This commitment persists despite ample research, theory, and philosophy revealing the corrosive consequences of both testing and grading in an education system designed to support human agency and democratic principles. This revised edited volume brings together a collection of updated and new essays that confronts the failure of testing and grading. The book explores the historical failure of testing and grading; the theoretical and philosophical arguments against testing and grading; the negative influence of tests and grades on social justice, race, class, and gender; and the role that they play in perpetuating a deficit perspective of children. The chapters fall under two broad sections. Part I, Degrading Learning, Detesting Education: The Failure of High-Stake Accountability in Education, includes essays on the historical, theoretical, and philosophical arguments against testing and grading. Part II, De-Grading and De-Testing in a Time of High-Stakes Education Reform, presents practical experiments in de-testing and de-grading classrooms for authentic learning experiences.

Python is one of the most popular programming languages, widely used for data analysis and modelling, and is fast becoming the leading choice for scientists and engineers. Unlike other textbooks introducing Python, typically organised by language syntax, this book uses many examples from across Biology, Chemistry, Physics, Earth science, and Engineering to teach and motivate students in science and engineering. The text is organised by the tasks and workflows students undertake day-to-day, helping them see the connections between programming tools and their disciplines. The pace of study is carefully developed for complete beginners, and a spiral pedagogy is used so concepts are introduced across multiple chapters, allowing readers to engage with topics more than once. "Try This!" exercises and online Jupyter notebooks encourage students to test their new knowledge, and further develop their programming skills. Online solutions are available for instructors, alongside discipline-specific homework problems across the sciences and engineering.

Petty trade helped vast numbers of people to survive the crisis faced by post-Soviet Russia. The book analyses how this survival technique was carried out in practice. On the basis of his fieldwork research, the author shows how people coped with rapid social change and places their activities within a context of government policies, migration flows and entrepreneurial strategies. "This is an original work based on extensive fieldwork research. Wielecki skillfully intertwined "ethnographic meat" with "the bones of theory", which has resulted in a "flesh-and-blood" anthropology." Michal Buchowski "This is an immensely insightful exploration of petty trade in post-Soviet Russia. The author laces his genuine ethnographic work in a coherent account of the concepts of uncertainty, embeddedness, and informal economy." Violetta Zentai

As the analysis of big datasets in sports performance becomes a more entrenched part of the sporting landscape, so the value of sport scientists and analysts with formal training in data analytics grows. Sports Analytics: Analysis, Visualisation and Decision Making in Sports Performance provides the most authoritative and comprehensive guide to the use of analytics in sport and its application in sports performance, coaching, talent identification and sports medicine available. Employing an approach-based structure and integrating problem-based learning throughout the text, the book clearly defines the difference between analytics and analysis and goes on to explain and illustrate methods including: Interactive visualisation Simulation and modelling Geospatial data analysis Spatiotemporal analysis Machine learning Genomic data analysis Social network analysis Offering a mixed-methods case study chapter, no other book offers the same level of scientific grounding or practical application in sports data analytics. Sports Analytics is essential reading for all students of sports analytics, and useful supplementary reading for students and professionals in talent identification and development, sports performance analysis, sports medicine and applied computer science.

Critical Theory and Qualitative Data Analysis in Education offers a path-breaking explanation of how critical theories can be used within the analysis of qualitative data to inform research processes, such as data collection, analysis, and interpretation. This contributed volume offers examples of qualitative data analysis techniques and exemplars of empirical studies that employ critical theory concepts in data analysis. By creating a clear and accessible bridge between data analysis and critical social theories, this book helps scholars and researchers effectively translate their research designs and findings to multiple audiences for more equitable outcomes and disruption of historical and contemporary inequality.

Introduces new and advanced methods of model discovery for time-series data using artificial intelligence. Implements topological approaches to distill "machine-intuitive" models from complex dynamics data. Introduces a new paradigm for a parsimonious model of a dynamical system without resorting to differential equations. Heralds a new era in data-driven science and engineering based on the operational concept of "computational intuition".

"Using Web and Paper Questionnaires for Data-Based Decision Making maintains the same strengths as Thomas?s previous book: it is clearly written, easy to understand, and has plenty of examples and guides for those implementing these ideas. Designed as a cookbook, it superbly enables educators to write, administer, and analyze a survey."

Sandra L. Stein, Professor of Education

Rider University

How effectively are teachers implementing the new literacy program? What do parents think of the proposed homework policy? Is bullying a growing problem? Understanding how to create appropriate questionnaires is essential in making data-based decisions that improve school policies, processes, and procedures.

Using Web and Paper Questionnaires for Data-Based Decision Making is a practical handbook for creating exceptional questionnaires for a variety of purposes, including data-based decision making. Author Susan J. Thomas provides authoritative guidance for planning a survey project, creating a questionnaire, gathering data, and analyzing and communicating the results to a variety of audiences.

Features of this reader-friendly guidebook include

• Sample cover letters, invitations, parental permission forms, and planning templates
• Extensive examples, activities, and checklists
• Web-based questionnaire guidelines
• A step-by-step case study of a successful survey project
• Appendices with further resources and recommended readings

Offering suggestions for successfully using both Web-based and paper-based questionnaires, this practitioner-focused manual summarizes the key steps of successful survey projects and identifies critical success factors for each step.

Designed primarily for principals, district-level administrators, and teachers, this invaluable resource is also suitable for policymakers, state-level administrators, and graduate students in education and social sciences.

View the Table of Contents. Read Chapter 1.

"Auerbach and Silverstein write at a level that can be understood by beginners but is sophisticated enough for scholars...informative and interesting."
--"Choice"

Qualitative Data is meant for the novice researcher who needs guidance on what specifically to do when faced with a sea of information. It takes readers through the qualitative research process, beginning with an examination of the basic philosophy of qualitative research, and ending with planning and carrying out a qualitative research study. It provides an explicit, step-by-step procedure that will take the researcher from the raw text of interview data through data analysis and theory construction to the creation of a publishable work.

The volume provides actual examples based on the authors' own work, including two published pieces in the appendix, so that readers can follow examples for each step of the process, from the project's inception to its finished product. The volume also includes an appendix explaining how to implement these data analysis procedures using NVIVO, a qualitative data analysis program.

Classification and regression trees (CART) is one of the several contemporary statistical techniques with good promise for research in many academic fields. There are very few books on CART, especially on applied CART. This book, as a good practical primer with a focus on applications, introduces the relatively new statistical technique of CART as a powerful analytical tool. The easy-to-understand (non-technical) language and illustrative graphs (tables) as well as the use of the popular statistical software program (SPSS) appeal to readers without strong statistical background. This book helps readers understand the foundation, the operation, and the interpretation of CART analysis, thus becoming knowledgeable consumers and skillful users of CART. The chapter on advanced CART procedures not yet well-discussed in the literature allows readers to effectively seek further empowerment of their research designs by extending the analytical power of CART to a whole new level. This highly practical book is specifically written for academic researchers, data analysts, and graduate students in many disciplines such as economics, social sciences, medical sciences, and sport sciences who do not have strong statistical background but still strive to take full advantage of CART as a powerful analytical tool for research in their fields.

This book is concerned with data in which the observations are independent and in which the response is multivariate. Anthony Atkinson has been Professor of Statistics at the London School of Economics since 1989. Before that he was a Professor at Imperial College, London. He is the author of Plots, Transformations, and Regression, co-author of Optimum Experimental Designs, and joint editor of The Fascination of Statistics, a volume celebrating the centenary of the International Statistical Institute. Professor Atkinson has served as editor of The Journal of the Royal Statistical Society, Series B and as associate editor of Biometrika and Technometrics. He has published well over 100 articles in these and other journals including The Annals of Statistics, Biometrics, The Journal of the American Statistical Association, and Statistics and Computing. Marco Riani, after receiving his Ph.D. in Statistics in 1995 from the University of Florence, joined the Faculty of Economics at Parma University as postdoctoral fellow. In 1997 he won the prize for the best Italian Ph.D. thesis in Statistics. He is currently Associate Professor of Statistics in the University of Parma. He has published in Technometrics, The Journal of Computational and Graphical Statistics, The Journal of Business and Economic Statistics, The Journal of Forecasting, Environmetrics, Computational Statistics and Data Analysis, Metron, and other journals.

From the reviews:

"The book requires knowledge of multivariate statistical methods, because it provides only basic background information on the methods considered (although with excellent references for futher reading at the end of each chapter). Each chapter alsoincludes exercises with solutions...This book could serve as an excellent text for an advanced course on modern multivariate statistics, as it is intended." Technometrics, November 2004

"This book is full of interest for anyone undertaking multivariate analyses, clearly emphasizing that uncritical use of standard methods can be misleading." Short Book Reviews of the International Statistical Institute, December 2004

"This book is an interesting complement to various textbooks on multivariate statistics." Biometrics, December 2005

"This book discusses multivariate data from a different perspective. a ] it is an excellent book for researchers with interests in multivariate data and cluster analysis. It may also be a good reference for students of advanced statistics and practitioners working with large volumes of data a ] ." (Kassim S. Mwitondi, Journal of Applied Statistics, Vol. 32 (4), 2005)

"This is a companion to an earlier book a ] both of which feature many informative graphs. Here, the forward search has been applied in detail to classical multivariate approaches used with Gaussian data. a ] One valuable feature of the book is the way that the illustrations concentrate on a relatively small number a ] . This makes it easy to concentrate on the application a ] . The implications of this book also strengthen the importance of data visualization, as well as providing a valuable approach to visualization." (Paul Hewson, Journal of the Royal Statistical Society Series A, Vol. 168 (2), 2005)

"This book is a companion to Atkinson a ] . The objective is to identify outliers, appreciate their influence a ] which would result in an overall improvement. a ] Graphical tools arewidely used, resulting in three hundred and ninety figures. Each chapter is followed by extensive exercises and their solutions, and the book could be used as an advanced textbook for multivariate analysis courses. Web-sites provide the relevant software a ] . This book is full of interest for anyone undertaking multivariate analyses a ] ." (B.J.T. Morgan, Short Book Reviews International Statistical Institute, Vol. 24 (3), 2004)

"This book discusses forward search (FS), a method using graphs to explore and model continuous multivariate data a ] . Its viewpoint is toward applications, and it demonstrates the merits of FS using a variety of examples, with a thorough discussion of statistical issues and interpretation of results. a ] This book could serve as an excellent text for an advanced course on modern multivariate statistics, as it is intended." (Tena Ipsilantis Katsaounis, Technometrics, Vol. 46 (4), November, 2004)

"The theoretical exercises with detailed solutions at the end of each chapter are extremely useful. I would recommend this book to practitioners who analyze moderately sized multivariate data. Of course, anyone associated with the application of statistics should find the book interesting to read." (Tathgata Banerjee, Journal of the American Statistical Association, March 2006)

For many organizations data is a by-product, but for the smarter ones it is the heartbeat of their business. Most businesses have a wealth of data buried in their systems which, if used effectively, could increase revenue, reduce costs and risk and improve customer satisfaction and employee experience. Beginning with how to choose projects which reflect your organization's goals and how to make the business case for investing in data, this book then takes the reader through the five 'waves' of organizational data maturity. It takes the reader from getting started on the data journey with some quick wins, to how data can help your business become a leading innovator which systematically outperforms competitors. Data and Analytics Strategy for Business outlines how to build consistent, high-quality sources of data which will create business value and explores how automation, AI and machine learning can improve performance and decision making. Filled with real-world examples and case studies, this book is a stage-by-stage guide to designing and implementing a results-driven data strategy.

Praise forEnvisioning the Survey Interview of the Future

"This book is an excellent introduction to some brave new technologies . . . and their possible impacts on the way surveys might be conducted. Anyone interested in the future of survey methodology should read this book."

Norman M. Bradburn, PhD, National Opinion Research Center, University of Chicago

"Envisioning the Survey Interview of the Future gathers some of the brightest minds in alternative methods of gathering self-report data, with an eye toward the future self-report sample survey. Conrad and Schober, by assembling a group of talented survey researchers and creative inventors of new software-based tools to gather information from human subjects, have created a volume of importance to all interested in imagining future ways of interviewing."

Robert M. Groves, PhD, Survey Research Center, University of Michigan

This collaboration provides extensive insight into the impact of communication technology on survey research

As previously unimaginable communication technologies rapidly become commonplace, survey researchers are presented with both opportunities and obstacles when collecting and interpreting data based on human response. Envisioning the Survey Interview of the Future explores the increasing influence of emerging technologies on the data collection process and, in particular, self-report data collection in interviews, providing the key principles for using these new modes of communication.

With contributions written by leading researchers in the fields of survey methodology and communication technology, this compilation integrates the use of modern technological developments with establishedsocial science theory. The book familiarizes readers with these new modes of communication by discussing the challenges to accuracy, legitimacy, and confidentiality that researchers must anticipate while collecting data, and it also provides tools for adopting new technologies in order to obtain high-quality results with minimal error or bias.

Envisioning the Survey Interview of the Future addresses questions that researchers in survey methodology and communication technology must consider, such as:

How and when should new communication technology be adopted in the interview process?

What are the principles that extend beyond particular technologies?

Why do respondents answer questions from a computer differently than questions from a human interviewer?

How can systems adapt to respondents' thinking and feeling?

What new ethical concerns about privacy and confidentiality are raised from using new communication technologies?

With its multidisciplinary approach, extensive discussion of existing and future technologies, and practical guidelines for adopting new technology, Envisioning the Survey Interview of the Future is an essential resource for survey methodologists, questionnaire designers, and communication technologists in any field that conducts survey research. It also serves as an excellent supplement for courses in research methods at the upper-undergraduate or graduate level.

Making sense of sports performance data can be a challenging task but is nevertheless an essential part of performance analysis investigations. Focusing on techniques used in the analysis of sport performance, this book introduces the fundamental principles of data analysis, explores the most important tools used in data analysis, and offers guidance on the presentation of results.

The book covers key topics such as:

• The purpose of data analysis, from statistical analysis to algorithmic processing
• Commercial packages for performance and data analysis, including Focus, Sportscode, Dartfish, Prozone, Excel, SPSS and Matlab
• Effective use of statistical procedures in sport performance analysis
• Analysing data from manual notation systems, player tracking systems and computerized match analysis systems
• Creating visually appealing dashboard interfaces for presenting data
• Assessing reliability.

The book includes worked examples from real sport, offering clear guidance to the reader and bringing the subject to life. This book is invaluable reading for any student, researcher or analyst working in sport performance or undertaking a sport-related research project or methods course"

This is the first comprehensive overview of the 'science of science,' an emerging interdisciplinary field that relies on big data to unveil the reproducible patterns that govern individual scientific careers and the workings of science. It explores the roots of scientific impact, the role of productivity and creativity, when and what kind of collaborations are effective, the impact of failure and success in a scientific career, and what metrics can tell us about the fundamental workings of science. The book relies on data to draw actionable insights, which can be applied by individuals to further their career or decision makers to enhance the role of science in society. With anecdotes and detailed, easy-to-follow explanations of the research, this book is accessible to all scientists and graduate students, policymakers, and administrators with an interest in the wider scientific enterprise.

This textbook presents an innovative new perspective on the economics of development, including insights from a broad range of disciplines. It starts with the current state of affairs, a discussion of data availability, reliability, and analysis, and an historic overview of the deep influence of fundamental factors on human prosperity. Next, it focuses on the role of human interaction in terms of trade, capital, and knowledge flows, as well as the associated implications for institutions, contracts, and finance. The book also highlights differences in the development paths of emerging countries in order to provide a better understanding of the concepts of development and the Millennium Development Goals. Insights from other disciplines are used help to understand human development with regard to other issues, such as inequalities, health, demography, education, and poverty. The book concludes by emphasizing the importance of connections, location, and human interaction in determining future prosperity.

This dissertation comprises five studies analyzing daily stock returns of listed firms. Studies one and two shed light on corporate diversification through M&A and how related risk dynamics affect shareholder wealth. Carrying over the risk analysis methodology 'GARCH' to external events in studies three and four, the author individually scrutinizes the adverse implications of bank failures and bailouts in the 2007-2009 financial crisis. Finding opposing return shocks, he identifies the limits of the 'symmetric' GARCH. As observed of the behavior of stock return data, volatility reacts asymmetrically to positive and negative return shocks. The advanced EGARCH incorporates this so called 'leverage effect'. Applying the EGARCH in his final study, the author can simultaneously scrutinize the adverse bank events with an appropriate econometric foundation.

Achieve successful digital transformation with this authoritative guide designed specifically for established organizations. At a time where even the most recognized business models are under threat, organizations risk devastation if they do not transition successfully to the new digital reality. Yet what works for digital natives does not always work for established organizations. Recognized as one of the world's top global executives leading innovative transformation, Neetan Chopra's deep experience of steering organizations through digital disruption drives the practical approach of Accelerated Digital Transformation. Having designed transformation journeys, overcome setbacks and driven outcomes within multiple leading companies, Neetan Chopra tackles key factors for established organizations including inertia, impetus, outcomes, digital capabilities and culture. The book is underpinned by a tried and tested framework that will guide readers step by step through the entire digital transformation journey. This will be an essential resource for leaders, managers and practitioners leading and executing digital transformation.