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Since the emerging discipline of engineering enterprise systems extends traditional systems engineering to develop webs of systems and systems-of-systems, the engineering management and management science communities need new approaches for analyzing and managing risk in engineering enterprise systems. Advanced Risk Analysis in Engineering Enterpri
Statistical methods are a key part of data science, yet few data scientists have formal statistical training. Courses and books on basic statistics rarely cover the topic from a data science perspective. The second edition of this popular guide adds comprehensive examples in Python, provides practical guidance on applying statistical methods to data science, tells you how to avoid their misuse, and gives you advice on what’s important and what’s not. Many data science resources incorporate statistical methods but lack a deeper statistical perspective. If you’re familiar with the R or Python programming languages and have some exposure to statistics, this quick reference bridges the gap...
The focus of this book is on the birth and historical development of permutation statistical methods from the early 1920s to the near present. Beginning with the seminal contributions of R.A. Fisher, E.J.G. Pitman, and others in the 1920s and 1930s, permutation statistical methods were initially introduced to validate the assumptions of classical statistical methods. Permutation methods have advantages over classical methods in that they are optimal for small data sets and non-random samples, are data-dependent, and are free of distributional assumptions. Permutation probability values may be exact, or estimated via moment- or resampling-approximation procedures. Because permutation methods are inherently computationally-intensive, the evolution of computers and computing technology that made modern permutation methods possible accompanies the historical narrative. Permutation analogs of many well-known statistical tests are presented in a historical context, including multiple correlation and regression, analysis of variance, contingency table analysis, and measures of association and agreement. A non-mathematical approach makes the text accessible to readers of all levels.
The Outcast Majority invites policymakers, practitioners, academics, students, and others to think about three commanding contemporary issues—war, development, and youth—in new ways. The starting point is the following irony: while African youth are demographically dominant, most see themselves as members of an outcast minority. The irony directly informs young people’s lives in war-affected Africa, where differences separating the priorities of youth and those of international agencies are especially prominent. Drawing on interviews with development experts and young people, Marc Sommers shines a light on this gap and offers guidance on how to close it. He begins with a comprehensive consideration of forces that shape and propel the lives of African youth today, particularly those experiencing or emerging from war. They are contrasted with forces that influence and constrain the international development aid enterprise. The book concludes with a framework for making development policies and practices significantly more relevant and effective for youth in areas affected by African wars and other places where vast and vibrant youth populations reside.
A considerable number of journal publications using a range of qualitative synthesis approaches has been published. Mary Dixon-Woods and colleagues (Mary Dixon-Woods, Booth, & Sutton, 2007) identified 42 qualitative evidence synthesis papers published in health care literature between 1990 and 2004. An ongoing update by Hannes and Macaitis (2010)identified around 100 additional qualitative or mixed methods syntheses. Yet these generally lack a clear, detailed description of what was done and why (Greenhalgh et al, 2007; McInnes & Wimpenny, 2008). Choices are most commonly influenced by what others have successfully used in the past or by a particular school of thought (Atkins et al, 2008; Br...
One of the most salient findings from the field of education is that there are huge national differences in student achievement as shown in international comparative studies like PISA and TIMSS. The shockingly large gap between the highest performing countries (mostly in East Asia) and many European countries corresponds to a difference in attainment of two years of schooling. Although this finding has been replicated in several studies, the reasons for and consequences of such differences are currently not well understood. This book is a collection of essays and studies by leading experts in international comparative education who demonstrate how international comparative assessments can be used to evaluate educational policies. The volume is organized into two parts that address, first, theoretical foundations and methodological developments in the field of international assessments, and, second, innovative substantive studies that utilize international data for policy evaluation studies. The intention of this book is to revisit the idea of 'using the world as an educational laboratory', both to inform policy and to facilitate theory development.
Computational inference is based on an approach to statistical methods that uses modern computational power to simulate distributional properties of estimators and test statistics. This book describes computationally intensive statistical methods in a unified presentation, emphasizing techniques, such as the PDF decomposition, that arise in a wide range of methods.
This book examines the field of learning disabilities and the education of learning disabled (LD) children through the eyes of several experts. Contributors bring to the book such diverse academic backgrounds as education, psychology, special education, a.
"Randomization tests are not a new idea, but they only became really useful after the advent of fast computing. Making randomization tests accessible to many more potential users by providing the means to use them within familiar statistical software, this book serves as an introduction and provides macros to perform in the familiar environments of SPSS and Excel. Though we expect that the book will still appeal to researchers, we believe the changes in the new edition will make the book an essential aid for graduate and senior undergraduate courses in statistics, data analysis, and/or research methods, taught in departments of psychology (especially clinical or counseling psychology), medicine, nursing, and other health and social sciences"--Provided by publisher.
This book analyses and elaborates on learning processes within work environments and explores professional learning. It presents research indicating general characteristics of the work environment that support learning, as well as barriers to workplace learning. Themes of professional development, lifelong learning and business organisation emerge through the chapters and contributions explore theoretical and empirical analyses on the boundary between working and learning in various contexts and with various methodological approaches. Readers will discover how current workplace learning approaches can emphasise the learning potential of the work environment and how workplaces can combine the...