"The Myth of the Normal Curve provides a much-needed critique of commonly and even scientifically accepted notions of normality. For too long we have supported an ideology of normality without much interrogation of the subject. This book provides that interrogation."---Lennard J. Davis, Professor of English and Disability Studies, University of Illinois at Chicago --Book Jacket.

An in-depth guide to understanding probability distributions and financial modeling for the purposes of investment management In Financial Models with Lévy Processes and Volatility Clustering, the expert author team provides a framework to model the behavior of stock returns in both a univariate and a multivariate setting, providing you with practical applications to option pricing and portfolio management. They also explain the reasons for working with non-normal distribution in financial modeling and the best methodologies for employing it. The book's framework includes the basics of probability distributions and explains the alpha-stable distribution and the tempered stable distribution. The authors also explore discrete time option pricing models, beginning with the classical normal model with volatility clustering to more recent models that consider both volatility clustering and heavy tails. Reviews the basics of probability distributions Analyzes a continuous time option pricing model (the so-called exponential Lévy model) Defines a discrete time model with volatility clustering and how to price options using Monte Carlo methods Studies two multivariate settings that are suitable to explain joint extreme events Financial Models with Lévy Processes and Volatility Clustering is a thorough guide to classical probability distribution methods and brand new methodologies for financial modeling.

This book chronicles the professional life of a career-long, inclusive educator in New York City through eight different stages in special and general education. Developing a new approach to research as part of qualitative methodology, David J. Connor merges the academic genre of autoethnography with memoir to create a narrative that engages the reader through stories of personal experiences within the professional world that politicized him as an educator. After each chapter’s narrative, a systematic analytic commentary follows that focuses on: teaching and learning in schools and universities; the influence of educational laws; specific models of disability and how influence educators and educational researchers; and educational structures and systems—including their impact on social, political, and cultural experiences of people with disabilities. This autoethnographic memoir documents, over three decades, the relationship between special and general education, the growth of the inclusion movement, and the challenge of special education as a discrete academic field. As part of a national group of critical special educators, Connor describes the growth of counter-theory through the inception and subsequent growth of DSE as a viable academic field, and the importance of rethinking human differences in new ways.

This book answers two questions: What does the implementation of inclusive education require of a system of education and all parts of the system? How do various parts of the education system act on their commitment to inclusive educational practice? Decades after major legislation (i.e., the Civil Rights Act, the Elementary and Secondary Education Act, and the Education for All Handicapped Children Act) made high-quality education a fundamental right for all children in the United States, the dream of diverse, inclusive, democratic schooling has yet to be realized. Nevertheless, some classrooms, schools, districts, states, and universities have made progress. Inclusive Education: A Systematic Perspective explores the theoretical implications of inclusive practice as well as illustrative case studies and evaluation findings from states, educator preparation programs, districts, and schools that have reframed their work around the principles of inclusive practice. Whether these organizations position the work as “social justice education,” “culturally responsive teaching,” or “inclusion,” their efforts lead in the same direction—toward higher quality and more equitable education for all. The chapters will be relevant to graduate students, faculty members, and education leaders, at all levels, who seek a comprehensive overview of the commitment and practice of “inclusive education”. Chapters vary in their approaches to the topic, some presenting theoretical underpinnings, others describing practices or programs at particular sites, others reporting findings from empirical studies, and edited interviews with state and district leaders of inclusive-education initiatives. The book explores why inclusion is important and how it can be accomplished.

Every child should have access to an education that works. The Quest for a Meaningful Special Education follows the educational journeys of nine students with a language-based learning disability (LBLD) who, through a combination of parental advocacy and luck, were removed from a debilitating learning situation and enrolled in a school designed to address their particular learning needs. In the process of following their journeys, the book explores the role of cultures within and outside the school and examines some of the ways that the construction of special education has affected student learning. In the context of the ongoing national conversation about student academic success, high school dropout rates, the disproportionate number of prison inmates with learning disabilities, the costs of educating students, and the controversy over the placement of minorities in special education, The Quest For a Meaningful Special Education is a timely book that will add a new perspective to current debates

Statistics and probability are fascinating fields, tightly interwoven with the context of the problems which have to be modelled. The authors demonstrate how investigations and experiments provide promising teaching strategies to help high-school students acquire statistical and probabilistic literacy. In the first chapter the authors put into practice the following educational principles, reflecting their views of how these subjects should be taught: a focus on the most relevant ideas and postpone extensions to later stages; illustrating the complementary/dual nature of statistical and probabilistic reasoning; utilising the potential of technology and show its limits; and reflecting on the different levels of formalisation to meet the wide variety of students’ previous knowledge, abilities, and learning types. The remaining chapters deal with exploratory data analysis, modelling information by probabilities, exploring and modelling association, and with sampling and inference. Throughout the book, a modelling view of the concepts guides the presentation. In each chapter, the development of a cluster of fundamental ideas is centred around a statistical study or a real-world problem that leads to statistical questions requiring data in order to be answered. The concepts developed are designed to lead to meaningful solutions rather than remain abstract entities. For each cluster of ideas, the authors review the relevant research on misconceptions and synthesise the results of research in order to support teaching of statistics and probability in high school. What makes this book unique is its rich source of worked-through tasks and its focus on the interrelations between teaching and empirical research on understanding statistics and probability.

A New York Times–bestselling author looks at mathematics education in America—when it’s worthwhile, and when it’s not. Why do we inflict a full menu of mathematics—algebra, geometry, trigonometry, even calculus—on all young Americans, regardless of their interests or aptitudes? While Andrew Hacker has been a professor of mathematics himself, and extols the glories of the subject, he also questions some widely held assumptions in this thought-provoking and practical-minded book. Does advanced math really broaden our minds? Is mastery of azimuths and asymptotes needed for success in most jobs? Should the entire Common Core syllabus be required of every student? Hacker worries that our nation’s current frenzied emphasis on STEM is diverting attention from other pursuits and even subverting the spirit of the country. Here, he shows how mandating math for everyone prevents other talents from being developed and acts as an irrational barrier to graduation and careers. He proposes alternatives, including teaching facility with figures, quantitative reasoning, and understanding statistics. Expanding upon the author’s viral New York Times op-ed, The Math Myth is sure to spark a heated and needed national conversation—not just about mathematics but about the kind of people and society we want to be. “Hacker’s accessible arguments offer plenty to think about and should serve as a clarion call to students, parents, and educators who decry the one-size-fits-all approach to schooling.” —Publishers Weekly, starred review

The mathematical and statistical tools needed in the rapidly growing quantitative finance field With the rapid growth in quantitative finance, practitioners must achieve a high level of proficiency in math and statistics. Mathematical Methods and Statistical Tools for Finance, part of the Frank J. Fabozzi Series, has been created with this in mind. Designed to provide the tools needed to apply finance theory to real world financial markets, this book offers a wealth of insights and guidance in practical applications. It contains applications that are broader in scope from what is covered in a typical book on mathematical techniques. Most books focus almost exclusively on derivatives pricing, the applications in this book cover not only derivatives and asset pricing but also risk management—including credit risk management—and portfolio management. Includes an overview of the essential math and statistical skills required to succeed in quantitative finance Offers the basic mathematical concepts that apply to the field of quantitative finance, from sets and distances to functions and variables The book also includes information on calculus, matrix algebra, differential equations, stochastic integrals, and much more Written by Sergio Focardi, one of the world's leading authors in high-level finance Drawing on the author's perspectives as a practitioner and academic, each chapter of this book offers a solid foundation in the mathematical tools and techniques need to succeed in today's dynamic world of finance.

"Learning Statistics with R" covers the contents of an introductory statistics class, as typically taught to undergraduate psychology students, focusing on the use of the R statistical software and adopting a light, conversational style throughout. The book discusses how to get started in R, and gives an introduction to data manipulation and writing scripts. From a statistical perspective, the book discusses descriptive statistics and graphing first, followed by chapters on probability theory, sampling and estimation, and null hypothesis testing. After introducing the theory, the book covers the analysis of contingency tables, t-tests, ANOVAs and regression. Bayesian statistics are covered at the end of the book. For more information (and the opportunity to check the book out before you buy!) visit http://ua.edu.au/ccs/teaching/lsr or http://learningstatisticswithr.com

Formerly published by Chicago Business Press, now published by Sage Performance Management, Fifth Edition covers the design and implementation of effective and successful performance management systems – the key tools that can be used to transform employee talent and motivation into a strategic business advantage. Author Herman Aguinis focuses on research-based findings and up-to-date applications that consider the changing nature of work and organizations. Hear the author share teaching strategies using content from the Fifth Edition.