| data science wayne state: Data Analysis Techniques for Physical Scientists Claude A. Pruneau, 2017-10-05 A comprehensive guide to data analysis techniques for physical scientists, providing a valuable resource for advanced undergraduate and graduate students, as well as seasoned researchers. The book begins with an extensive discussion of the foundational concepts and methods of probability and statistics under both the frequentist and Bayesian interpretations of probability. It next presents basic concepts and techniques used for measurements of particle production cross-sections, correlation functions, and particle identification. Much attention is devoted to notions of statistical and systematic errors, beginning with intuitive discussions and progressively introducing the more formal concepts of confidence intervals, credible range, and hypothesis testing. The book also includes an in-depth discussion of the methods used to unfold or correct data for instrumental effects associated with measurement and process noise as well as particle and event losses, before ending with a presentation of elementary Monte Carlo techniques. |
| data science wayne state: Exit and Voice Lauren Duquette-Rury, 2019-11-26 A free open access ebook is available upon publication. Learn more at www.luminosoa.org. Sometimes leaving home allows you to make an impact on it—but at what cost? Exit and Voice is a compelling account of how Mexican migrants with strong ties to their home communities impact the economic and political welfare of the communities they have left behind. In many decentralized democracies like Mexico, migrants have willingly stepped in to supply public goods when local or state government lack the resources or political will to improve the town. Though migrants’ cross-border investments often improve citizens’ access to essential public goods and create a more responsive local government, their work allows them to unintentionally exert political engagement and power, undermining the influence of those still living in their hometowns. In looking at the paradox of migrants who have left their home to make an impact on it, Exit and Voice sheds light on how migrant transnational engagement refashions the meaning of community, democratic governance, and practices of citizenship in the era of globalization. |
| data science wayne state: Detroit Remains Krysta Ryzewski, 2021-11-16 An archaeologically grounded narrative of six legendary Detroit places-- |
| data science wayne state: Healthcare Data Analytics Chandan K. Reddy, Charu C. Aggarwal, 2015-06-23 At the intersection of computer science and healthcare, data analytics has emerged as a promising tool for solving problems across many healthcare-related disciplines. Supplying a comprehensive overview of recent healthcare analytics research, Healthcare Data Analytics provides a clear understanding of the analytical techniques currently available |
| data science wayne state: Environmental Statistics and Data Analysis Wayne R. Ott, 2018-12-13 This easy-to-understand introduction emphasizes the areas of probability theory and statistics that are important in environmental monitoring, data analysis, research, environmental field surveys, and environmental decision making. It communicates basic statistical theory with very little abstract mathematical notation, but without omitting importa |
| data science wayne state: Statistical Foundations of Data Science Jianqing Fan, Runze Li, Cun-Hui Zhang, Hui Zou, 2020-09-21 Statistical Foundations of Data Science gives a thorough introduction to commonly used statistical models, contemporary statistical machine learning techniques and algorithms, along with their mathematical insights and statistical theories. It aims to serve as a graduate-level textbook and a research monograph on high-dimensional statistics, sparsity and covariance learning, machine learning, and statistical inference. It includes ample exercises that involve both theoretical studies as well as empirical applications. The book begins with an introduction to the stylized features of big data and their impacts on statistical analysis. It then introduces multiple linear regression and expands the techniques of model building via nonparametric regression and kernel tricks. It provides a comprehensive account on sparsity explorations and model selections for multiple regression, generalized linear models, quantile regression, robust regression, hazards regression, among others. High-dimensional inference is also thoroughly addressed and so is feature screening. The book also provides a comprehensive account on high-dimensional covariance estimation, learning latent factors and hidden structures, as well as their applications to statistical estimation, inference, prediction and machine learning problems. It also introduces thoroughly statistical machine learning theory and methods for classification, clustering, and prediction. These include CART, random forests, boosting, support vector machines, clustering algorithms, sparse PCA, and deep learning. |
| data science wayne state: Robust Quality Rajesh Jugulum, 2018-09-03 Historically, the term quality was used to measure performance in the context of products, processes and systems. With rapid growth in data and its usage, data quality is becoming quite important. It is important to connect these two aspects of quality to ensure better performance. This book provides a strong connection between the concepts in data science and process engineering that is necessary to ensure better quality levels and takes you through a systematic approach to measure holistic quality with several case studies. Features: Integrates data science, analytics and process engineering concepts Discusses how to create value by considering data, analytics and processes Examines metrics management technique that will help evaluate performance levels of processes, systems and models, including AI and machine learning approaches Reviews a structured approach for analytics execution |
| data science wayne state: Data Clustering Charu C. Aggarwal, Chandan K. Reddy, 2013-08-21 Research on the problem of clustering tends to be fragmented across the pattern recognition, database, data mining, and machine learning communities. Addressing this problem in a unified way, Data Clustering: Algorithms and Applications provides complete coverage of the entire area of clustering, from basic methods to more refined and complex data clustering approaches. It pays special attention to recent issues in graphs, social networks, and other domains. The book focuses on three primary aspects of data clustering: Methods, describing key techniques commonly used for clustering, such as feature selection, agglomerative clustering, partitional clustering, density-based clustering, probabilistic clustering, grid-based clustering, spectral clustering, and nonnegative matrix factorization Domains, covering methods used for different domains of data, such as categorical data, text data, multimedia data, graph data, biological data, stream data, uncertain data, time series clustering, high-dimensional clustering, and big data Variations and Insights, discussing important variations of the clustering process, such as semisupervised clustering, interactive clustering, multiview clustering, cluster ensembles, and cluster validation In this book, top researchers from around the world explore the characteristics of clustering problems in a variety of application areas. They also explain how to glean detailed insight from the clustering process—including how to verify the quality of the underlying clusters—through supervision, human intervention, or the automated generation of alternative clusters. |
| data science wayne state: Analytics Across the Enterprise Brenda L. Dietrich, Emily C. Plachy, Maureen F. Norton, 2014-05-15 How to Transform Your Organization with Analytics: Insider Lessons from IBM’s Pioneering Experience Analytics is not just a technology: It is a better way to do business. Using analytics, you can systematically inform human judgment with data-driven insight. This doesn’t just improve decision-making: It also enables greater innovation and creativity in support of strategy. Your transformation won’t happen overnight; however, it is absolutely achievable, and the rewards are immense. This book demystifies your analytics journey by showing you how IBM has successfully leveraged analytics across the enterprise, worldwide. Three of IBM’s pioneering analytics practitioners share invaluable real-world perspectives on what does and doesn’t work and how you can start or accelerate your own transformation. This book provides an essential framework for becoming a smarter enterprise and shows through 31 case studies how IBM has derived value from analytics throughout its business. Coverage Includes Creating a smarter workforce through big data and analytics More effectively optimizing supply chain processes Systematically improving financial forecasting Managing financial risk, increasing operational efficiency, and creating business value Reaching more B2B or B2C customers and deepening their engagement Optimizing manufacturing and product management processes Deploying your sales organization to increase revenue and effectiveness Achieving new levels of excellence in services delivery and reducing risk Transforming IT to enable wider use of analytics “Measuring the immeasurable” and filling gaps in imperfect data Whatever your industry or role, whether a current or future leader, analytics can make you smarter and more competitive. Analytics Across the Enterprise shows how IBM did it--and how you can, too. Learn more about IBM Analytics |
| data science wayne state: Edge Computing: A Primer Jie Cao, Quan Zhang, Weisong Shi, 2018-11-01 The success of the Internet of Things and rich cloud services have helped create the need for edge computing, in which data processing occurs in part at the network edge, rather than completely in the cloud. In Edge Computing: A Primer the vision and definition of Edge computing is introduced, as well as several key techniques that enable Edge computing. Then, four applications that benefit from Edge computing are presented as case studies, ranging from smart homes and public safety to medical services, followed by a discussion of several open challenges and opportunities in Edge computing. Finally, several key tools for edge computing such as virtualization and resource management are explained. |
| data science wayne state: Contemporary Archaeology and the City Laura McAtackney, Krysta Ryzewski, 2017 This book argues archaeology is uniquely placed to contribute a variety of perspectives on the current life-cycles of cities including processes of decay, revitalization, and transformation. It foregrounds the materialities of post-industrial, post-modern and other urban transformations through a diverse, international collection of case studies. |
| data science wayne state: Common Data Sense for Professionals Rajesh Jugulum, 2022-01-27 Data is an intrinsic part of our daily lives. Everything we do is a data point. Many of these data points are recorded with the intent to help us lead more efficient lives. We have apps that track our workouts, sleep, food intake, and personal finance. We use the data to make changes to our lives based on goals we have set for ourselves. Businesses use vast collections of data to determine strategy and marketing. Data scientists take data, analyze it, and create models to help solve problems. You may have heard of companies having data management teams or chief information officers (CIOs) or chief data officers (CDOs), etc. They are all people who work with data, but their function is more related to vetting data and preparing it for use by data scientists. The jump from personal data usage for self-betterment to mass data analysis for business process improvement often feels bigger to us than it is. In turn, we often think big data analysis requires tools held only by advanced degree holders. Although advanced degrees are certainly valuable, this book illustrates how it is not a requirement to adequately run a data science project. Because we are all already data users, with some simple strategies and exposure to basic analytical software programs, anyone who has the proper tools and determination can solve data science problems. The process presented in this book will help empower individuals to work on and solve data-related challenges. The goal of this book is to provide a step-by-step guide to the data science process so that you can feel confident in leading your own data science project. To aid with clarity and understanding, the author presents a fictional restaurant chain to use as a case study, illustrating how the various topics discussed can be applied. Essentially, this book helps traditional businesspeople solve data-related problems on their own without any hesitation or fear. The powerful methods are presented in the form of conversations, examples, and case studies. The conversational style is engaging and provides clarity. |
| data science wayne state: Financial Data Analytics Sinem Derindere Köseoğlu, 2022-04-25 This book presents both theory of financial data analytics, as well as comprehensive insights into the application of financial data analytics techniques in real financial world situations. It offers solutions on how to logically analyze the enormous amount of structured and unstructured data generated every moment in the finance sector. This data can be used by companies, organizations, and investors to create strategies, as the finance sector rapidly moves towards data-driven optimization. This book provides an efficient resource, addressing all applications of data analytics in the finance sector. International experts from around the globe cover the most important subjects in finance, including data processing, knowledge management, machine learning models, data modeling, visualization, optimization for financial problems, financial econometrics, financial time series analysis, project management, and decision making. The authors provide empirical evidence as examples of specific topics. By combining both applications and theory, the book offers a holistic approach. Therefore, it is a must-read for researchers and scholars of financial economics and finance, as well as practitioners interested in a better understanding of financial data analytics. |
| data science wayne state: Energy Efficient Manufacturing John W. Sutherland, David A. Dornfeld, Barbara S. Linke, 2018-08-14 Over the last several years, manufacturers have expressed increasing interest in reducing their energy consumption and have begun to search for opportunities to reduce their energy usage. In this book, the authors explore a variety of opportunities to reduce the energy footprint of manufacturing. These opportunities cover the entire spatial scale of the manufacturing enterprise: from unit process-oriented approaches to enterprise-level strategies. Each chapter examines some aspect of this spatial scale, and discusses and describes the opportunities that exist at that level. Case studies demonstrate how the opportunity may be acted on with practical guidance on how to respond to these opportunities. |
| data science wayne state: The Data Science Design Manual Steven S. Skiena, 2017-07-01 This engaging and clearly written textbook/reference provides a must-have introduction to the rapidly emerging interdisciplinary field of data science. It focuses on the principles fundamental to becoming a good data scientist and the key skills needed to build systems for collecting, analyzing, and interpreting data. The Data Science Design Manual is a source of practical insights that highlights what really matters in analyzing data, and provides an intuitive understanding of how these core concepts can be used. The book does not emphasize any particular programming language or suite of data-analysis tools, focusing instead on high-level discussion of important design principles. This easy-to-read text ideally serves the needs of undergraduate and early graduate students embarking on an “Introduction to Data Science” course. It reveals how this discipline sits at the intersection of statistics, computer science, and machine learning, with a distinct heft and character of its own. Practitioners in these and related fields will find this book perfect for self-study as well. Additional learning tools: Contains “War Stories,” offering perspectives on how data science applies in the real world Includes “Homework Problems,” providing a wide range of exercises and projects for self-study Provides a complete set of lecture slides and online video lectures at www.data-manual.com Provides “Take-Home Lessons,” emphasizing the big-picture concepts to learn from each chapter Recommends exciting “Kaggle Challenges” from the online platform Kaggle Highlights “False Starts,” revealing the subtle reasons why certain approaches fail Offers examples taken from the data science television show “The Quant Shop” (www.quant-shop.com) |
| data science wayne state: Sport Business Analytics C. Keith Harrison, Scott Bukstein, 2016-11-18 Developing and implementing a systematic analytics strategy can result in a sustainable competitive advantage within the sport business industry. This timely and relevant book provides practical strategies to collect data and then convert that data into meaningful, value-added information and actionable insights. Its primary objective is to help sport business organizations utilize data-driven decision-making to generate optimal revenue from such areas as ticket sales and corporate partnerships. To that end, the book includes in-depth case studies from such leading sports organizations as the Orlando Magic, Tampa Bay Buccaneers, Duke University, and the Aspire Group. The core purpose of sport business analytics is to convert raw data into information that enables sport business professionals to make strategic business decisions that result in improved company financial performance and a measurable and sustainable competitive advantage. Readers will learn about the role of big data and analytics in: Ticket pricing Season ticket member retention Fan engagement Sponsorship valuation Customer relationship management Digital marketing Market research Data visualization. This book examines changes in the ticketing marketplace and spotlights innovative ticketing strategies used in various sport organizations. It shows how to engage fans with social media and digital analytics, presents techniques to analyze engagement and marketing strategies, and explains how to utilize analytics to leverage fan engagement to enhance revenue for sport organizations. Filled with insightful case studies, this book benefits both sports business professionals and students. The concluding chapter on teaching sport analytics further enhances its value to academics. |
| data science wayne state: American Women of Science since 1900 [2 volumes] Tiffany K. Wayne, 2010-10-11 A comprehensive examination of American women scientists across the sciences throughout the 20th century, providing a rich historical context for understanding their achievements and the way they changed the practice of science. Much more than a Who's Who, this exhaustive two-volume encyclopedia examines the significant achievements of 20th century American women across the sciences in light of the historical and cultural factors that affected their education, employment, and research opportunities. With coverage that includes a number of scientists working today, the encyclopedia shows just how much the sciences have evolved as a professional option for women, from the dawn of the 20th century to the present. American Women of Science since 1900 focuses on 500 of the 20th century's most notable American women scientists—many overlooked, undervalued, or simply not well known. In addition, it offers individual features on 50 different scientific disciplines (Women in Astronomy, etc.), as well as essays on balancing career and family, girls and science education, and other sociocultural topics. Readers will encounter some extraordinary scientific minds at work, getting a sense of the obstacles they faced as the scientific community faced the questions of feminism and gender confronting the nation as a whole. |
| data science wayne state: Translational Neuropsychopharmacology Trevor W. Robbins, Barbara J. Sahakian, 2016-09-22 This book covers wide areas of animal and human psychopharmacology with clinical utility in the treatment of psychiatric and neurological (e.g Alzheimer's disease) disorders. The main theme is to develop a new paradigm for drug discovery that questions the claim that animal models or assays fail adequately to predict Phase 3 clinical trials. A new paradigm is advocated that stresses the importance of intermediate staging points between these extremes that depend on suitable translation of findings from animal studies to Phase 1 or Phase 2 studies utilising experimental medicine. |
| data science wayne state: Data Science for Marketing Analytics Mirza Rahim Baig, Gururajan Govindan, Vishwesh Ravi Shrimali, 2021-09-07 Turbocharge your marketing plans by making the leap from simple descriptive statistics in Excel to sophisticated predictive analytics with the Python programming language Key FeaturesUse data analytics and machine learning in a sales and marketing contextGain insights from data to make better business decisionsBuild your experience and confidence with realistic hands-on practiceBook Description Unleash the power of data to reach your marketing goals with this practical guide to data science for business. This book will help you get started on your journey to becoming a master of marketing analytics with Python. You'll work with relevant datasets and build your practical skills by tackling engaging exercises and activities that simulate real-world market analysis projects. You'll learn to think like a data scientist, build your problem-solving skills, and discover how to look at data in new ways to deliver business insights and make intelligent data-driven decisions. As well as learning how to clean, explore, and visualize data, you'll implement machine learning algorithms and build models to make predictions. As you work through the book, you'll use Python tools to analyze sales, visualize advertising data, predict revenue, address customer churn, and implement customer segmentation to understand behavior. By the end of this book, you'll have the knowledge, skills, and confidence to implement data science and machine learning techniques to better understand your marketing data and improve your decision-making. What you will learnLoad, clean, and explore sales and marketing data using pandasForm and test hypotheses using real data sets and analytics toolsVisualize patterns in customer behavior using MatplotlibUse advanced machine learning models like random forest and SVMUse various unsupervised learning algorithms for customer segmentationUse supervised learning techniques for sales predictionEvaluate and compare different models to get the best outcomesOptimize models with hyperparameter tuning and SMOTEWho this book is for This marketing book is for anyone who wants to learn how to use Python for cutting-edge marketing analytics. Whether you're a developer who wants to move into marketing, or a marketing analyst who wants to learn more sophisticated tools and techniques, this book will get you on the right path. Basic prior knowledge of Python and experience working with data will help you access this book more easily. |
| data science wayne state: Secrets of Analytical Leaders Wayne Eckerson, 2012 Imagine spending a day with top analytical leaders and asking any question you want. In this book, Wayne Eckerson illustrates analytical best practices by weaving his perspective with commentary from seven directors of analytics who unveil their secrets of success. With an innovative flair, Eckerson tackles a complex subject with clarity and insight. Each of the book's 20 chapters is a stand-alone essay on an analytical topic, yet collectively they form a concise methodology about how to implement a successful analytics program. From the Foreword by Michael Halbherr, Executive Vice President, Nokia We are living in a time of radical change. From my vantage point as head of Nokia's Location and Commerce business, I see many business and technical trends shaping our future--and all depend on a new commodity: data. In our mapping business, I see the need to evolve from a road-centric tool to something that allows people to truly understand and maneuver the complexities of a modern city. To accomplish this, we need a lot of data and ways to correlate disparate information into what we call Smart Data. Analytics is core to what we do, and how we deliver value to customers today and in the future. I recently spoke to the Nokia board about our data, and some members questioned how we could monetize this asset. Since a few members are executives in the oil industry, I told them that data is the oil of the future, and that you monetize this new resource the same way you monetize oil, by spending time and money refining it. In our case, we are refining data about people, locations, social interactions, traffic, musical preferences, and so on to bring maps to life. The analytical leaders profiled in this book demonstrate how to refine data for business gain and innovation. They play a pivotal role by bridging the worlds of business and technology. When supported by the business, they've delivered remarkable solutions that have given their organizations a competitive edge. I highly recommend this book to anyone who wants to monetize the most important resource of our time: data. It's written in language that both a CEO and a CIO can understand, and carries important lessons no matter what side of the business-technology aisle someone sits. |
| data science wayne state: The Integration of the Humanities and Arts with Sciences, Engineering, and Medicine in Higher Education National Academies of Sciences, Engineering, and Medicine, Policy and Global Affairs, Board on Higher Education and Workforce, Committee on Integrating Higher Education in the Arts, Humanities, Sciences, Engineering, and Medicine, 2018-06-21 In the United States, broad study in an array of different disciplines â€arts, humanities, science, mathematics, engineering†as well as an in-depth study within a special area of interest, have been defining characteristics of a higher education. But over time, in-depth study in a major discipline has come to dominate the curricula at many institutions. This evolution of the curriculum has been driven, in part, by increasing specialization in the academic disciplines. There is little doubt that disciplinary specialization has helped produce many of the achievement of the past century. Researchers in all academic disciplines have been able to delve more deeply into their areas of expertise, grappling with ever more specialized and fundamental problems. Yet today, many leaders, scholars, parents, and students are asking whether higher education has moved too far from its integrative tradition towards an approach heavily rooted in disciplinary silos. These silos represent what many see as an artificial separation of academic disciplines. This study reflects a growing concern that the approach to higher education that favors disciplinary specialization is poorly calibrated to the challenges and opportunities of our time. The Integration of the Humanities and Arts with Sciences, Engineering, and Medicine in Higher Education examines the evidence behind the assertion that educational programs that mutually integrate learning experiences in the humanities and arts with science, technology, engineering, mathematics, and medicine (STEMM) lead to improved educational and career outcomes for undergraduate and graduate students. It explores evidence regarding the value of integrating more STEMM curricula and labs into the academic programs of students majoring in the humanities and arts and evidence regarding the value of integrating curricula and experiences in the arts and humanities into college and university STEMM education programs. |
| data science wayne state: Basketball Data Science Paola Zuccolotto, Marica Manisera, 2020-01-03 Using data from one season of NBA games, Basketball Data Science: With Applications in R is the perfect book for anyone interested in learning and applying data analytics in basketball. Whether assessing the spatial performance of an NBA player's shots or doing an analysis of the impact of high pressure game situations on the probability of scoring, this book discusses a variety of case studies and hands-on examples using a custom R package. The codes are supplied so readers can reproduce the analyses themselves or create their own. Assuming a basic statistical knowledge, Basketball Data Science with R is suitable for students, technicians, coaches, data analysts and applied researchers. Features: One of the first books to provide statistical and data mining methods for the growing field of analytics in basketball Presents tools for modelling graphs and figures to visualize the data Includes real world case studies and examples, such as estimations of scoring probability using the Golden State Warriors as a test case Provides the source code and data so readers can do their own analyses on NBA teams and players |
| data science wayne state: Gendered Worlds Judy Root Aulette, Judith G. Wittner, 2012 In Gendered Worlds, Second Edition, authors Judy Root Aulette and Judith Wittner use the sociological imagination to explore gender relations throughout the world. They look at how concrete forms of gender, race, class, and sexual inequality operate transnationally; examine the impact of globalization on local and everyday life experiences; and identify how local actors re-imagine social possibilities, resist injustice, and work toward change. Integrating theory with empirical studies that are of particular interest to college students--including research on violence, sports, and sexuality--the authors make gender concepts genuinely interesting and accessible. They also demonstrate how students can think critically about gender, both within and beyond the classroom. Incorporating a broad range of pedagogical features, including boxed sections and end-of-chapter sections that focus on social movements, Gendered Worlds, Second Edition, is ideal for courses in sociology of gender, sociology of sex roles, and gender studies. New to this Edition * A new concluding chapter, Gender and Globalization, and an expanded Chapter 1 * A completely rewritten Chapter 4 featuring the most current research on gender and sexuality, particularly the gendered character of heterosexuality and heterosexual relationships * A reconceptualized Chapter 9 exploring illness as a function of a global division of labor by race, ethnicity, gender, and nation * More research on gender outside of the United States in every chapter * Additional coverage of race, intersectionality, masculinity, and transgender issues-- |
| data science wayne state: Performance Dashboards Wayne W. Eckerson, 2005-10-27 Tips, techniques, and trends on how to use dashboard technology to optimize business performance Business performance management is a hot new management discipline that delivers tremendous value when supported by information technology. Through case studies and industry research, this book shows how leading companies are using performance dashboards to execute strategy, optimize business processes, and improve performance. Wayne W. Eckerson (Hingham, MA) is the Director of Research for The Data Warehousing Institute (TDWI), the leading association of business intelligence and data warehousing professionals worldwide that provide high-quality, in-depth education, training, and research. He is a columnist for SearchCIO.com, DM Review, Application Development Trends, the Business Intelligence Journal, and TDWI Case Studies & Solution. |
| data science wayne state: The Pig Book Citizens Against Government Waste, 2013-09-17 The federal government wastes your tax dollars worse than a drunken sailor on shore leave. The 1984 Grace Commission uncovered that the Department of Defense spent $640 for a toilet seat and $436 for a hammer. Twenty years later things weren't much better. In 2004, Congress spent a record-breaking $22.9 billion dollars of your money on 10,656 of their pork-barrel projects. The war on terror has a lot to do with the record $413 billion in deficit spending, but it's also the result of pork over the last 18 years the likes of: - $50 million for an indoor rain forest in Iowa - $102 million to study screwworms which were long ago eradicated from American soil - $273,000 to combat goth culture in Missouri - $2.2 million to renovate the North Pole (Lucky for Santa!) - $50,000 for a tattoo removal program in California - $1 million for ornamental fish research Funny in some instances and jaw-droppingly stupid and wasteful in others, The Pig Book proves one thing about Capitol Hill: pork is king! |
| data science wayne state: Democratic Theory Giovanni Sartori, 1965 |
| data science wayne state: Slaughterhouse-Five Kurt Vonnegut, 1999-01-12 Kurt Vonnegut’s masterpiece, Slaughterhouse-Five is “a desperate, painfully honest attempt to confront the monstrous crimes of the twentieth century” (Time). Selected by the Modern Library as one of the 100 best novels of all time Slaughterhouse-Five, an American classic, is one of the world’s great antiwar books. Centering on the infamous World War II firebombing of Dresden, the novel is the result of what Kurt Vonnegut described as a twenty-three-year struggle to write a book about what he had witnessed as an American prisoner of war. It combines historical fiction, science fiction, autobiography, and satire in an account of the life of Billy Pilgrim, a barber’s son turned draftee turned optometrist turned alien abductee. As Vonnegut had, Billy experiences the destruction of Dresden as a POW. Unlike Vonnegut, he experiences time travel, or coming “unstuck in time.” An instant bestseller, Slaughterhouse-Five made Kurt Vonnegut a cult hero in American literature, a reputation that only strengthened over time, despite his being banned and censored by some libraries and schools for content and language. But it was precisely those elements of Vonnegut’s writing—the political edginess, the genre-bending inventiveness, the frank violence, the transgressive wit—that have inspired generations of readers not just to look differently at the world around them but to find the confidence to say something about it. Authors as wide-ranging as Norman Mailer, John Irving, Michael Crichton, Tim O’Brien, Margaret Atwood, Elizabeth Strout, David Sedaris, Jennifer Egan, and J. K. Rowling have all found inspiration in Vonnegut’s words. Jonathan Safran Foer has described Vonnegut as “the kind of writer who made people—young people especially—want to write.” George Saunders has declared Vonnegut to be “the great, urgent, passionate American writer of our century, who offers us . . . a model of the kind of compassionate thinking that might yet save us from ourselves.” More than fifty years after its initial publication at the height of the Vietnam War, Vonnegut’s portrayal of political disillusionment, PTSD, and postwar anxiety feels as relevant, darkly humorous, and profoundly affecting as ever, an enduring beacon through our own era’s uncertainties. |
| data science wayne state: Fuzzy Control and Modeling Hao Ying, 2000-08-15 The emerging, powerful fuzzy control paradigm has led to the worldwide success of countless commercial products and real-world applications. Fuzzy control is exceptionally practical and cost-effective due to its unique ability to accomplish tasks without knowing the mathematical model of the system, even if it is nonlinear, time varying and complex. Nevertheless, compared with the conventional control technology, most fuzzy control applications are developed in an ad hoc manner with little analytical understanding and without rigorous system analysis and design. Fuzzy Control and Modeling is the only book that establishes the analytical foundations for fuzzy control and modeling in relation to the conventional linear and nonlinear theories of control and systems. The coverage is up-to-date, comprehensive, in-depth and rigorous. Numeric examples and applications illustrate the utility of the theoretical development. Important topics discussed include: Structures of fuzzy controllers/models with respect to conventional fuzzy controllers/models Analysis of fuzzy control and modeling in relation to their classical counterparts Stability analysis of fuzzy systems and design of fuzzy control systems Sufficient and necessary conditions on fuzzy systems as universal approximators Real-time fuzzy control systems for treatment of life-critical problems in biomedicine Fuzzy Control and Modeling is a self-contained, invaluable resource for professionals and students in diverse technical fields who aspire to analytically study fuzzy control and modeling. |
| data science wayne state: Analytics, Operations, and Strategic Decision Making in the Public Sector Evans, Gerald William, Biles, William E., Bae, Ki-Hwan G., 2019-02-15 Analytics for the public sector involves the application of operations research and statistical techniques to solve various problems existing outside of the private sector. The use of analytics for the public sector results in more efficient and effective services for the clients and users of these systems. Analytics, Operations, and Strategic Decision Making in the Public Sector is an essential reference source that discusses analytics applications in various public sector organizations, and addresses the difficulties associated with the design and operation of these systems including multiple conflicting objectives, uncertainties and resulting risk, ill-structured nature, combinatorial design aspects, and scale. Featuring research on topics such as analytical modeling techniques, data mining, and statistical analysis, this book is ideally designed for academicians, educators, researchers, students, and public sector professionals including those in local, state, and federal governments; criminal justice systems; healthcare; energy and natural resources; waste management; emergency response; and the military. |
| data science wayne state: Growing Diverse STEM Communities Leyte L. Winfield, Gloria Thomas, Linette M. Watkins, Zakiya S. Wilson-Kennedy, 2020-10-22 Role of the MSEIP grant in the success of STEM undergraduate research at Queensborough Community College and beyond -- Enhancing student engagement with peer-led team learning and course-based undergraduate research experiences -- Aiming toward an effective Hispanic serving chemistry curriculum -- Computational chemistry and biology courses for undergraduates at an HBCU : cultivating a diverse computational science community -- NanoHU : a boundary-spanning education model for maximizing human and intellectual capital -- Design and implementation of a STEM student success program at Grambling State University -- The role of the ReBUILDetroit Scholars Program at Wayne State University in broadening participation in STEM -- Using scholars programs to enhance success of underrepresented students in chemistry, biomedical sciences, and STEM -- The MARC U*STAR Program at University of Maryland Baltimore County (UMBC) 1997-2018 -- Pathways to careers in science, engineering, and math -- Leadership dimensions for broadening participation in STEM : the role of HBCUs and MSIs -- Bloom where you are planted : a model for campus climate change to retain minoritzed faculty scholars in STEM fields -- Maximizing mentoring : enhancing the impact of mentoring programs and initiatives through the Center for the Advancement of Teaching and Faculty Development at Xavier University of Louisiana -- Mentors, mentors everywhere : weaving informal and formal mentoring into a robust chemical sciences mentoring quilt -- Using technology to foster peer mentoring relationships : development of a virtual peer mentorship model for broadening participation in STEM. |
| data science wayne state: Current Index to Journals in Education , 1999 |
| data science wayne state: University Physics for the Life Sciences Randall Knight, Brian Jones, Stuart Field, 2021-03-19 For courses in university physics for the life sciences. Targeting university physics for life sciences courses University Physics for the Life Sciences helps premed students understand the connection between physics and biology. By blending light calculus-based physics with biology and consistently presenting the medical application, students see the relevance and real-world application of physics to their career. Informed by Physics Education Research (PER), Knight/Jones/Field and contributor Catherine Crouch prepare life-science students for success on the MCAT by showing the connections between true biology and physics principles. Reach every student with Mastering Physics Mastering(R) empowers you to personalize learning and reach every student. This flexible digital platform combines trusted content with customizable features so you can teach your course your way. And with digital tools and assessments, students become active participants in their learning, leading to better results. Learn more about Mastering Physics. Plus, give students anytime, anywhere access with Pearson eText Pearson eText is an easy-to-use digital textbook available within Mastering. It lets students read, highlight, take notes, and review key vocabulary all in one place, even when offline. For instructors not using Mastering, Pearson eText can also be adopted on its own as the main course material. Learn more about Pearson eText or contact your rep for purchase options. |
| data science wayne state: Data Science in the Public Interest: Improving Government Performance in the Workforce Joshua D. Hawley, 2020-07-22 This book is about how new and underutilized types of big data sources can inform public policy decisions related to workforce development. Hawley describes how government is currently using data to inform decisions about the workforce at the state and local levels. He then moves beyond standardized performance metrics designed to serve federal agency requirements and discusses how government can improve data gathering and analysis to provide better, up-to-date information for government decision making. |
| data science wayne state: National Science Research Data Processing and Information Retrieval System, Hearings Before the General Subcommittee on Education....91-1, on H.R. 8809, April 29, 30, 1969 United States. Congress. House. Education and Labor, United States. Congress. House. Committee on Education and Labor. General Subcommittee on Education, 1969 |
| data science wayne state: Hark, Hark! Hear the Story of a Science Educator Jazlin Ebenezer, 2020-06-16 Hark, Hark! Hear the Story of a Science Educator highlights some compelling ideas on science teaching and learning through the author's journey and includes evolution and revolution in the growth of scientific knowledge. The book discusses views of McComas et al. and Lederman et al. on the nature of science, as well as the learning theories of Piaget (1926), Vygotsky (1978), and Marton (1981). The three theories of learning frame methods in teaching science. The author is well known in the science education research community for her groundbreaking work in student conceptions and conceptual change, particularly as related to phenomenography. Key Features: Helps science educators explore new avenues related to various innovative curricula, teaching, and learning Presents abstract learning theories, such as social constructivism in personal stories and experiences Bridges the divide between the science education community and the general public on significant ideas of science teaching and learning Uncovers relational conceptual change inquiry learning Discusses current socioscientific community-based issues-other-centeredness-through scientific investigation and engineering design challenges |
| data science wayne state: A Platform for Biomedical Discovery and Data-powered Health National Library of Medicine (U.S.). Board of Regents, 2018 |
| data science wayne state: Microsoft Excel 2010 Wayne L. Winston, 2011 An award-winning business professor and corporate consultant shares the best of his real-world experience in this practical, scenario-focused guide--fully updated for Excel 2010. |
| data science wayne state: Roundtable on Data Science Postsecondary Education National Academies of Sciences, Engineering, and Medicine, Division of Behavioral and Social Sciences and Education, Division on Engineering and Physical Sciences, Board on Science Education, Computer Science and Telecommunications Board, Committee on Applied and Theoretical Statistics, Board on Mathematical Sciences and Analytics, 2020-09-02 Established in December 2016, the National Academies of Sciences, Engineering, and Medicine's Roundtable on Data Science Postsecondary Education was charged with identifying the challenges of and highlighting best practices in postsecondary data science education. Convening quarterly for 3 years, representatives from academia, industry, and government gathered with other experts from across the nation to discuss various topics under this charge. The meetings centered on four central themes: foundations of data science; data science across the postsecondary curriculum; data science across society; and ethics and data science. This publication highlights the presentations and discussions of each meeting. |
| data science wayne state: Strategies for Fostering Inclusive Classrooms in Higher Education Jaimie Hoffman, Patrick Blessinger, Mandla Makhanya, 2019-02-04 This volume will provide educators with an understanding of challenges associated with equity and inclusion at higher education institutions globally and with evidence-based strategies for addressing the challenges associated with implementing equity and inclusion. |
| data science wayne state: Business Analytics S. Christian Albright, Wayne L. Winston, 2017 |
Data and Digital Outputs Management Plan (DDOMP)
Data and Digital Outputs Management Plan (DDOMP)
Building New Tools for Data Sharing and Reuse through a …
Jan 10, 2019 · The SEI CRA will closely link research thinking and technological innovation toward accelerating the full path of discovery-driven data use and open science. This will …
Open Data Policy and Principles - Belmont Forum
The data policy includes the following principles: Data should be: Discoverable through catalogues and search engines; Accessible as open data by default, and made available with …
Belmont Forum Adopts Open Data Principles for Environmental …
Jan 27, 2016 · Adoption of the open data policy and principles is one of five recommendations in A Place to Stand: e-Infrastructures and Data Management for Global Change Research, …
Belmont Forum Data Accessibility Statement and Policy
The DAS encourages researchers to plan for the longevity, reusability, and stability of the data attached to their research publications and results. Access to data promotes reproducibility, …
Climate-Induced Migration in Africa and Beyond: Big Data and …
CLIMB will also leverage earth observation and social media data, and combine them with survey and official statistical data. This holistic approach will allow us to analyze migration process …
Advancing Resilience in Low Income Housing Using Climate …
Jun 4, 2020 · Environmental sustainability and public health considerations will be included. Machine Learning and Big Data Analytics will be used to identify optimal disaster resilient …
Belmont Forum
What is the Belmont Forum? The Belmont Forum is an international partnership that mobilizes funding of environmental change research and accelerates its delivery to remove critical …
Waterproofing Data: Engaging Stakeholders in Sustainable Flood …
Apr 26, 2018 · Waterproofing Data investigates the governance of water-related risks, with a focus on social and cultural aspects of data practices. Typically, data flows up from local levels …
Data Management Annex (Version 1.4) - Belmont Forum
A full Data Management Plan (DMP) for an awarded Belmont Forum CRA project is a living, actively updated document that describes the data management life cycle for the data to be …
Data and Digital Outputs Management Plan (DDOMP)
Data and Digital Outputs Management Plan (DDOMP)
Building New Tools for Data Sharing and Reuse through a …
Jan 10, 2019 · The SEI CRA will closely link research thinking and technological innovation toward accelerating the full path of discovery-driven data use and open science. This will …
Open Data Policy and Principles - Belmont Forum
The data policy includes the following principles: Data should be: Discoverable through catalogues and search engines; Accessible as open data by default, and made available with …
Belmont Forum Adopts Open Data Principles for Environmental …
Jan 27, 2016 · Adoption of the open data policy and principles is one of five recommendations in A Place to Stand: e-Infrastructures and Data Management for Global Change Research, …
Belmont Forum Data Accessibility Statement and Policy
The DAS encourages researchers to plan for the longevity, reusability, and stability of the data attached to their research publications and results. Access to data promotes reproducibility, …
Climate-Induced Migration in Africa and Beyond: Big Data and …
CLIMB will also leverage earth observation and social media data, and combine them with survey and official statistical data. This holistic approach will allow us to analyze migration process …
Advancing Resilience in Low Income Housing Using Climate …
Jun 4, 2020 · Environmental sustainability and public health considerations will be included. Machine Learning and Big Data Analytics will be used to identify optimal disaster resilient …
Belmont Forum
What is the Belmont Forum? The Belmont Forum is an international partnership that mobilizes funding of environmental change research and accelerates its delivery to remove critical …
Waterproofing Data: Engaging Stakeholders in Sustainable Flood …
Apr 26, 2018 · Waterproofing Data investigates the governance of water-related risks, with a focus on social and cultural aspects of data practices. Typically, data flows up from local levels …
Data Management Annex (Version 1.4) - Belmont Forum
A full Data Management Plan (DMP) for an awarded Belmont Forum CRA project is a living, actively updated document that describes the data management life cycle for the data to be …
