When would a casino stop a gambler from playing his next hand? How could a company use statistical analysis to blackball you from the job you want? Why should you worry when customer services pay attention to your needs? Beginning with examples of the mathematician who out-predicted wine buffs in determining the best vintages, and the sports scouts who now use statistics rather than intuition to pick winners, Super Crunchers exposes the hidden patterns all around us. No businessperson, academic, student, or consumer (statistically that's everyone) should make another move without getting to grips with thinking-by-numbers - the new way to be smart, savvy and statistically superior.

The approximation and the estimation of nonparametric functions by projections on an orthonormal basis of functions are useful in data analysis. This book presents series estimators defined by projections on bases of functions, they extend the estimators of densities to mixture models, deconvolution and inverse problems, to semi-parametric and nonparametric models for regressions, hazard functions and diffusions. They are estimated in the Hilbert spaces with respect to the distribution function of the regressors and their optimal rates of convergence are proved. Their mean square errors depend on the size of the basis which is consistently estimated by cross-validation. Wavelets estimators are defined and studied in the same models.The choice of the basis, with suitable parametrizations, and their estimation improve the existing methods and leads to applications to a wide class of models. The rates of convergence of the series estimators are the best among all nonparametric estimators with a great improvement in multidimensional models. Original methods are developed for the estimation in deconvolution and inverse problems. The asymptotic properties of test statistics based on the estimators are also established.

Written for anyone beginning a research project, this introductory book takes you through the process of analysing your data from start to finish. The author sets out an easy-to-use model for coding data in order to break it down into parts, and then to reassemble it to create a meaningful picture of the phenomenon under study. Full of useful advice, the book guides the reader through the last difficult integrating phase of qualitative analysis including diagramming, memoing, thinking aloud, and using one's feelings, and how to incorporate the use of software where appropriate. Ideal for third year undergraduate students, master students, postgraduates and anybody beginning a research project, the book includes examples covering a wide range of subjects - making the book useful for students across the social science disciplines. Hennie Boeije is currently an Associate Professor with the Department of Methodology and Statistics of the Faculty of Social and Behavioural Sciences at Utrecht University, The Netherlands.

This book is aimed primarily at microbiologists who are undertaking research, and who require a basic knowledge of statistics to analyse their experimental data. Computer software employing a wide range of data analysis methods is widely available to experimental scientists. The availability of this software, however, makes it even more essential that microbiologists understand the basic principles of statistics.

Statistical analysis of data can be complex with many different methods of approach, each of which applies in a particular experimental circumstance. In addition, most statistical software commercially available is complex and difficult to use. Hence, it is easy to apply an incorrect statistical method to data and to draw the wrong conclusions from an experiment.

The purpose of this book is an attempt to present the basic logic of statistics as clearly as possible and therefore, to dispel some of the myths that often surround the subject. The book is presented as a series of 2018Statnotes', many of which were originally published in the 2018Microbiologist' by the Society for Applied Microbiology, each of which deals with various topics including the nature of variables, comparing the means of two or more groups, non-parametric statistics, analysis of variance, correlating variables, and more complex methods such as multiple linear regression and factor analysis. In each case, the relevant statistical methods are illustrated with scenarios and real experimental data drawn from experiments in microbiology. The text will incorporate a glossary of the most commonly used statistical terms and a section to aid the investigator to select the most appropriate test.

Every new tractor now contains built-in sensors that collect data and stream it to cloud-based infrastructure. Seed and chemical companies are using these data, and these agribusinesses are a form of big tech alongside firms like Google and Facebook. The Immaculate Conception of Data peeks behind the secretive legal agreements surrounding agricultural big data to trace how it is used and with what consequences. Agribusinesses are among the oldest oligopoly corporations in the world, and their concentration gives them an advantage over other food system actors. Kelly Bronson explores what happens when big data get caught up in pre-existing arrangements of power. Her richly ethnographic account details the work of corporate scientists, farmers using the data, and activist "hackers" building open-source data platforms. Actors working in private and public contexts have divergent views on whom new technology is for, how it should be developed, and what kinds of agriculture it should support. Surprisingly, despite their differences, these groups share a way of speaking about data and its value for the future. Bronson calls this the immaculate conception of data, arguing that this phenomenon is a dangerous framework for imagining big data and what it might do for society. Drawing our attention to agriculture as an important new site for big tech criticism, The Immaculate Conception of Data uniquely bridges science and technology studies, critical data studies, and food studies, bringing to light salient issues related to data justice and a sustainable food system.

Numerical Methods in Environmental Data Analysis introduces environmental scientists to the numerical methods available to help answer research questions through data analysis. One challenge in data analysis is misrepresentation of datasets that are relevant directly or indirectly to the research. This book illustrates new ways of screening dataset or images for maximum utilization, introducing environmental modeling, numerical methods, and computations techniques in data analysis. Throughout the book, the author includes case studies that provide guidance on how to translate research questions into appropriate models. Individuals working with data sets or images generated from environmental monitoring centers or satellites will find this book to be a concise guide for analyzing and interpreting their data.

We think we know bullshit when we hear it, but do we?

Two science professors give us the tools to dismantle misinformation and think clearly in a world of fake news and bad data

Politicians are unconstrained by facts. Science is conducted by press release. Start-up culture elevates hype to high art. The world is awash in bullshit, and we're drowning in it.

Based on a popular course at the University of Washington, this book gives us the tools to see through the obfuscations, deliberate and careless, that dominate every realm of our lives. In this lively, provocative guide, biologist Carl Bergstrom and data scientist Jevin West show that calling out nonsense is crucial to a properly functioning social group, whether it be a circle of friends, a community of researchers, or the citizens of a nation.

Through six rules of thumb, they help us to recognize when numbers are being manipulated, to cut through the crap wherever we encounter it - even within ourselves - and learn how to give the real facts to a crystal-loving friend or climate change denier uncle.

Calling Bullshit is an indispensable handbook to the art of scepticism.

From the quality of the air we breathe to the national leaders we choose, data and statistics are a pervasive feature of daily life and daily news. But how do news, numbers and public opinion interact with each other - and with what impacts on society at large? Featuring an international roster of established and emerging scholars, this book is the first comprehensive collection of research into the little understood processes underpinning the uses/misuses of statistical information in journalism and their socio-psychological and political effects. Moving beyond the hype around "data journalism," News, Numbers and Public Opinion delves into a range of more latent, fundamental questions such as: * Is it true that most citizens and journalists do not have the necessary skills and resources to critically process and assess numbers? * How do/should journalists make sense of the increasingly data-driven world? * What strategies, formats and frames do journalists use to gather and represent different types of statistical data in their stories? * What are the socio-psychological and political effects of such data gathering and representation routines, formats and frames on the way people acquire knowledge and form attitudes? * What skills and resources do journalists and publics need to deal effectively with the influx of numbers into in daily work and life - and how can newsrooms and journalism schools meet that need? The book is a must-read for not only journalists, journalism and media scholars, statisticians and data scientists but also anybody interested in the interplay between journalism, statistics and society.

Edited by Terri D. Pigott, Ann Marie Ryan, and Charles Tocci, the purpose of this volume is to present high-quality reviews that examine change to teaching practice from a variety of perspectives and a range of disciplines with an eye toward the enormous scope of the field. Taken as a whole, this volume presents a compelling profile of the core challenges and opportunities facing those engaged in the work of changing teaching practice and those who research these efforts. Divided into four sections, the first section of this volume delves into the history and policy of changing teaching practice, the second set of chapters consider the capacity of teachers to make changes, the third set of chapters review literature examining how to change practice in numerous settings in various ways, and the final section of the volume centers on emerging issues for practice. This volume considers some of the most critical problems facing educators and scholars today: how our history shapes our present-day possibilities, how we develop the capacity of educators to change and improve practice, the innumerable aspects that can be changed, which dimensions of teaching should we prioritize, and what emerging issues will shape this work in the coming years?

Real-Time Data Analytics for Large-Scale Sensor Data covers the theory and applications of hardware platforms and architectures, the development of software methods, techniques and tools, applications, governance and adoption strategies for the use of massive sensor data in real-time data analytics. It presents the leading-edge research in the field and identifies future challenges in this fledging research area. The book captures the essence of real-time IoT based solutions that require a multidisciplinary approach for catering to on-the-fly processing, including methods for high performance stream processing, adaptively streaming adjustment, uncertainty handling, latency handling, and more.

This exciting new textbook offers an accessible, business-focused overview of the key theoretical concepts underpinning modern data analytics. It provides engaging and practical advice on using the key software tools, including SAS Visual Analytics, R and DataRobot, that are used in organisations to help make effective data-driven decisions. Combining theory with hands-on practical examples, this essential text includes cutting edge coverage of new areas of interest including social media analytics, design thinking and the ethical implications of using big data. A wealth of learning features including exercises, cases, online resources and data sets help students to develop analytic problem-solving skills. With its management perspective on analytics and its coverage of a range of popular software tools, this is an ideal essential text for upper-level undergraduate, postgraduate and MBA students. It is also ideal for practitioners wanting to understand the broader organisational context of big data analysis and to engage critically with the tools and techniques of business analytics. Accompanying online resources for this title can be found at bloomsburyonlineresources.com/business-analytics. These resources are designed to support teaching and learning when using this textbook and are available at no extra cost.

The general theme of this book is to encourage the use of relevant methodology in data mining which is or could be applied to the interplay of education, statistics and computer science to solve psychometric issues and challenges in the new generation of assessments. In addition to item response data, other data collected in the process of assessment and learning will be utilized to help solve psychometric challenges and facilitate learning and other educational applications. Process data include those collected or available for collection during the process of assessment and instructional phase such as responding sequence data, log files, the use of help features, the content of web searches, etc. Some book chapters present the general exploration of process data in large -scale assessment. Further, other chapters also address how to integrate psychometrics and learning analytics in assessment and survey, how to use data mining techniques for security and cheating detection, how to use more assessment results to facilitate student's learning and guide teacher's instructional efforts. The book includes both theoretical and methodological presentations that might guide the future in this area, as well as illustrations of efforts to implement big data analytics that might be instructive to those in the field of learning and psychometrics. The context of the effort is diverse, including K-12, higher education, financial planning, and survey utilization. It is hoped that readers can learn from different disciplines, especially those who are specialized in assessment, would be critical to expand the ideas of what we can do with data analytics for informing assessment practices.

According to a wry saying among radiologists, finding a tumour in a mammogram is like finding a snowball in a blizzard. Up to thirty percent of breast-cancer diagnoses are given to those who have no cancer at all. Medicine is subject to far more uncertainty than we commonly acknowledge. While it is portrayed a science, it can sometimes be scarily close to educated guesswork. Covering everything from the efficacy of Prozac to the regular barrage of health advice by the media, Snowball in a Blizzard is a profound meditation on why it's essential that doctors and their patients know what we don't know. The world is more complicated than we like to believe. Informed by years of frontline medical experience and filled with personal reflections, this important book is filled with counter-intuitive revelations about flawed reasoning, helpful guidance and hard-earned insight. It will change the way you view the health of yourself, your loved ones or your patients.

The Data and Analytics Playbook: Proven Methods for Governed Data and Analytic Quality explores the way in which data continues to dominate budgets, along with the varying efforts made across a variety of business enablement projects, including applications, web and mobile computing, big data analytics, and traditional data integration. The book teaches readers how to use proven methods and accelerators to break through data obstacles to provide faster, higher quality delivery of mission critical programs. Drawing upon years of practical experience, and using numerous examples and an easy to understand playbook, Lowell Fryman, Gregory Lampshire, and Dan Meers discuss a simple, proven approach to the execution of multiple data oriented activities. In addition, they present a clear set of methods to provide reliable governance, controls, risk, and exposure management for enterprise data and the programs that rely upon it. In addition, they discuss a cost-effective approach to providing sustainable governance and quality outcomes that enhance project delivery, while also ensuring ongoing controls. Example activities, templates, outputs, resources, and roles are explored, along with different organizational models in common use today and the ways they can be mapped to leverage playbook data governance throughout the organization.

Data Analytics and Data-based Decision-making are hot topics now. Big Data has entered the common parlance. Many kinds of data are generated by business, social media, machines, and more. Organizations have a choice: they can be buried under the avalanche of data, or they can do something with it to increase competitive advantage. A new field of Data Science is born, and Data Scientist has been called the sexiest job of the decade. Students across a variety of academic departments, including business, computer science, statistics, and engineering are attracted to the idea of discovering new insights and ideas from data. This is a proposal for a short and lucid book on this whole area. It is designed to provide a student with the intuition behind this evolving area, along with a solid toolset of the major data mining techniques and platforms, all within a single semester- or quarter-long course.

Biopower & data In her book BioMachtData, Sophie Reyer looks at data and the phenomenon of "dataism," the homage paid to the unlimited flow of data. She describes "dataism" as a theory that has evolved into a veritable religion, yielding not only prophecies but also commandments, such as "Increase the flow of data!" Which means, in essence, "Consume and produce!" In the process, humanity recedes into the background, and the free flow or even flood of information becomes the new value. Based on Michel Foucault's concept of biopower, Reyer develops artistic-philosophical approaches in words and verbal images - in the form of essays, monologues, dialogues, and theatrical fragments. She examines various figures of dataism, from incels to nerds and heroines. A linguistic-artistic and philosophical examination of biopower in times of unlimited data flow From data to "dataism" - in essays, experimental texts, and images A new book by Sophie Reyer, following on from the publication BioMachtTheater (2020)

A complete and comprehensive collaboration providing insight on future approaches to telephone survey methodology

Over the past fifteen years, advances in technology have transformed the field of survey methodology, from how interviews are conducted to the management and analysis of compiled data. Advances in Telephone Survey Methodology is an all--encompassing and authoritative resource that presents a theoretical, methodological, and statistical treatment of current practices while also establishing a discussion on how state--of--the--art developments in telecommunications have and will continue to revolutionize the telephone survey process.

Seventy--five prominent international researchers and practitioners from government, academic, and private sectors have collaborated on this pioneering volume to discuss basic survey techniques and introduce the future directions of the telephone survey. Concepts and findings are organized in four parts--sampling and estimation, data collection, operations, and nonresponse--equipping the reader with the needed practical applications to approach issues such as choice of target population, sample design, questionnaire construction, interviewing training, and measurement error. The book also introduces important topics that have been overlooked in previous literature, including:

The impact of mobile telephones on telephone surveys and the rising presence of mobile--only households worldwide

The design and construction of questionnaires using Computer Assisted Telephone Interviewing (CATI) software

The emerging use of wireless communication and Voice over Internet Protocol (VoIP) versus the telephone

Methods for measuring andimproving interviewer performance and productivity

Privacy, confidentiality, and respondent burden as main factors in telephone survey nonresponse

Procedures for the adjustment of nonresponse in telephone surveys

In--depth reviews of the literature presented along with a full bibliography, assembled from references throughout the world

Advances in Telephone Survey Methodology is an indispensable reference for survey researchers and practitioners in almost any discipline involving research methods such as sociology, social psychology, survey methodology, and statistics. This book also serves as an excellent text for courses and seminars on survey methods at the undergraduate and graduate levels.

"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.

"The authors discuss self-administered questionnaires, the content and format of the questionnaire, "user-friendly" questionnaires and response categories, and survey implementation. They offer excellent checklists for deciding whether or not to use a mail questionnaire, for constructing questions and response categories, for minimizing bias, for writing questionnaire specifications, for formatting and finalizing questionnaires, and for motivating respondents and writing cover letters."
--Peter Hernon, Graduate School of Library and Information Science, Simmons College

This accessible introduction to the theory and practice of longitudinal research takes the reader through the strengths and weaknesses of this kind of research, making clear: how to design a longitudinal study; how to collect data most effectively; how to make the best use of statistical techniques; and how to interpret results. Although the book provides a broad overview of the field, the focus is always on the practical issues arising out of longitudinal research. This book supplies the student with all that they need to get started and acts as a manual for dealing with opportunities and pitfalls. It is the ideal primer for this growing area of social research.

What is the most effective way for a researcher to read and analyze life-story materials? Using a new model for the classification of types of readings, Narrative Research shows readers how to read, analyze and interpret life story materials. The authors first introduce readers to four models of reading and interpreting a text: the holistic-content reading, the holistic-form reading, categorical-content reading, and categorical-form reading. They next present two complete narratives so that readers can compare the author?s interpretations against the actual text as well as try to analyze the stories on their own. The subsequent chapters provide readings, interpretations, and analyses of the narrative data from the four models. Each of the examples is highlighted by sharing with the reader some of the processes of the researcher? work, including various considerations, doubts, self-criticism, and dialogues about the narratives. Readers wanting to learn more about life story research will not only learn the tools for doing this analysis, but will be inspired to contribute their own creativity to this developing field.