David J. Hand – författare

Measurement is a fundamental concept that underpins almost every aspect of the modern world. It is central to the sciences, social sciences, medicine, and economics, but it affects everyday life. We measure everything - from the distance of far-off galaxies to the temperature of the air, levels of risk, political majorities, taxes, blood pressure, IQ, and weight. The history of measurement goes back to the ancient world, and its story has been one of gradual standardization. Today there are different types of measurement, levels of accuracy, and systems of units, applied in different contexts. Measurement involves notions of variability, accuracy, reliability, and error, and challenges such as the measurement of extreme values.In this Very Short Introduction, David Hand explains the common mathematical framework underlying all measurement, the main approaches to measurement, and the challenges involved. Following a brief historical account of measurement, he discusses measurement as used in the physical sciences and engineering, the life sciences and medicine, the social and behavioural sciences, economics, business, and public policy.ABOUT THE SERIES: The Very Short Introductions series from Oxford University Press contains hundreds of titles in almost every subject area. These pocket-sized books are the perfect way to get ahead in a new subject quickly. Our expert authors combine facts, analysis, perspective, new ideas, and enthusiasm to make interesting and challenging topics highly readable.

Measurement is a fundamental concept that underpins almost every aspect of the modern world. It is central to the sciences, social sciences, medicine, and economics, but it affects everyday life. We measure everything - from the distance of far-off galaxies to the temperature of the air, levels of risk, political majorities, taxes, blood pressure, IQ, and weight. The history of measurement goes back to the ancient world, and its story has been one of gradual standardization. Today there are different types of measurement, levels of accuracy, and systems of units, applied in different contexts. Measurement involves notions of variability, accuracy, reliability, and error, and challenges such as the measurement of extreme values.In this Very Short Introduction, David Hand explains the common mathematical framework underlying all measurement, the main approaches to measurement, and the challenges involved. Following a brief historical account of measurement, he discusses measurement as used in the physical sciences and engineering, the life sciences and medicine, the social and behavioural sciences, economics, business, and public policy.ABOUT THE SERIES: The Very Short Introductions series from Oxford University Press contains hundreds of titles in almost every subject area. These pocket-sized books are the perfect way to get ahead in a new subject quickly. Our expert authors combine facts, analysis, perspective, new ideas, and enthusiasm to make interesting and challenging topics highly readable.

Modern statistics is very different from the dry and dusty discipline of the popular imagination. In its place is an exciting subject which uses deep theory and powerful software tools to shed light and enable understanding. And it sheds this light on all aspects of our lives, enabling astronomers to explore the origins of the universe, archaeologists to investigate ancient civilisations, governments to understand how to benefit and improve society, and businesses to learn how best to provide goods and services. Aimed at readers with no prior mathematical knowledge, this Very Short Introduction explores and explains how statistics work, and how we can decipher them. ABOUT THE SERIES: The Very Short Introductions series from Oxford University Press contains hundreds of titles in almost every subject area. These pocket-sized books are the perfect way to get ahead in a new subject quickly. Our expert authors combine facts, analysis, perspective, new ideas, and enthusiasm to make interesting and challenging topics highly readable.

Modern statistics is very different from the dry and dusty discipline of the popular imagination. In its place is an exciting subject which uses deep theory and powerful software tools to shed light and enable understanding. And it sheds this light on all aspects of our lives, enabling astronomers to explore the origins of the universe, archaeologists to investigate ancient civilisations, governments to understand how to benefit and improve society, and businesses to learn how best to provide goods and services. Aimed at readers with no prior mathematical knowledge, this Very Short Introduction explores and explains how statistics work, and how we can decipher them. ABOUT THE SERIES: The Very Short Introductions series from Oxford University Press contains hundreds of titles in almost every subject area. These pocket-sized books are the perfect way to get ahead in a new subject quickly. Our expert authors combine facts, analysis, perspective, new ideas, and enthusiasm to make interesting and challenging topics highly readable.

Measurement is a fundamental concept that underpins almost every aspect of the modern world. It is central to the sciences, social sciences, medicine, and economics, but it affects everyday life. We measure everything - from the distance of far-off galaxies to the temperature of the air, levels of risk, political majorities, taxes, blood pressure, IQ, and weight. The history of measurement goes back to the ancient world, and its story has been one of gradual standardization. Today there are different types of measurement, levels of accuracy, and systems of units, applied in different contexts. Measurement involves notions of variability, accuracy, reliability, and error, and challenges such as the measurement of extreme values.In this Very Short Introduction, David Hand explains the common mathematical framework underlying all measurement, the main approaches to measurement, and the challenges involved. Following a brief historical account of measurement, he discusses measurement as used in the physical sciences and engineering, the life sciences and medicine, the social and behavioural sciences, economics, business, and public policy.ABOUT THE SERIES: The Very Short Introductions series from Oxford University Press contains hundreds of titles in almost every subject area. These pocket-sized books are the perfect way to get ahead in a new subject quickly. Our expert authors combine facts, analysis, perspective, new ideas, and enthusiasm to make interesting and challenging topics highly readable.

Modern statistics is very different from the dry and dusty discipline of the popular imagination. In its place is an exciting subject which uses deep theory and powerful software tools to shed light and enable understanding. And it sheds this light on all aspects of our lives, enabling astronomers to explore the origins of the universe, archaeologists to investigate ancient civilisations, governments to understand how to benefit and improve society, and businesses to learn how best to provide goods and services. Aimed at readers with no prior mathematical knowledge, this Very Short Introduction explores and explains how statistics work, and how we can decipher them. ABOUT THE SERIES: The Very Short Introductions series from Oxford University Press contains hundreds of titles in almost every subject area. These pocket-sized books are the perfect way to get ahead in a new subject quickly. Our expert authors combine facts, analysis, perspective, new ideas, and enthusiasm to make interesting and challenging topics highly readable.

This book should be of interest to statistics lecturers who want ready-made data sets complete with notes for teaching.

Repeated measures data arise when the same characteristic is measured on each case or subject at several times or under several conditions. There is a multitude of techniques available for analysing such data and in the past this has led to some confusion. This book describes the whole spectrum of approaches, beginning with very simple and crude methods, working through intermediate techniques commonly used by consultant statisticians, and concluding with more recent and advanced methods. Those covered include multiple testing, response feature analysis, univariate analysis of variance approaches, multivariate analysis of variance approaches, regression models, two-stage line models, approaches to categorical data and techniques for analysing crossover designs. The theory is illustrated with examples, using real data brought to the authors during their work as statistical consultants.

Repeated measures data arise when the same characteristic is measured on each case or subject at several times or under several conditions. There is a multitude of techniques available for analysing such data and in the past this has led to some confusion. This book describes the whole spectrum of approaches, beginning with very simple and crude methods, working through intermediate techniques commonly used by consultant statisticians, and concluding with more recent and advanced methods. Those covered include multiple testing, response feature analysis, univariate analysis of variance approaches, multivariate analysis of variance approaches, regression models, two-stage line models, approaches to categorical data and techniques for analysing crossover designs. The theory is illustrated with examples, using real data brought to the authors during their work as statistical consultants.

This book should be of interest to statistics lecturers who want ready-made data sets complete with notes for teaching.

This book presents a summary of recent work on the interface between artificial intelligence and statistics. It does this through a series of papers by different authors working in different areas of this interface. These papers are a selected and referenced subset of papers presented at the 3rd Interntional Workshop on Artificial Intelligence and Statistics, Florida, January 1991.

This text describes regression-based approaches to analyzing longitudinal and repeated measures data. It emphasizes statistical models, discusses the relationships between different approaches, and uses real data to illustrate practical applications. It uses commercially available software when it exists and illustrates the program code and output. The data appendix provides many real data sets-beyond those used for the examples-which can serve as the basis for exercises.

We live in a world of measurements. Measurements, be they of length, speed, weight, temperature, intelligence, income, endurance, greed, gross domestic product, quality of life, unemployment or skill at a job, are all numerical manifestations of the extent of some underlying attribute. They reflect the reality around us – length and weight provide examples of systems that represent clear physical attributes. At the same time, measurements also define the reality around us – psychometric tests and price inflation constitute both the definitions and the procedures for measuring these concepts. Altogether, measurements are central to our modern world and our view of it. This book explores the nature of measurement, investigating its different kinds, how these kinds should be interpreted, and the legitimacy of their statistical manipulation. The procedures through which numbers are assigned to objects are described, and measurement in psychology, medicine, the physical sciences, and the social sciences are examined in detail. The ideas of measurement are so ubiquitous that we often fail to notice them; they are concealed behind a veil of familiarity. This book lifts the corner of that veil and, in doing so, shows that there are aspects of the familiar world that are occasionally puzzling, sometimes downright extraordinary, and often more intriguing than is generally believed.

The chapters in this book describe various aspects of the application of statistical methods in finance. It will interest and attract statisticians to this area, illustrate some of the many ways that statistical tools are used in financial applications, and give some indication of problems which are still outstanding. The statisticians will be stimulated to learn more about the kinds of models and techniques outlined in the book - both the domain of finance and the science of statistics will benefit from increased awareness by statisticians of the problems, models, and techniques applied in financial applications. For this reason, extensive references are given. The level of technical detail varies between the chapters. Some present broad non-technical overviews of an area, while others describe the mathematical niceties. This illustrates both the range of possibilities available in the area for statisticians, while simultaneously giving a flavour of the different kinds of mathematical and statistical skills required. Whether you favour data analysis or mathematical manipulation, if you are a statistician there are problems in finance which are appropriate to your skills.

The author has written an accessible book presenting the central issues and placing particular emphasis on comparison, performance assessment and how to match method to application. He reviews the different approaches and guides researchers (and the huge class of users and potential users) to suitable classes of techniques. He points the way to more detailed study in "further reading" sections in each chapter.

A practical guide to making good decisions in a world of missing dataIn the era of big data, it is easy to imagine that we have all the information we need to make good decisions. But in fact the data we have are never complete, and may be only the tip of the iceberg. Just as much of the universe is composed of dark matter, invisible to us but nonetheless present, the universe of information is full of dark data that we overlook at our peril. In Dark Data, data expert David Hand takes us on a fascinating and enlightening journey into the world of the data we don't see.Dark Data explores the many ways in which we can be blind to missing data and how that can lead us to conclusions and actions that are mistaken, dangerous, or even disastrous. Examining a wealth of real-life examples, from the Challenger shuttle explosion to complex financial frauds, Hand gives us a practical taxonomy of the types of dark data that exist and the situations in which they can arise, so that we can learn to recognize and control for them. In doing so, he teaches us not only to be alert to the problems presented by the things we don’t know, but also shows how dark data can be used to our advantage, leading to greater understanding and better decisions.Today, we all make decisions using data. Dark Data shows us all how to reduce the risk of making bad ones.

A practical guide to making good decisions in a world of missing dataIn the era of big data, it is easy to imagine that we have all the information we need to make good decisions. But in fact the data we have are never complete, and may be only the tip of the iceberg. Just as much of the universe is composed of dark matter, invisible to us but nonetheless present, the universe of information is full of dark data that we overlook at our peril. In Dark Data, data expert David Hand takes us on a fascinating and enlightening journey into the world of the data we don't see.Dark Data explores the many ways in which we can be blind to missing data and how that can lead us to conclusions and actions that are mistaken, dangerous, or even disastrous. Examining a wealth of real-life examples, from the Challenger shuttle explosion to complex financial frauds, Hand gives us a practical taxonomy of the types of dark data that exist and the situations in which they can arise, so that we can learn to recognize and control for them. In doing so, he teaches us not only to be alert to the problems presented by the things we don’t know, but also shows how dark data can be used to our advantage, leading to greater understanding and better decisions.Today, we all make decisions using data. Dark Data shows us all how to reduce the risk of making bad ones.

This book should be of interest to statistics lecturers who want ready-made data sets complete with notes for teaching.

This book presents a summary of recent work on the interface between artificial intelligence and statistics. It does this through a series of papers by different authors working in different areas of this interface. These papers are a selected and referenced subset of papers presented at the 3rd Interntional Workshop on Artificial Intelligence and Statistics, Florida, January 1991.

This book presents a summary of recent work on the interface between artificial intelligence and statistics. It does this through a series of papers by different authors working in different areas of this interface. These papers are a selected and referenced subset of papers presented at the 3rd Interntional Workshop on Artificial Intelligence and Statistics, Florida, January 1991.

Since ROC curves have become ubiquitous in many application areas, the various advances have been scattered across disparate articles and texts. ROC Curves for Continuous Data is the first book solely devoted to the subject, bringing together all the relevant material to provide a clear understanding of how to analyze ROC curves.The fundamental theory of ROC curvesThe book first discusses the relationship between the ROC curve and numerous performance measures and then extends the theory into practice by describing how ROC curves are estimated. Further building on the theory, the authors present statistical tests for ROC curves and their summary statistics. They consider the impact of covariates on ROC curves, examine the important special problem of comparing two ROC curves, and cover Bayesian methods for ROC analysis. Special topicsThe text then moves on to extensions of the basic analysis to cope with more complex situations, such as the combination of multiple ROC curves and problems induced by the presence of more than two classes. Focusing on design and interpretation issues, it covers missing data, verification bias, sample size determination, the design of ROC studies, and the choice of optimum threshold from the ROC curve. The final chapter explores applications that not only illustrate some of the techniques but also demonstrate the very wide applicability of these techniques across different disciplines.With nearly 5,000 articles published to date relating to ROC analysis, the explosive interest in ROC curves and their analysis will continue in the foreseeable future. Embracing this growth of interest, this timely book will undoubtedly guide present and future users of ROC analysis.

Since ROC curves have become ubiquitous in many application areas, the various advances have been scattered across disparate articles and texts. ROC Curves for Continuous Data is the first book solely devoted to the subject, bringing together all the relevant material to provide a clear understanding of how to analyze ROC curves.The fundamenta

Statistics and data science aim to extract understanding from data and guide decision-making. However, before applying any analytical tools, we need absolute clarity about what we want to know or accomplish. Ambiguous objectives inevitably lead to mistaken conclusions and flawed actions. This book investigates the deeper challenges of formulating clear questions and matching analytical methods to those questions - issues that apply as much to elementary statistical tools as to sophisticated techniques. Rather than focusing on standard statistical misuses or data provenance issues, this work examines the critical step of ensuring your analysis actually answers the question you mean to ask.Drawing from collaborative work across finance, medicine, government, manufacturing, defence, and other fields, the book deliberately emphasises basic and familiar tools so the fundamental issues are accessible to everyone. Following John Tukey's insight about the simplest problems of data analysis, the most detailed discussions centre on averages and comparisons between distributions, though the principles apply with even greater force to advanced methods that fewer people fully understand.Key Features: * Focusses on question formulation rather than computational techniques, addressing the step that precedes all successful data analysis* Emphasises basic statistical tools (averages, comparisons) to make fundamental challenges visible to all practitioners* Contains 130 text boxes presenting essential ideas in non-technical language, creating a "e;two-in-one"e; book accessible to both mathematical and non-mathematical readers* Provides real-world examples drawn from diverse fields including finance, healthcare, government, manufacturing, and defence* Offers a deep-dive analysis of a specific comparison method to illustrate the care required for precise statistical reasoning* Presents a progression from general principles through detailed mathematical exploration to practical applications across various analytical scenariosThis book serves as an essential guide for statisticians, data scientists, researchers, and anyone who uses data to make decisions. Whether you're a practitioner seeking to improve your analytical approach or a student learning to think critically about statistical questions, this work will help you use data analytical tools more effectively and avoid the costly mistakes that arise from asking the wrong questions of your data.

Statistics and data science aim to extract understanding from data and guide decision-making. However, before applying any analytical tools, we need absolute clarity about what we want to know or accomplish. Ambiguous objectives inevitably lead to mistaken conclusions and flawed actions. This book investigates the deeper challenges of formulating clear questions and matching analytical methods to those questions - issues that apply as much to elementary statistical tools as to sophisticated techniques. Rather than focusing on standard statistical misuses or data provenance issues, this work examines the critical step of ensuring your analysis actually answers the question you mean to ask.Drawing from collaborative work across finance, medicine, government, manufacturing, defence, and other fields, the book deliberately emphasises basic and familiar tools so the fundamental issues are accessible to everyone. Following John Tukey's insight about the simplest problems of data analysis, the most detailed discussions centre on averages and comparisons between distributions, though the principles apply with even greater force to advanced methods that fewer people fully understand.Key Features: * Focusses on question formulation rather than computational techniques, addressing the step that precedes all successful data analysis* Emphasises basic statistical tools (averages, comparisons) to make fundamental challenges visible to all practitioners* Contains 130 text boxes presenting essential ideas in non-technical language, creating a "e;two-in-one"e; book accessible to both mathematical and non-mathematical readers* Provides real-world examples drawn from diverse fields including finance, healthcare, government, manufacturing, and defence* Offers a deep-dive analysis of a specific comparison method to illustrate the care required for precise statistical reasoning* Presents a progression from general principles through detailed mathematical exploration to practical applications across various analytical scenariosThis book serves as an essential guide for statisticians, data scientists, researchers, and anyone who uses data to make decisions. Whether you're a practitioner seeking to improve your analytical approach or a student learning to think critically about statistical questions, this work will help you use data analytical tools more effectively and avoid the costly mistakes that arise from asking the wrong questions of your data.

THE WELLBEING OF NATIONSMEANING, MOTIVE AND MEASUREMENT ‘A great book that adds much needed well-reasoned argument and weight to the global debate on how we better measure what is getting better and what is not. Hand and Allin chart a series of paths away from the beguiling simplicity of GDP, show where those routes began and to where they might lead. Slowly we are learning to better count what really matters in our lives. This book explains the international collaboration behind this new learning and moves it far forward.’Daniel Dorling, School of Geography and the Environment, University of Oxford How and why to use new measures of national wellbeing We have known for many years that standard measures of a country’s economic performance, like GDP and GNP, fail to tell the whole story about progress and wellbeing. The Wellbeing of Nations explores national and cross-national initiatives to build wider measures. It covers economic performance, quality of life, the state of the environment, progress, development and sustainability. The authors take the view that national wellbeing — how a country is doing — embraces all these aspects and so measures of real progress need these dimensions. This book: Presents insights drawn from a wide range of national and international developments and provides an extensive appendix of resource materials.Provides an in-depth study of the UK measuring national wellbeing programme, with which both authors continue to be involved.Explores all the main approaches to wellbeing, such as developments to the national economic accounts, Sen’s capabilities approach and the concept and measurement of sustainable development.Offers a historical perspective on progress and examines current developments in this field.The authors note that it is still early days in the practical application of these wider measures by government and business, but that use should be the main factor driving their development and production. Aspirations are high and there is much to be gained by the use of such wider measures of national wellbeing, progress and development around the world. The Wellbeing of Nations is aimed at statisticians, economists, social researchers and policy makers in government, including national and international statistics offices. Academics in development studies, economics, environmental studies, positive psychology, health research, anthropology, political studies and sociology will also benefit from this book.