Courses and books on basic statistics rarely cover the topic from a data science perspective. This practical guide explains how to apply various statistical methods to data science, tells you how to avoid their misuse, and gives you advice on what's important and what's not.Many data science resources incorporate statistical methods but lack a deeper statistical perspective. If you're familiar with the R programming language, and have some exposure to statistics, this quick reference bridges the gap in an accessible, readable format.With this book, you'll learn:Why exploratory data analysis is a key preliminary step in data scienceHow random sampling can reduce bias and yield a higher quality dataset, even with big dataHow the principles of experimental design yield definitive answers to questionsHow to use regression to estimate outcomes and detect anomaliesKey classification techniques for predicting which categories a record belongs toStatistical machine learning methods that "learn" from dataUnsupervised learning methods for extracting meaning from unlabeled data

    The science of complexity studies how single elements, such as a species or a stock, spontaneously organize into complicated structures like ecosystems and economies; stars become galaxies, and snowflakes avalanches almost as if these systems were obeying a hidden yearning for order. Drawing from diverse fields, scientific luminaries such as Nobel Laureates Murray Gell-Mann and Kenneth Arrow are studying complexity at a think tank called The Santa Fe Institute. The revolutionary new discoveries researchers have made there could change the face of every science from biology to cosmology to economics. M. Mitchell Waldrop's groundbreaking bestseller takes readers into the hearts and minds of these scientists to tell the story behind this scientific revolution as it unfolds.

    The New York Times bestseller that introduced the business world to a future that s already here -- now in paperback with a new chapter about Long Tail Marketing and a new epilogue.Winner of the Gerald Loeb Award for Best Business Book of the Year.In the most important business book since The Tipping Point, Chris Anderson shows how the future of commerce and culture isn t in hits, the high-volume head of a traditional demand curve, but in what used to be regarded as misses -- the endlessly long tail of that same curve.

    So wrong that a chimpanzee choosing answers at random will consistently outguess teachers, journalists, Nobel laureates, and investment bankers.In Factfulness, Professor of International Health and global TED phenomenon Hans Rosling, together with his two long-time collaborators, Anna and Ola, offers a radical new explanation of why this happens. They reveal the ten instincts that distort our perspective—from our tendency to divide the world into two camps (usually some version of us and them) to the way we consume media (where fear rules) to how we perceive progress (believing that most things are getting worse).Our problem is that we don’t know what we don’t know, and even our guesses are informed by unconscious and predictable biases.It turns out that the world, for all its imperfections, is in a much better state than we might think. That doesn’t mean there aren’t real concerns. But when we worry about everything all the time instead of embracing a worldview based on facts, we can lose our ability to focus on the things that threaten us most.Inspiring and revelatory, filled with lively anecdotes and moving stories, Factfulness is an urgent and essential book that will change the way you see the world and empower you to respond to the crises and opportunities of the future.

    The presentation stresses analytical methods, concrete examples, and geometric intuition. A unique feature of the book is its emphasis on applications. These include mechanical vibrations, lasers, biological rhythms, superconducting circuits, insect outbreaks, chemical oscillators, genetic control systems, chaotic waterwheels, and even a technique for using chaos to send secret messages. In each case, the scientific background is explained at an elementary level and closely integrated with mathematical theory.About the Author:Steven Strogatz is in the Center for Applied Mathematics and the Department of Theoretical and Applied Mathematics at Cornell University. Since receiving his Ph.D. from Harvard university in 1986, Professor Strogatz has been honored with several awards, including the E.M. Baker Award for Excellence, the highest teaching award given by MIT.

    Its techniques are widely applied in engineering, science, finance, and commerce. This book is designed for a short course on machine learning. It is a short course, not a hurried course. From over a decade of teaching this material, we have distilled what we believe to be the core topics that every student of the subject should know. We chose the title `learning from data' that faithfully describes what the subject is about, and made it a point to cover the topics in a story-like fashion. Our hope is that the reader can learn all the fundamentals of the subject by reading the book cover to cover. ---- Learning from data has distinct theoretical and practical tracks. In this book, we balance the theoretical and the practical, the mathematical and the heuristic. Our criterion for inclusion is relevance. Theory that establishes the conceptual framework for learning is included, and so are heuristics that impact the performance of real learning systems. ---- Learning from data is a very dynamic field. Some of the hot techniques and theories at times become just fads, and others gain traction and become part of the field. What we have emphasized in this book are the necessary fundamentals that give any student of learning from data a solid foundation, and enable him or her to venture out and explore further techniques and theories, or perhaps to contribute their own. ---- The authors are professors at California Institute of Technology (Caltech), Rensselaer Polytechnic Institute (RPI), and National Taiwan University (NTU), where this book is the main text for their popular courses on machine learning. The authors also consult extensively with financial and commercial companies on machine learning applications, and have led winning teams in machine learning competitions.

    Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them all—IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools.Working scientists and data crunchers familiar with reading and writing Python code will find this comprehensive desk reference ideal for tackling day-to-day issues: manipulating, transforming, and cleaning data; visualizing different types of data; and using data to build statistical or machine learning models. Quite simply, this is the must-have reference for scientific computing in Python.With this handbook, you’ll learn how to use: * IPython and Jupyter: provide computational environments for data scientists using Python * NumPy: includes the ndarray for efficient storage and manipulation of dense data arrays in Python * Pandas: features the DataFrame for efficient storage and manipulation of labeled/columnar data in Python * Matplotlib: includes capabilities for a flexible range of data visualizations in Python * Scikit-Learn: for efficient and clean Python implementations of the most important and established machine learning algorithms

    Here is a complete library of dimensional modeling techniques-- the most comprehensive collection ever written. Greatly expanded to cover both basic and advanced techniques for optimizing data warehouse design, this second edition to Ralph Kimball's classic guide is more than sixty percent updated.The authors begin with fundamental design recommendations and gradually progress step-by-step through increasingly complex scenarios. Clear-cut guidelines for designing dimensional models are illustrated using real-world data warehouse case studies drawn from a variety of business application areas and industries, including:* Retail sales and e-commerce* Inventory management* Procurement* Order management* Customer relationship management (CRM)* Human resources management* Accounting* Financial services* Telecommunications and utilities* Education* Transportation* Health care and insuranceBy the end of the book, you will have mastered the full range of powerful techniques for designing dimensional databases that are easy to understand and provide fast query response. You will also learn how to create an architected framework that integrates the distributed data warehouse using standardized dimensions and facts.This book is also available as part of the Kimball's Data Warehouse Toolkit Classics Box Set (ISBN: 9780470479575) with the following 3 books:The Data Warehouse Toolkit, 2nd Edition (9780471200246)The Data Warehouse Lifecycle Toolkit, 2nd Edition (9780470149775)The Data Warehouse ETL Toolkit (9780764567575)

    Tricks of the Trade will help students learn how to think about research projects. Assisted by Becker's sage advice, students can make better sense of their research and simultaneously generate fresh ideas on where to look next for new data. The tricks cover four broad areas of social science: the creation of the "imagery" to guide research; methods of "sampling" to generate maximum variety in the data; the development of "concepts" to organize findings; and the use of "logical" methods to explore systematically the implications of what is found. Becker's advice ranges from simple tricks such as changing an interview question from "Why?" to "How?" (as a way of getting people to talk without asking for a justification) to more technical tricks such as how to manipulate truth tables. Becker has extracted these tricks from a variety of fields such as art history, anthropology, sociology, literature, and philosophy; and his dazzling variety of references ranges from James Agee to Ludwig Wittgenstein. Becker finds the common principles that lie behind good social science work, principles that apply to both quantitative and qualitative research. He offers practical advice, ideas students can apply to their data with the confidence that they will return with something they hadn't thought of before. Like Writing for Social Scientists, Tricks of the Trade will bring aid and comfort to generations of students. Written in the informal, accessible style for which Becker is known, this book will be an essential resource for students in a wide variety of fields."An instant classic. . . . Becker's stories and reflections make a great book, one that will find its way into the hands of a great many social scientists, and as with everything he writes, it is lively and accessible, a joy to read."—Charles Ragin, Northwestern University

    In The Anatomy of Violence, Raine dissects the criminal mind with a fascinating, readable, and far-reaching scientific journey into the body of evidence that reveals the brain to be a key culprit in crime causation.  Raine documents from genetic research that the seeds of sin are sown early in life, giving rise to abnormal physiological functioning that cultivates crime. Drawing on classical case studies of well-known killers in history—including Richard Speck, Ted Kaczynski, and Henry Lee Lucas—Raine illustrates how impairments to brain areas controlling our ability to experience fear, make good decisions, and feel guilt predispose us to violence. He contends that killers can actually be coldhearted: something as simple as a low resting heart rate can give rise to violence. But arguing that biology is not destiny, he also sketches out provocative new biosocial treatment approaches that can change the brain and prevent violence.  Finally, Raine tackles the thorny legal and ethical dilemmas posed by his research, visualizing a futuristic brave new world where our increasing ability to identify violent offenders early in life might shape crime-prevention policies, for good and bad. Will we sacrifice our notions of privacy and civil rights to identify children as potential killers in the hopes of helping both offenders and victims? How should we punish individuals with little to no control over their violent behavior? And should parenting require a license? The Anatomy of Violence offers a revolutionary appraisal of our understanding of criminal offending, while also raising provocative questions that challenge our core human values of free will, responsibility, and punishment.From the Hardcover edition.

    Now he's sharing his collection of antipatterns--the most common errors he's identified in those thousands of requests for help. Most developers aren't SQL experts, and most of the SQL that gets used is inefficient, hard to maintain, and sometimes just plain wrong. This book shows you all the common mistakes, and then leads you through the best fixes. What's more, it shows you what's behind these fixes, so you'll learn a lot about relational databases along the way. Each chapter in this book helps you identify, explain, and correct a unique and dangerous antipattern. The four parts of the book group the anti​patterns in terms of logical database design, physical database design, queries, and application development. The chances are good that your application's database layer already contains problems such as Index Shotgun, Keyless Entry, Fear of the Unknown, and Spaghetti Query. This book will help you and your team find them. Even better, it will also show you how to fix them, and how to avoid these and other problems in the future. SQL Antipatterns gives you a rare glimpse into an SQL expert's playbook. Now you can stamp out these common database errors once and for all. Whatever platform or programming language you use, whether you're a junior programmer or a Ph.D., SQL Antipatterns will show you how to design and build databases, how to write better database queries, and how to integrate SQL programming with your application like an expert. You'll also learn the best and most current technology for full-text search, how to design code that is resistant to SQL injection attacks, and other techniques for success.

    It’s fully updated to match the latest sociology teaching, research and developments to support your learning about sociology today.Brought to you by a team of experts, Collins Sociology Themes and Perspectives is written by Michael Haralambos and Martin Holborn and has supported over one million sociology students worldwide.Build your understanding through clear and comprehensive explanations and apply your knowledge with contextualised examples and research. Stay relevant with the most up-to-date developments, empirical studies and theories while consolidating your learning with quick-reference conclusions and summaries at the end of each chapter. Bring sociology alive with full-colour explanations and photos.New topics covered in this sociology book include globalisation, the Arab Spring, the possible decline of US power, UK Coalition policies, environmental sociology, new media, the financial crash and recession, network society, crime and deviance sociology, victimology – and many more! For additional resources, try the Haralambos and Holborn AQA A-level Sociology Themes and Perspectives Year 1 and AS (9780008242770) and Year 2 (9780008242787) sociology textbooks written specifically for the 2015 AQA specification.Contents:• Chapter 1: Stratification, class and inequality• Chapter 2: Sex and gender• Chapter 3: ‘Race’, ethnicity and nationality• Chapter 4: Poverty, social exclusion and the welfare state• Chapter 5: Health, medicine and the body• Chapter 6: Crime and deviance• Chapter 7: Religion• Chapter 8: Families, households and personal life• Chapter 9: Power, politics and the state• Chapter 10: Education• Chapter 11: Culture, socialisation and identity• Chapter 12: The mass media• Chapter 13: Age and the life course• Chapter 14: Methodology• Chapter 15: Sociological theory

    William Mitchell makes extensive use of practical examples and illustrations in a technically well-grounded yet accessible examination of architecture and urbanism in the context of the digital telecommunications revolution, the ongoing miniaturization of electronics, the commodification of bits, and the growing domination of software over materialized form.

    In this new book, Wurman examines how the Internet, desktop computing, and advances in digital technology have not simply enhanced access to information, but in fact have changed the way we live and work. In examining the sources of information anxiety, Wurman takes an in-depth look at how technological advances can hinder understanding and influence how business is conducted.

    In How Not to Be Wrong, Jordan Ellenberg shows us how terribly limiting this view is: Math isn’t confined to abstract incidents that never occur in real life, but rather touches everything we do—the whole world is shot through with it.Math allows us to see the hidden structures underneath the messy and chaotic surface of our world. It’s a science of not being wrong, hammered out by centuries of hard work and argument. Armed with the tools of mathematics, we can see through to the true meaning of information we take for granted: How early should you get to the airport? What does “public opinion” really represent? Why do tall parents have shorter children? Who really won Florida in 2000? And how likely are you, really, to develop cancer?How Not to Be Wrong presents the surprising revelations behind all of these questions and many more, using the mathematician’s method of analyzing life and exposing the hard-won insights of the academic community to the layman—minus the jargon. Ellenberg chases mathematical threads through a vast range of time and space, from the everyday to the cosmic, encountering, among other things, baseball, Reaganomics, daring lottery schemes, Voltaire, the replicability crisis in psychology, Italian Renaissance painting, artificial languages, the development of non-Euclidean geometry, the coming obesity apocalypse, Antonin Scalia’s views on crime and punishment, the psychology of slime molds, what Facebook can and can’t figure out about you, and the existence of God.Ellenberg pulls from history as well as from the latest theoretical developments to provide those not trained in math with the knowledge they need. Math, as Ellenberg says, is “an atomic-powered prosthesis that you attach to your common sense, vastly multiplying its reach and strength.” With the tools of mathematics in hand, you can understand the world in a deeper, more meaningful way. How Not to Be Wrong will show you how.