Mostly Harmless Econometrics: An Empiricist's Companion


Joshua D. Angrist - 2008
    In the modern experimentalist paradigm, these techniques address clear causal questions such as: Do smaller classes increase learning? Should wife batterers be arrested? How much does education raise wages? Mostly Harmless Econometrics shows how the basic tools of applied econometrics allow the data to speak.In addition to econometric essentials, Mostly Harmless Econometrics covers important new extensions--regression-discontinuity designs and quantile regression--as well as how to get standard errors right. Joshua Angrist and Jorn-Steffen Pischke explain why fancier econometric techniques are typically unnecessary and even dangerous. The applied econometric methods emphasized in this book are easy to use and relevant for many areas of contemporary social science.An irreverent review of econometric essentials A focus on tools that applied researchers use most Chapters on regression-discontinuity designs, quantile regression, and standard errors Many empirical examples A clear and concise resource with wide applications

Social Research Methods: Quantitative and Qualitative Approaches


W. Lawrence Neuman - 1991
    It provides dozens of new examples from actual research studies are used to provide illustrations of concepts and methods. Key terms are now called out and defined in boxes at the bottom of the pages where they appear, for easier study and review. In chapter 1, there are now separate descriptions and examples of the steps in the research process for quantitative and qualitative approaches, to underscore some of the fundamental differences. Chapter 2 has new discussions of participatory action research, instrumental and reflexive knowledge, the various audiences for social research findings, and researcher autonomy when research is commissioned. The discussion of social theories in Chapter 3 now covers levels of abstraction, and relationships among concepts

Introduction to Algorithms


Thomas H. Cormen - 1989
    Each chapter is relatively self-contained and can be used as a unit of study. The algorithms are described in English and in a pseudocode designed to be readable by anyone who has done a little programming. The explanations have been kept elementary without sacrificing depth of coverage or mathematical rigor.

Data Smart: Using Data Science to Transform Information into Insight


John W. Foreman - 2013
    Major retailers are predicting everything from when their customers are pregnant to when they want a new pair of Chuck Taylors. It's a brave new world where seemingly meaningless data can be transformed into valuable insight to drive smart business decisions.But how does one exactly do data science? Do you have to hire one of these priests of the dark arts, the "data scientist," to extract this gold from your data? Nope.Data science is little more than using straight-forward steps to process raw data into actionable insight. And in Data Smart, author and data scientist John Foreman will show you how that's done within the familiar environment of a spreadsheet. Why a spreadsheet? It's comfortable! You get to look at the data every step of the way, building confidence as you learn the tricks of the trade. Plus, spreadsheets are a vendor-neutral place to learn data science without the hype. But don't let the Excel sheets fool you. This is a book for those serious about learning the analytic techniques, the math and the magic, behind big data.Each chapter will cover a different technique in a spreadsheet so you can follow along: - Mathematical optimization, including non-linear programming and genetic algorithms- Clustering via k-means, spherical k-means, and graph modularity- Data mining in graphs, such as outlier detection- Supervised AI through logistic regression, ensemble models, and bag-of-words models- Forecasting, seasonal adjustments, and prediction intervals through monte carlo simulation- Moving from spreadsheets into the R programming languageYou get your hands dirty as you work alongside John through each technique. But never fear, the topics are readily applicable and the author laces humor throughout. You'll even learn what a dead squirrel has to do with optimization modeling, which you no doubt are dying to know.

The Elements of Statistical Learning: Data Mining, Inference, and Prediction


Trevor Hastie - 2001
    With it has come vast amounts of data in a variety of fields such as medicine, biology, finance, and marketing. The challenge of understanding these data has led to the development of new tools in the field of statistics, and spawned new areas such as data mining, machine learning, and bioinformatics. Many of these tools have common underpinnings but are often expressed with different terminology. This book describes the important ideas in these areas in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of color graphics. It should be a valuable resource for statisticians and anyone interested in data mining in science or industry. The book's coverage is broad, from supervised learning (prediction) to unsupervised learning. The many topics include neural networks, support vector machines, classification trees and boosting—the first comprehensive treatment of this topic in any book. Trevor Hastie, Robert Tibshirani, and Jerome Friedman are professors of statistics at Stanford University. They are prominent researchers in this area: Hastie and Tibshirani developed generalized additive models and wrote a popular book of that title. Hastie wrote much of the statistical modeling software in S-PLUS and invented principal curves and surfaces. Tibshirani proposed the Lasso and is co-author of the very successful An Introduction to the Bootstrap. Friedman is the co-inventor of many data-mining tools including CART, MARS, and projection pursuit.

Diffusion of Innovations


Everett M. Rogers - 1982
    It has sold 30,000 copies in each edition and will continue to reach a huge academic audience.In this renowned book, Everett M. Rogers, professor and chair of the Department of Communication & Journalism at the University of New Mexico, explains how new ideas spread via communication channels over time. Such innovations are initially perceived as uncertain and even risky. To overcome this uncertainty, most people seek out others like themselves who have already adopted the new idea. Thus the diffusion process consists of a few individuals who first adopt an innovation, then spread the word among their circle of acquaintances--a process which typically takes months or years. But there are exceptions: use of the Internet in the 1990s, for example, may have spread more rapidly than any other innovation in the history of humankind. Furthermore, the Internet is changing the very nature of diffusion by decreasing the importance of physical distance between people. The fifth edition addresses the spread of the Internet, and how it has transformed the way human beings communicate and adopt new ideas.

The World Is Flat: A Brief History of the Twenty-first Century


Thomas L. Friedman - 2005
    With his inimitable ability to translate complex foreign policy and economic issues, Friedman explains how the flattening of the world happened at the dawn of the 21st century; what it means to countries, companies, communities and individuals; and how governments and societies can, and must, adapt.

The Language Instinct: How the Mind Creates Language


Steven Pinker - 1994
    With deft use of examples of humor and wordplay, Steven Pinker weaves our vast knowledge of language into a compelling story: language is a human instinct, wired into our brains by evolution. The Language Instinct received the William James Book Prize from the American Psychological Association and the Public Interest Award from the Linguistics Society of America. This edition includes an update on advances in the science of language since The Language Instinct was first published.

Naked Statistics: Stripping the Dread from the Data


Charles Wheelan - 2012
    How can we catch schools that cheat on standardized tests? How does Netflix know which movies you’ll like? What is causing the rising incidence of autism? As best-selling author Charles Wheelan shows us in Naked Statistics, the right data and a few well-chosen statistical tools can help us answer these questions and more.For those who slept through Stats 101, this book is a lifesaver. Wheelan strips away the arcane and technical details and focuses on the underlying intuition that drives statistical analysis. He clarifies key concepts such as inference, correlation, and regression analysis, reveals how biased or careless parties can manipulate or misrepresent data, and shows us how brilliant and creative researchers are exploiting the valuable data from natural experiments to tackle thorny questions.And in Wheelan’s trademark style, there’s not a dull page in sight. You’ll encounter clever Schlitz Beer marketers leveraging basic probability, an International Sausage Festival illuminating the tenets of the central limit theorem, and a head-scratching choice from the famous game show Let’s Make a Deal—and you’ll come away with insights each time. With the wit, accessibility, and sheer fun that turned Naked Economics into a bestseller, Wheelan defies the odds yet again by bringing another essential, formerly unglamorous discipline to life.

How Children Develop


Robert S. Siegler - 2002
    In its first edition, this highly anticipated textbook for the topically-organized child development course provided a fresh, non-encyclopedic approach, offering the latest, straight-from-the-research understanding of child development without overwhelming the student with inessential detail.The new edition brings those hallmark features forward, again providing a thoroughly contemporary, streamlined introduction to the study of child development that emphasizes fundamental principles, enduring themes, and important recent studies.  Student-friendly pedagogy, a new chapter on gender, and an enhanced media and supplements package further enrich this accessible, engaging, and informative text.

Kuby Immunology


Judy A. Owen - 2012
    The new edition is thoroughly updated, including most notably a new chapter on innate immunity, a capstone chapter on immune responses in time and space, and many new focus boxes drawing attention to exciting clinical, evolutionary, or experimental connections that help bring the material to life.See what's in the LaunchPad

Generation Me: Why Today's Young Americans Are More Confident, Assertive, Entitled--and More Miserable Than Ever Before


Jean M. Twenge - 2006
    In this provocative new book, headline-making psychologist and social commentator Dr. Jean Twenge explores why the young people she calls "Generation Me" -- those born in the 1970s, 1980s, and 1990s -- are tolerant, confident, open-minded, and ambitious but also cynical, depressed, lonely, and anxious.Herself a member of Generation Me, Dr. Twenge uses findings from the largest intergenerational research study ever conducted -- with data from 1.3 million respondents spanning six decades -- to reveal how profoundly different today's young adults are. Here are the often shocking truths about this generation, including dramatic differences in sexual behavior, as well as controversial predictions about what the future holds for them and society as a whole. Her often humorous, eyebrow-raising stories about real people vividly bring to life the hopes and dreams, disappointments and challenges of Generation Me.GenMe has created a profound shift in the American character, changing what it means to be an individual in today's society. The collision of this generation's entitled self-focus and today's competitive marketplace will create one of the most daunting challenges of the new century. Engaging, controversial, prescriptive, funny, "Generation Me" will give Boomers new insight into their offspring, and help those in their teens, 20s, and 30s finally make sense of themselves and their goals and find their road to happiness.

Data Science for Business: What you need to know about data mining and data-analytic thinking


Foster Provost - 2013
    This guide also helps you understand the many data-mining techniques in use today.Based on an MBA course Provost has taught at New York University over the past ten years, Data Science for Business provides examples of real-world business problems to illustrate these principles. You’ll not only learn how to improve communication between business stakeholders and data scientists, but also how participate intelligently in your company’s data science projects. You’ll also discover how to think data-analytically, and fully appreciate how data science methods can support business decision-making.Understand how data science fits in your organization—and how you can use it for competitive advantageTreat data as a business asset that requires careful investment if you’re to gain real valueApproach business problems data-analytically, using the data-mining process to gather good data in the most appropriate wayLearn general concepts for actually extracting knowledge from dataApply data science principles when interviewing data science job candidates

Orality and Literacy: The Technologizing of the Word


Walter J. Ong - 1982
    Ong offers fascinating insights into oral genres across the globe and through time, and examines the rise of abstract philosophical and scientific thinking. He considers the impact of orality-literacy studies not only on literary criticism and theory but on our very understanding of what it is to be a human being, conscious of self and other.This is a book no reader, writer or speaker should be without.

How to Take Smart Notes: One Simple Technique to Boost Writing, Learning and Thinking – for Students, Academics and Nonfiction Book Writers


Sönke Ahrens - 2017
    This book helps students, academics and nonfiction writers to get more done, write intelligent texts and learn for the long run. It teaches you how to take smart notes and ensure they bring you and your projects forward. The Take Smart Notes principle is based on established psychological insight and draws from a tried and tested note-taking-technique. This is the first comprehensive guide and description of this system in English, and not only does it explain how it works, but also why. It suits students and academics in the social sciences and humanities, nonfiction writers and others who are in the business of reading, thinking and writing. Instead of wasting your time searching for notes, quotes or references, you can focus on what really counts: thinking, understanding and developing new ideas in writing. It does not matter if you prefer taking notes with pen and paper or on a computer, be it Windows, Mac or Linux. And you can start right away.