"This is a great book for social science students. Clearly written, with many examples, Garner certainly makes learning and teaching introductory statistics a joy!" - Nikolaos Liodakis, Wilfrid Laurier University

In this "important and comprehensive" guide to statistical thinking (New Yorker), discover how data literacy is changing the world and gives you a better understanding of life’s biggest problems. Statistics are everywhere, as integral to science as they are to business, and in the popular media hundreds of times a day. In this age of big data, a basic grasp of statistical literacy is more important than ever if we want to separate the fact from the fiction, the ostentatious embellishments from the raw evidence -- and even more so if we hope to participate in the future, rather than being simple bystanders. In The Art of Statistics, world-renowned statistician David Spiegelhalter shows readers how to derive knowledge from raw data by focusing on the concepts and connections behind the math. Drawing on real world examples to introduce complex issues, he shows us how statistics can help us determine the luckiest passenger on the Titanic, whether a notorious serial killer could have been caught earlier, and if screening for ovarian cancer is beneficial. The Art of Statistics not only shows us how mathematicians have used statistical science to solve these problems -- it teaches us how we too can think like statisticians. We learn how to clarify our questions, assumptions, and expectations when approaching a problem, and -- perhaps even more importantly -- we learn how to responsibly interpret the answers we receive. Combining the incomparable insight of an expert with the playful enthusiasm of an aficionado, The Art of Statistics is the definitive guide to stats that every modern person needs.

Armed with custom software that scours the English-speaking world's new Internet blog posts every minute, hunting down the phrases "I feel" and "I am feeling, " the authors have collected over 12 million feelings since 2005, amassing an ever-growing database of human emotion that adds more than 10,000 new feelings a day. Equal parts pop culture and psychology, computer science and conceptual art, sociology and storytelling, this is no ordinary book -- with thousands of authors from all over the world sharing their uncensored emotions, it is a radical experiment in mass authorship, merging the online and offline worlds to create an indispensable handbook for anyone interested in what it's like to be human.

Based on Neil J. Salkind’s bestselling text, Statistics for People Who (Think They) Hate Statistics, this adapted Excel 2016 version presents an often intimidating and difficult subject in a way that is clear, informative, and personable. Researchers and students uncomfortable with the analysis portion of their work will appreciate the book′s unhurried pace and thorough, friendly presentation. Opening with an introduction to Excel 2016, including functions and formulas, this edition shows students how to install the Excel Data Analysis Tools option to access a host of useful analytical techniques and then walks them through various statistical procedures, beginning with correlations and graphical representation of data and ending with inferential techniques and analysis of variance. New to the Fourth Edition: A new chapter 20 dealing with large data sets using Excel functions and pivot tables, and illustrating how certain databases and other categories of functions and formulas can help make the data in big data sets easier to work with and the results more understandable. New chapter-ending exercises are included and contain a variety of levels of application. Additional TechTalks have been added to help students master Excel 2016. A new, chapter-ending Real World Stats feature shows readers how statistics is applied in the everyday world. Basic maths instruction and practice exercises for those who need to brush up on their math skills are included in the appendix.

Taken literally, the title "All of Statistics" is an exaggeration. But in spirit, the title is apt, as the book does cover a much broader range of topics than a typical introductory book on mathematical statistics. This book is for people who want to learn probability and statistics quickly. It is suitable for graduate or advanced undergraduate students in computer science, mathematics, statistics, and related disciplines. The book includes modern topics like non-parametric curve estimation, bootstrapping, and classification, topics that are usually relegated to follow-up courses. The reader is presumed to know calculus and a little linear algebra. No previous knowledge of probability and statistics is required. Statistics, data mining, and machine learning are all concerned with collecting and analysing data.

The Joy of Stats offers a reader-friendly introduction to applied statistics and quantitative analysis in the social sciences and public policy. Perfect as an undergraduate text or self-study manual, it emphasizes how to understand concepts, interpret algorithms and formulas, analyze data, and answer research questions. This brand new edition offers examples and visualizations using real-life data, a revised discussion of statistical inference, and introductory examples in R and SPSS. The third edition has been extensively reorganized with shorter chapters and closer links between concepts and formulas, while retaining useful pedagogical features including key terms, practice exercises, a math refresher, and playful inserts on "the mathematical imagination." The Joy of Stats also places a strong emphasis on learning how to write and speak clearly about data results. Supported by a companion website with data sets and additional resources, The Joy of Stats is a superb choice for introducing students to applied statistics and for refreshing and reviewing stats as a social scientist, public policy professional, or community activist.