"Now fully updated for "big data" analytics and the newest applications, Even You Can Learn Statistics and Analytics, Third Edition is the practical, up-to-date introduction to statistics and analytics -- for everyone! One easy step at a time, you'll learn all the statistical techniques you'll need for finance, marketing, quality, science, social science, or anything else. Simple jargon-free explanations help you understand every technique, and realistic examples and worked problems give you all the hands-on practice you'll need. This edition contains more practical examples than ever -- all updated for the newest versions of Microsoft Excel. You'll find downloadable practice files, templates, data sets, and sample models -- including complete solutions you can put right to work in business, school, or anywhere else."--Publisher's description.
This edition delivers new examples, more detailed problems and sample solutions, plus an all-new chapter on powerful multiple regression techniques. Hate math? No sweat. You’ll be amazed at how little you need. Like math?
After introducing the theory, the book covers the analysis of contingency tables, t-tests, ANOVAs and regression. Bayesian statistics are covered at the end of the book.
A Guide for Everyone Who Has Ever Been Afraid of Statistics, Enhanced Edition David M. Levine, David F. Stephan. Acknowledgments We would especially like to thank the staff at Financial Times/Pearson: Jim Boyd for making this book a ...
The Book of R is a comprehensive, beginner-friendly guide to R, the world’s most popular programming language for statistical analysis.
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.
This book presents some of the most important modeling and prediction techniques, along with relevant applications.
Now even more indispensable in our data-driven world than it was when first published, How to Lie with Statistics is the book that generations of readers have relied on to keep from being fooled.
Convergence rates of posterior distributions. The Annals of Statistics 28 500–531. GILKs, W. R., RICHARDSON, S. and SPIEGELHALTER, D. J. (1998). Markov Chain Monte Carlo in Practice. Chapman & Hall. GRIMMETT, G. and STIRZAKER, D.
With this book, you’ll learn: Why exploratory data analysis is a key preliminary step in data science How random sampling can reduce bias and yield a higher quality dataset, even with big data How the principles of experimental design ...
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.