Statistical methods are a key part of data science, yet few data scientists have formal statistical training. Courses and books on basic statistics rarely cover the topic from a data science perspective. The second edition of this practical guide-now including examples in Python as well as R-explains how to apply various statistical methods to data science, tells you how to avoid their misuse, …
This fully updated second edition offers an advanced introduction to quantitative methods that focuses on why and how to conduct research that contributes to social justice. Includes Appendix & Index
This book presents a template for a research proposal and explains how to conceptualize and fill in every section. Interdisciplinary research examples draw on current events and social justice issues. Glossary : page 269-285. Bibliography : page 287-301. Index : page 303-321.
Effective visualization is the best way to communicate information from the increasingly large and complex datasets in the natural and social sciences. But with the increasing power of visualization software today, scientists, engineers, and business analysts often have to navigate a bewildering array of visualization choices and options. This practical book takes you through many commonly enco…
In this book, you'll find 54 hands-on descriptions that help you do the key methods used in service design. These methods include instructions, guidelines, and tips-and-tricks for activities within research, ideation, prototyping, and facilitation. This is the print version of the method companion to the book This Is Service Design Doing (#TiSDD). It includes the same content that you can find …
A key component of data science is statistics and machine learning, but only a small proportion of data scientists are actually trained as statisticians. This concise guide illustrates how to apply statistical concepts essential to data science, with advice on how to avoid their misuse. Many courses and books teach basic statistics, but rarely from a data science perspective. And while many dat…
Become an expert in Bayesian Machine Learning methods using R and apply them to solve real-world big data problems About This Book * Understand the principles of Bayesian Inference with less mathematical equations * Learn state-of-the art Machine Learning methods * Familiarize yourself with the recent advances in Deep Learning and Big Data frameworks with this step-by-step guide Who This Book I…