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About the Book
What is a data analysis? What makes for a successful data analysis? These are difficult questions that even long-time practitioners have difficulty answering. The way that we have thought about data analysis to date has been focused on the data and the statistical tools that we employ to produce results. But data analysis is about more than those things, and developing an understanding of the things "outside" the data is critical to characterizing the actual process of data analysis, the process that data analysts go through every day.
This book attempts to draw a more complete picture of the data analysis process and presents a new view about what makes for a successful data analysis. It is presented in a completely non-technical and highly readable style that should be of interest to practitioners and managers in data analysis.
About the Author
Roger D. Peng is a Professor of Statistics and Data Sciences at the University of Texas, Austin. Previously, he was Professor of Biostatistics at the Johns Hopkins Bloomberg School of Public Health. His research focuses on the development of statistical methods for addressing environmental health problems and on developing tools for doing better data analysis. He is the author of the popular book R Programming for Data Science and 10 other books on data science and statistics. He is also the co-creator of the Johns Hopkins Data Science Specialization, the Simply Statistics blog where he writes about statistics for the public, the Not So Standard Deviations podcast with Hilary Parker, and The Effort Report podcast with Elizabeth Matsui. Roger is a Fellow of the American Statistical Association and is the recipient of the Mortimer Spiegelman Award from the American Public Health Association, which honors a statistician who has made outstanding contributions to public health. He can be found on Twitter and GitHub at @rdpeng.