This is a book containing 12 comprehensive case studies focused primarily on data manipulation, programming and computional aspects of statistical topics in authentic research applications. The aim is to provide students, researchers and faculty with exposure to the entire thought process of approaching the computations of a complete data analysis project. This differs from teaching a programming language. Instead, it illustrates how to think about programming with very concrete and complete examples. We also emphasize testing and validating computations, when and how to make them faster, and give the reader insight into how high-level programming evolves.

Each chapter works through all of the computations and programming to acquire, transform and explore the data or create the simulations. We discuss different aspects of the analysis and show results. However, readers have the opportunity to take the analyses much further, building on the core computational work described in the chapters.

Suitable for self-study or as supplementary reading in a statistical computing course, the book enables instructors to incorporate interesting problems into their courses so that students gain valuable experience and data science skills. Students learn how to acquire and work with unstructured or semistructured data as well as how to narrow down and carefully frame the questions of interest about the data.

Blending computational details with statistical and data analysis concepts, this book provides readers with an understanding of how professional data scientists think about daily computational tasks. It will improve readers’ computational reasoning of real-world data analyses.


April 21, 2015 by Chapman and Hall/CRC 
Textbook - 539 Pages - 79 B/W Illustrations 
ISBN 9781482234817 - CAT# K23014 
https://rdatasciencecases.org/