In Computational Statistics in Data Science, a team of distinguished mathematicians and statisticians delivers an expert compilation of concepts, theories, techniques, and practices in computational statistics for readers who seek a single, standalone sourcebook on statistics in contemporary data science. The book contains multiple sections devoted to key, specific areas in computational statistics, offering modern and accessible presentations of up-to-date techniques.

Computational Statistics in Data Science provides complimentary access to finalized entries in the Wiley StatsRef: Statistics Reference Online compendium. Readers will also find:

A thorough introduction to computational statistics relevant and accessible to practitioners and researchers in a variety of data-intensive areas
Comprehensive explorations of active topics in statistics, including big data, data stream processing, quantitative visualization, and deep learning

Perfect for researchers and scholars working in any field requiring intermediate and advanced computational statistics techniques, Computational Statistics in Data Science will also earn a place in the libraries of scholars researching and developing computational data-scientific technologies and statistical graphics.

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Yes, you can access Computational Statistics in Data Science by Walter W. Piegorsch, Richard A. Levine, Hao Helen Zhang, Thomas C. M. Lee, Walter W. Piegorsch,Richard A. Levine,Hao Helen Zhang,Thomas C. M. Lee in PDF and/or ePUB format, as well as other popular books in Mathematics & Computer Science General. We have over one million books available in our catalogue for you to explore.