Author Description

<p>An essential roadmap to the application of computational statistics in contemporary data science<br></p><p>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.<br></p><p>Computational Statistics in Data Science provides complimentary access to finalized entries in the Wiley StatsRef: Statistics Reference Online compendium. Readers will also find:<br></p><ul> <li>A thorough introduction to computational statistics relevant and accessible to practitioners and researchers in a variety of data-intensive areas </li> <li>Comprehensive explorations of active topics in statistics, including big data, data stream processing, quantitative visualization, and deep learning </li></ul><p>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.<br></p>