Probability and statistics for data science : math + R + data / Norman Matloff.
| Author/creator | Matloff, Norman S. author. |
| Format | Electronic |
| Publication | Boca Raton : CRC Press, [2020] |
| Description | 1 online resource. |
| Supplemental Content | Ebook Central |
| Subjects |
| Series | CRC Data science series CRC Data science series. UNAUTHORIZED |
| Abstract | Probability and Statistics for Data Science: Math + R + Datacovers "math stat"--distributions, expected value, estimation etc.--but takes the phrase "Data Science" in the title quite seriously: * Real datasets are used extensively. * All data analysis is supported by R coding. * Includes many Data Science applications, such as PCA, mixture distributions, random graph models, Hidden Markov models, linear and logistic regression, and neural networks. * Leads the student to think critically about the "how" and "why" of statistics, and to "see the big picture." * Not "theorem/proof"-oriented, but concepts and models are stated in a mathematically precise manner. Prerequisites are calculus, some matrix algebra, and some experience in programming. Norman Matloff is a professor of computer science at the University of California, Davis, and was formerly a statistics professor there. He is on the editorial boards of the Journal of Statistical Software and The R Journal. His book Statistical Regression and Classification: From Linear Models to Machine Learning was the recipient of the Ziegel Award for the best book reviewed in Technometrics in 2017. He is a recipient of his university's Distinguished Teaching Award. |
| Bibliography note | Includes bibliographical references and index. |
| Biographical note | Norman Matloff is a professor of computer science at the University of California, Davis, and was formerly a statistics professor there. He is on the editorial boards of the Journal of Statistical Software and The R Journal. His book Statistical Regression and Classification: From Linear Models to Machine Learning was the recipient of the Ziegel Award for the best book reviewed in Technometrics in 2017. He is a recipient of his university's Distinguished Teaching Award. |
| Source of description | Online resource; title from PDF title page (EBSCO, viewed June 26, 2019). |
| Genre/form | Electronic books. |
| Genre/form | Textbooks. |
| ISBN | 9780429401862 (electronic bk.) |
| ISBN | 0429401868 (electronic bk.) |
| ISBN | 9780429687112 (electronic bk. : EPUB) |
| ISBN | 0429687117 (electronic bk. : EPUB) |
| ISBN | 9780429687105 (electronic bk. : Mobipocket) |
| ISBN | 0429687109 (electronic bk. : Mobipocket) |
| ISBN | 9780429687129 (electronic bk. : PDF) |
| ISBN | 0429687125 (electronic bk. : PDF) |
| Stock number | 9780429401862 Taylor & Francis |
Availability
| Library | Location | Call Number | Status | Item Actions |
|---|---|---|---|---|
| Electronic Resources | Access Content Online | ✔ Available |