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SRG Sites > NewTechReview > News > Probability and Statistics for Data Science: Math + R + Data, 1st Edition from CRC Press
Probability and Statistics for Data Science: Math + R + Data, 1st Edition from CRC Press
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Probability and Statistics for Data Science: Math + R + Data, 1st Edition from CRC PressCRC Press has published Probability and Statistics for Data Science: Math + R + Data, 1st Edition.

Probability and Statistics for Data Science: Math + R + Data covers "math stat"ódistributions, expected value, estimation etc.óbut 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.

For more information, visit:
* Amazon: https://amzn.to/2XBQcCg
* Website: crcpress.com
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