Probability and Statistics for Data Science Math R Data
Availability: Outof Stock
- Item Code: 63203
- Author: Norman Matloff
- Publisher: CRC PRESS
- Edition: 1st
- Isbn : 9781138393295
- 13 EAN: 9781138393295
Probability and Statistics for Data Science: Math + R + Data covers "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.
| Book specification | |
|---|---|
| Author | Norman Matloff |
| Publisher | CRC PRESS |
| Edition | 1st |
| Isbn | 9781138393295 |
| 13 EAN | 9781138393295 |
