Matloff Norman. Probability and Statistics for Data Science: Math + R + Data

CRC Press, 2020. — 444 p. — (Chapman & Hall/CRC Data Science Series). — ISBN-13: 978-1-138-39329-5.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.