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Introduction to Probability and Statistics for Data Science: with R

Introduction to Probability and Statistics for Data Science: with R

Introduction to Probability and Statistics for Data Science: with R
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Introduction to Probability and Statistics for Data Science: with R Paperback - 2024

by Rigdon, Steven E.,Fricker Jr, Ronald D.,Montgomery, Douglas C

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Cambridge University Press, 14/11/2024 00:00:01. paperback. Very Good. 4.4416 25.3807 20.5584.
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Details

  • Title Introduction to Probability and Statistics for Data Science: with R
  • Author Rigdon, Steven E.,Fricker Jr, Ronald D.,Montgomery, Douglas C
  • Binding Paperback
  • Condition Used - Very good
  • Pages 828
  • Volumes 1
  • Language ENG
  • Publisher Cambridge University Press
  • Publication date 14/11/2024 00:00:01
  • Bookseller's Inventory # mon0000300676
  • ISBN 9781009568357 / 1009568353
  • Weight 3.6 lbs (1.63 kg)
  • Dimensions 9.5 x 8 x 1.7 in (24.13 x 20.32 x 4.32 cm)
  • Size 4.4416 25.3807 20.5584
  • Category Mathematics
  • Quantity available 4

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From the publisher

Introduction to Probability and Statistics for Data Science provides a solid course in the fundamental concepts, methods and theory of statistics for students in statistics, data science, biostatistics, engineering, and physical science programs. It teaches students to understand, use, and build on modern statistical techniques for complex problems. The authors develop the methods from both an intuitive and mathematical angle, illustrating with simple examples how and why the methods work. More complicated examples, many of which incorporate data and code in R, show how the method is used in practice. Through this guidance, students get the big picture about how statistics works and can be applied. This text covers more modern topics such as regression trees, large scale hypothesis testing, bootstrapping, MCMC, time series, and fewer theoretical topics like the Cramer-Rao lower bound and the Rao-Blackwell theorem. It features more than 250 high-quality figures, 180 of which involve actual data. Data and R are code available on our website so that students can reproduce the examples and do hands-on exercises.

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