Introduction to Probability and Statistics for Data Science with R
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Description
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…
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Key features
- Provides a solid course in the fundamental concepts, methods and theory of statistics for a wide array of students in statistics, data science, biostatistics, engineering, and physical science programs
- Teaches students to understand, use, and build on modern statistical techniques for complex problems
- Develops statistical methods from both an intuitive and mathematical angle. Simple examples illustrate how and why the methods work, while more complicated examples show how the method is used in practice
- All theory is developed with immediate and direct applications
- Covers modern topics, like regression trees, large scale hypothesis testing, bootstrapping, MCMC, time series
- Accompanied by data and code repositories
About the book
- Subjects Computer Science,Data Science, Databases, Data Mining, and Information Retrieval,Statistical Theory and Methods,Statistics and Probability
- Format: Hardback
- Expected publication date: 31 August 2024
- ISBN: 9781107113046
- Dimensions (mm): 254 x 203 mm
- Page extent: 840 pages
- Availability: Not yet published - available from
- Format: Paperback
- Expected publication date: 31 August 2024
- ISBN: 9781009568357
- Availability: Not yet published - available from
- Format: Digital
- Expected publication date: 16 September 2024
- ISBN: 9781316286166