eBook: Modern Data Science with R (DRM EPUB)
 
電子書格式: DRM EPUB
作者: Benjamin S. Baumer, Daniel T. Kaplan, Nicholas J. Horton 
系列: Chapman & Hall/CRC Texts in Statistical Science
分類: Economic statistics ,
Probability & statistics ,
Science: general issues ,
Automatic control engineering ,
Mathematical & statistical software ,
Computer science  
書城編號: 20394174


售價: $1105.00

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製造商: CRC Press
出版日期: 2021/04/13
頁數: 632
ISBN: 9780429575396
 
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商品簡介
From a review of the first edition: "Modern Data Science with R... is rich with examples and is guided by a strong narrative voice. What's more, it presents an organizing framework that makes a convincing argument that data science is a course distinct from applied statistics" (The American Statistician).Modern Data Science with R is a comprehensive data science textbook for undergraduates that incorporates statistical and computational thinking to solve real-world data problems. Rather than focus exclusively on case studies or programming syntax, this book illustrates how statistical programming in the state-of-the-art R/RStudio computing environment can be leveraged to extract meaningful information from a variety of data in the service of addressing compelling questions. The second edition is updated to reflect the growing influence of the tidyverse set of packages. All code in the book has been revised and styled to be more readable and easier to understand. New functionality from packages like sf, purrr, tidymodels, and tidytext is now integrated into the text. All chapters have been revised, and several have been split, re-organized, or re-imagined to meet the shifting landscape of best practice.
Chapman & Hall/CRC Texts in Statistical Science

Principles of Uncertainty (2 ed) (Paperback)

Theory of Statistical Inference (Paperback)

Time Series for Data Science: Analysis and Forecasting (Paperback)

Beyond Multiple Linear Regression: Applied Generalized Linear Models And Multilevel Models in R (Paperback)

Stochastic Processes with R: An Introduction (Paperback)

Bayesian Nonparametric Mixture Models: Methods and Applications (Hardcover)

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