Statistical Inference via Data Science: into R by Chester Ismay (.PDF)

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Statistical Inference via Data Science: A ModernDive into R and the Tidyverse, 2nd Edition by Chester Ismay, Albert Y. Kim, Arturo Valdivia
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Overview: Statistical Inference via Data Science: A ModernDive into R and the Tidyverse, Second Edition offers a comprehensive guide to learning statistical inference with Data Science tools widely used in industry, academia, and government. The first part of this book introduces the Tidyverse suite of R packages, including ggplot2 for data visualization and dplyr for data wrangling. The second part introduces data modeling via simple and multiple linear regression. The third part presents statistical inference using simulation-based methods within a general framework implemented in R via the infer package, a suitable complement to the Tidyverse. By working with these methods, readers can implement effective exploratory data analyses, conduct statistical modeling with data, and carry out statistical inference via confidence intervals and hypothesis testing. All of these tasks are performed by strongly emphasizing data visualization. This book is intended for instructors of traditional introductory statistics classes using RStudio, who would like to inject more Data Science topics into their syllabus. RStudio can be used in either the server version or the desktop version. We assume that students taking the class will have no prior algebra, calculus, or programming/coding experience.
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