Introduction to Modern Statistics
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Introduction to Modern Statistics

About the Book

Introduction to Modern Statistics is a re-imagining of a previous title, Introduction to Statistics with Randomization and Simulation book. The new book puts a heavy emphasis on exploratory data analysis (specifically exploring multivariate relationships using visualization, summarization, and descriptive models) and provides a thorough discussion of simulation-based inference using randomization and bootstrapping, followed by a presentation of the related Central Limit Theorem based approaches. Other highlights include:

Web native book. The online book is available in HTML, which offers easy navigation and searchability in the browser. The book is built with the bookdown package and the source code to reproduce the book can be found on GitHub. Along with the bookdown site, this book is also available as a PDF and in paperback. Read the book online here.

Interactive R tutorials. While the main text of the book is agnostic to statistical software and computing language, each part features 4-8 interactive R tutorials (for a total of 32 tutorials) that walk you through the implementation of the part content in R with the tidyverse for data wrangling and visualisation and the tidyverse-friendly infer package for inference. The self-paced and interactive R tutorials were developed using the learnr R package, and only an internet browser is needed to complete them.  Browse the tutorials here.

Labs. Each part also features 1-2 R based labs. The labs consist of data analysis case studies and they also make heavy use of the tidyverse and infer packages. View the labs here.

Datasets. Datasets used in the book are marked with a link to where you can find the raw data. The majority of these point to the openintro package. You can install the openintro package from CRAN or get the development version on GitHub. Find out more about the package here.

To browse these and other resources, visit openintro.org/book/ims.

About the Authors

Mine Cetinkaya-Rundel
Mine Cetinkaya-Rundel

Mine Çetinkaya-Rundel is Senior Lecturer in the School of Mathematics at University of Edinburgh, Data Scientist and Professional Educator at RStudio, and Associate Professor of the Practice position at the Department of Statistical Science at Duke University. Mine’s work focuses on innovation in statistics and data science pedagogy, with an emphasis on computing, reproducible research, student-centered learning, and open-source education as well as pedagogical approaches for enhancing retention of women and underrepresented minorities in STEM. Mine works on integrating computation into the undergraduate statistics curriculum, using reproducible research methodologies and analysis of real and complex datasets. She also organizes ASA DataFest, an annual two-day competition in which teams of undergraduate students work to reveal insights into a rich and complex data set. Mine works on the OpenIntro project, whose mission is to make educational products that are free, transparent, and lower barriers to education. As part of this project, she co-authored four open-source introductory statistics textbooks. She is also the creator and maintainer of datasciencebox.org and she teaches the popular Statistics with R MOOC on Coursera. Mine is a Fellow of the ASA and an Elected Member of the ISI as well as the winner of the 2018 Harvard Pickard Award and the 2016 Waller Education Award.

Johanna Hardin
Johanna Hardin

Jo Hardin is Professor of Mathematics and Statistics at Pomona College. She collaborates with molecular biologists to create novel statistical methods for analyzing high throughput data. She has also worked extensively in statistics and data science education, facilitating modern curricula for higher education instructors. She was a co-author on the 2014 ASA Curriculum Guidelines for Undergraduate Programs in Statistical Science, and she writes on the blog teachdatascience.com. The best part of her job is collaborating with undergraduate students. In her spare time, she loves reading, running, and breeding tortoises.

OpenIntro
OpenIntro

OpenIntro is an educational nonprofit focused on making textbooks that are free, transparent, and lower barriers to education. We also feature supporting resources, such as slides, videos, and more.

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