Welcome

This is the online version of the textbook Introduction to Modern Statistics! The source code for the book can be found on GitHub.

This is the preliminary edition of OpenIntro::Introduction to Modern Statistics. The preliminary edition is currently under active development. The 1st edition will be available in 2021.

This book is a revamped version of OpenIntro::Introduction to Statistics with Randomization and Simulation, the 1st edition of which can be accessed at openintro.org/book/isrs.

License

Creative Commons License
This online work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. Visit openintro.org/license for more information about the license.

About the authors

Mine Çetinkaya-Rundel

Mine Çetinkaya-Rundel

University of Edinburgh, Duke University, RStudio

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 under-represented 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 three 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.


Johanna Hardin

Johanna Hardin

Pomona College

Jo Hardin is a 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 more 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/. Her favorite part of her job is collaborating with undergraduate students. In her spare time, she loves reading, running, and breeding tortoises.