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Announcing Open Textbook “Significant Statistics: An Introduction to Statistics”
The Open Education Initiative at Virginia Tech is pleased to announce the release of Significant Statistics: An Introduction to Statistics (2025), adapted by J. Morgan Russell.
Significant Statistics is a peer-reviewed open textbook intended for a one-semester introduction to statistics course for students who are not mathematics or engineering majors. It focuses on the interpretation of statistical results, especially in real world settings, and assumes that students have an understanding of intermediate algebra.
Significant Statistics attempts to focus on what is significant and eliminate some of the noise that may commonly be found in many introductory statistics texts. It covers the basic ideas of data collection, univariate and bivariate descriptives, and one and two sample inference for means and proportions. It does not emphasize one specific software, and instead offers links to many extra resources. Examples of each topic are explained step-by-step throughout the text and followed by a ‘Your Turn’ problem that is designed as extra practice for students. Additionally, there are over 600 extra practice problems at the end of the book.
The book is shared under a Creative Commons Attribution ShareAlike 4.0 license (CC BY SA 4.0).
Instructors reviewing, adopting, or adapting this textbook are asked to please help us understand your use of the material by filling out this form http://bit.ly/stat-interest.
Table of Contents
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- Sampling and Data
- Univariate Descriptive Statistics
- Bivariate Descriptive Statistics
- Probability Distributions
- Foundations of Inference
- Inference for One Sample
- Inference for Two Samples
How to Access the Book
Interactive, accessible, online version: https://pressbooks.lib.vt.edu/significantstatistics
PDF, epub, and other versions: https://doi.org/10.21061/significantstatistics, or order a paperback, full-color copy.
ISBN (PDF): 978-1-962841-01-6
ISBN (HTML): 978-1-957213-85-9
ISBN (print): 978-1-957213-86-6
ISBN (EPUB): 978-1-962841-00-9
The book is also listed in the Open Textbook Library, OER Commons, VIVA Open, and Merlot.
Adapted by
Attribution
The base of the book is from OpenStax Introductory Statistics by Barbara Illowsky and Susan Dean, which is licensed with a Creative Commons Attribution 4.0 (CC BY 4.0) license, much of which was reworded and reorganized. Additional content from OpenIntro Statistics by David Diez, Mine C¸ etinkaya-Rundel, and Christopher D Barr, and Introductory Statistics for the Life and Biomedical Sciences by Julie Vu and David Harrington, both licensed with a Creative Commons Attribution Share-Alike 3.0 (CC BY-SA 3.0) license, were then added to fill in gaps. Several figures were also adapted from the OpenIntro texts.
About the author
John Morgan Russell teaches various introductory statistics courses at Virginia Tech, and previously taught at George Mason University and Old Dominion University. He earned a BS in Mathematics from Christopher Newport University, an MS in Statistical Science from George Mason University, and an Ed.S. in Instructional design and Technology from Virginia Tech. His interests include statistics education, instructional design, and open educational resources.
Suggested citation
Russell, John Morgan (2025). Significant Statistics: An Introduction to Statistics. Blacksburg: Virginia Tech Department of Statistics. https://doi.org/10.21061/significantstatistics. Licensed with CC BY-SA 4.0 https://creativecommons.org/licenses/by-sa/4.0.
Editorial Team
Managing Editor: Anita Walz, Open Education Initiative
Production Editor & Designer: Kindred Grey
This work is published by the Virginia Tech Department of Statistics in association with the Open Education Initiative and Virginia Tech Publishing.
Accessibility
Virginia Tech is committed to making its publications accessible in accordance with the Americans with Disabilities Act of 1990. The Open Education Initiative is committed to continuous improvement regarding accessibility. The text, images, headings, and links in the PDF and HTML versions of this text are tagged structurally and include alternative text, which allows for machine readability. Please contact publishing@vt.edu if you are a person with a disability and have suggestions to make this book more accessible.
License
Unless otherwise noted, this work is released under a Creative Commons Attribution (CC BY SA 4.0) license which allows adaptation and redistribution with attribution for uses which are not primarily commercial as long as appropriate credit is given to the creator and new creations are licensed under the same terms. See the license terms and recommended practices for attribution for additional information.
