Significant Statistics: An Introduction to Statistics

Abstract

Statistics is about separating the signal from the noise, deciphering what is actually significant versus what is just happening due to random chance. In addition to demonstrating the basic concepts needed to do that, Significant Statistics: An Introduction to Statistics attempts to focus on what is significant and eliminate some of the noise that may commonly be found in many introductory statistics texts. This book is 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. 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. Are you reviewing or adopting this book for a course? Please help us understand your use by filling out this form. How to access this book

The main landing page for this book is https://doi.org/10.21061/significantstatistics. The PDF and EPUB versions are available to download on the left-hand side of the screen. An online, interactive, accessible version of this book is available here. A paperback print version (in color) is available for order here.

ISBNs ISBN (PDF): 978-1-962841-01-6 ISBN (HTML/Pressbooks): 978-1-957213-85-9 ISBN (print): 978-1-957213-86-6 ISBN (EPUB): 978-1-962841-00-9 Table of contents

Sampling and Data Univariate Descriptive Statistics Bivariate Descriptive Statistics Probability Distributions Foundations of Inference Inference for One Sample Inference for Two Samples

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/. Report errors View errata Funding and project support This publication was made possible in part through funding and publishing support provided by the Open Education Initiative of the University Libraries at Virginia Tech. Accessibility statement Virginia Tech is committed to making its publications accessible in accordance with the Americans with Disabilities Act of 1990. The text, images, and links in the PDF version of this text are tagged structurally and include alternative text, which allows for machine readability. We are continuously working to improve accessibility and welcome any feedback from readers. Cover design: Kindred Grey