34 Statistics
Beginning Statistics
2012
Licence: CC BY-NC-SA
This book is meant to be a textbook for a standard one-semester introductory statistics course for general education students.
Format: Online
Suggested for: MATH 215
Collaborative Statistics
Barbara Illowsky and Susan Dean (De Anza College)
2012
Licence: CC BY
This book is intended for introductory statistics courses being taken by students at two– and four–year colleges who are majoring in fields other than math or engineering. Intermediate algebra is the only prerequisite. The book focuses on applications of statistical knowledge rather than the theory behind it. The text is named Collaborative Statistics because students learn best by doing. In fact, they learn best by working in small groups. The old saying “two heads are better than one” truly applies here.
Format: Online and PDF
Suggested for: MATH 215
Intermediate Statistics with R
Mark C. Greenwood
2014
Licence: CC BY-NC
This textbook builds on the basic statistical thinking from an introductory course to explore a large number of statistical methods.
Format: PDF
Suggested for: MATH 216, MATH 315
Introduction to Modern Statistics
Mine Çetinkaya-Rundel and Johanna Hardin
Licence: CC BY-SA
Introduction to Modern Statistics is a re-imagining of a previous title, Introduction to Statistics with Randomization and Simulation. 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: 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 visualization 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. 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. 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.
Formats: Online and PDF
Suggested for: MATH 215, MATH 216
Introduction to Probability
Charles M. Grinstead (Swarthmore College), J. Laurie Snell (Dartmouth College)
2006
GNU Free Documentation Licence
This introductory probability book, published by the American Mathematical Society, emphasizes the use of computing to simulate experiments and make computations. The authors have prepared a set of programs to go with the book, along with solutions available to instructors. They also provide links to other probability resources.
Format: PDF
Suggested for: MATH 215, MATH 209
Introduction to Statistics
David Lane (Rice University)
2003
Licence: CC0 (Public Domain)
Introduction to Statistics is a resource for learning and teaching introductory statistics.
Format: Online, PDF, EPUB
Suggested for: MATH 215
Introductory Statistics 2e (OpenStax)
Barbara Illowsky (De Anza College), Susan Dean (De Anza College), and Laurel Chiappetta (University of Pittsburgh) (OpenStax)
2024
Licence: CC BY
Introductory Statistics follows the scope and sequence of a one-semester, introduction to statistics course and is geared toward students majoring in fields other than math or engineering. This text assumes students have been exposed to intermediate algebra, and it focuses on the applications of statistical knowledge rather than the theory behind it.
Formats: Online and PDF; online LibreTexts version
Suggested for: MATH 215
Introductory Statistics
Douglas S. Shafer and Zhiyi Zhang (University of North Carolina) (Saylor Foundation)
2012
Licence: CC BY-NC-SA
This peer-reviewed resource introduces statistical concepts, including: descriptive statistics, basic concepts of probability, discrete random variables, continuous random variables, sampling distributions, estimation, testing hypotheses, two-sample problems, correlation and regression, and chi-square and f-tests.
Formats: Online and PDF
Suggested for: MATH 215
Introductory Statistics for Life and Biomedical Sciences
Open Intro
Licence: CC BY-SA
Introduction to Statistics for the Life and Biomedical Sciences has been written to be used in conjunction with a set of self-paced learning labs. These labs guide students through learning how to apply statistical ideas and concepts discussed in the text with the R computing language.
The text discusses the important ideas used to support an interpretation (such as the notion of a confidence interval), rather than the process of generating such material from data (such as computing a confidence interval for a particular subset of individuals in a study). This allows students whose main focus is understanding statistical concepts to not be distracted by the details of a particular software package. In our experience, however, we have found that many students enter a research setting after only a single course in statistics. These students benefit from a practical introduction to data analysis that incorporates the use of a statistical computing language. In a classroom setting, we have found it beneficial for students to start working through the labs after having been exposed to the corresponding material in the text, either from self-reading or through an instructor presenting the main ideas. The labs are organized by chapter, and each lab corresponds to a particular section or set of sections in the text. There are traditional exercises at the end of each chapter that do not require the use of computing. More complicated methods, such as multiple regression, do not lend themselves to hand calculation and computing is necessary for gaining practical experience with these methods. The lab exercises for these later chapters become an increasingly important part of mastering the material. An essential component of the learning labs are the “Lab Notes” accompanying each chapter. The lab notes are a detailed reference guide to the R functions that appear in the labs, written to be accessible to a first-time user of a computing language. They provide more explanation than available in the R help documentation, with examples specific to what is demonstrated in the labs. The notes cover topics such as constructing histograms, writing loops, and running regression models.
Formats: PDF and LaTeX
Suggested for: MATH 215, MATH 216
Learning Statistics with R: A tutorial for psychology students and other beginners
Danielle Navarro (University of New South Wales)
2018
Licence: CC BY-SA
This book covers the contents of an introductory statistics class, as typically taught to undergraduate psychology students, focusing on the use of the R statistical software. The book discusses how to get started in R as well as giving an introduction to data manipulation and writing scripts. From a statistical perspective, the book discusses descriptive statistics and graphing first, followed by chapters on probability theory, sampling and estimation, and null hypothesis testing. After introducing the theory, the book covers the analysis of contingency tables, t-tests, ANOVAs and regression. Bayesian statistics are covered at the end of the book.
Format: PDF and LaTeX
Suggested for: MATH 216
Lies, Damned Lies, or Statistics: How to Tell the Truth with Statistics
Jonathan A. Poritz (Colorado State University)
2017
Licence: CC BY-SA
This textbook is intended for a one-semester, undergraduate statistics course. There are many concrete, specific questions that humans have about the world which are best answered by carefully collecting some data and using a modest amount of mathematics and a fair bit of logic to analyze them. It is, therefore, the goal of this book to help you learn How to Tell the Truth with Statistics and, therefore, how to tell when others are telling the truth … or are faking their “news.”
Format: PDF
Suggested for: MATH 215
Mathematical Statistics
Gregg Waterman (Oregon Institute of Technology)
2015
Licence: CC BY-NC-SA
The title of this book is perhaps misleading, as there is no statistics within. It is instead a fairly straightforward introduction to mathematical probability, which is the foundation of mathematical statistics. One could follow this course with a rigorous treatment of statistics, beyond that usually seen in most introductory statistics courses.
Format: PDF
Suggested for: MATH 215, MATH 209
Mostly Harmless Elementary Statistics – 1st Edition
Rachel L. Webb (Portland State University)
2023
Licence: CC BY-SA
This text is for an introductory level probability and statistics course with an intermediate algebra prerequisite. The focus of the text follows the American Statistical Association’s Guidelines for Assessment and Instruction in Statistics Education (GAISE). Software examples provided for Microsoft Excel, TI-84 & TI-89 calculators. Students new to statistics are sure to benefit from this ADA accessible and relevant textbook. The examples are current and resonate with everyday life. The casual narrative style, has a conversational tone to provide an inclusive and easy to read format for students.
Format: PDF
Suggested for: MATH 215
OpenIntro Statistics – Fourth Edition
David M. Diez (Harvard School of Public Health), Christopher D. Barr (Harvard School of Public Health), and Mine Cetinkaya-Rundel (Duke University)
2019
Licence: CC BY-SA
OpenIntro Statistics covers a first course in statistics, providing a rigorous introduction to applied statistics that is clear, concise, and accessible. This book was written with the undergraduate level in mind, but it’s also popular in high schools and graduate courses.
Format: PDF
Suggested for: MATH 215
Significant Statistics
John Morgan Russell, Virginia Tech University
2025
Licence: CC BY-SA
Significant Statistics: An Introduction to Statistics is intended for students enrolled in a one-semester introduction to statistics course 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. In addition to end of section practice and homework sets, 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.
Significant Statistics: An Introduction to Statistics was adapted from content published by OpenStax including Introductory Statistics, OpenIntro Statistics, and Introductory Statistics for the Life and Biomedical Sciences. John Morgan Russell reorganized the existing content and added new content where necessary.
Format: Online, Hardcopy, Ebook, PDF
Suggested for: MATH 215
Statistics Through an Equity Lens
Yvonne E. Anthony (Framingham State University)
2024
Licence: CC BY-NC-SA
This Open Educational Resource (OER) carries a significant responsibility by presenting statistics through an equity lens. The metaphor of a lens is used intentionally–as the glasses one wears can have a profound effect on what one sees. The book encourages further inspection of the ways in which data is collected, interpreted, and analyzed on a variety of social justice issues, such as health disparities, hunger and food insecurity, homelessness, behavioral health (mental health and substance use), and incarceration of males of color. It also attempts to reveal how the misuse of data can reinforce inequities, for example, by stigmatizing people and labeling neighborhoods as high poverty, violent, and having poor educational opportunities. Whether an intended or unintended consequence, irresponsible data use can contribute to racist impressions of people and communities.
Format: Online, PDF, eBook
Suggested for: MATH 215
Statistics Using Technology – Third Edition
Kathryn Kozak (Coconino Community College)
2021
Licence: CC BY-SA
This is an introductory Statistics textbook for first-year college courses. This book places data at the center of the course. It also uses the statistical package R, though you can use another statistical computer package if you wish.
Formats: PDF, Word, and R Markdown
Suggested for: MATH 216
Think Bayes: Bayesian Statistics Made Simple
Allen B. Downey (Franklin W. Olin College of Engineering)
2012
Licence: CC BY-NC-SA
This statistics text covers introductory concepts in Bayesian statistics, from computational statistics to dimensions. Most books on Bayesian statistics use mathematical notation and present ideas in terms of mathematical concepts like calculus. This book uses Python code instead of math, and discrete approximations instead of continuous mathematics. As a result, what would be an integral in a math book becomes a summation, and most operations on probability distributions are simple loops.
Formats: Online, PDF, and LaTex
