Digital library
Textbooks, references and open learning resources.
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Introduction to Statistics in the Psychological Sciences
Linda Cote; Rupa Gordon; Chrislyn Randell; Judy Schmitt · University of Missouri - St. Louis · 2021
Introduction to Statistics in the Psychological Sciences provides an accessible introduction to the fundamentals of statistics, and hypothesis testing as need for psychology students. The textbook introduces the fundamentals of statistics, an introduction to hypothesis testing, and t Tests. Related samples, independent samples, analysis of variance, correlations, linear regressions and chi-squares are all covered along with expanded appendices with z, t, F correlation, and a Chi-Square table. The text includes key terms and exercises with answers to odd-numbered exercises. Psychology students often find statistics courses to be different from their other psychology classes. There are some distinct differences, especially involving study strategies for class success. The first difference is learning a new vocabulary—it is similar to learning a new language. Knowing the meaning of certain words will help as you are reading the material and working through the problems. Secondly, practice is critical for success; reading over the material is not enough. Statistics is a subject learned by doing, so make sure you work through any homework questions, chapter questions, and practice problems available. Statistical knowledge gives you a set of skills employable in graduate school and the workplace. Data science is a burgeoning field, and there is practical significance in learning this material. The statistics presented in this book are some of the most common ones used in research articles, and we hope by the end of this OER you’ll feel comfortable reading (and not skipping!) the results section of an article. This work is broken into 14 chapters, covering the fundamentals of statistics, and hypothesis testing.
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Answering questions with data: Introductory Statistics for Psychology Students
Matthew Crump · Crump Lab · 2018
This is a free textbook teaching introductory statistics for undergraduates in Psychology. This textbook is part of a larger OER course package for teaching undergraduate statistics in Psychology, including this textbook, a lab manual, and a course website. All of the materials are free and copiable, with source code maintained in Github repositories.
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You're Smarter Than You Think: Statistics
Safaa Dabagh · Safaa Dabagh · 2026
You're Smarter Than You Think: Statistics is a free, openly licensed introduction to statistics written for community college students and designed from the ground up for neurodivergent and anxious learners. Every section follows the same six-step rhythm (Read This First, Let's Talk About It, Now We Name It, Watch It Work, Your Turn, Check Your Voice), and every chapter opens with a Math Skills warm-up so a missing arithmetic step never derails a big idea. The book is organized around the student learning outcomes shared by community college statistics courses: describing data, estimating with confidence, and testing claims. It covers data and sampling, graphs, center and spread, probability, distributions, the Central Limit Theorem, confidence intervals, hypothesis testing, two-sample tests, ANOVA, chi-square, and regression. Four free Technology Companions (R and RStudio, jamovi, StatCrunch, and the TI-84) carry every method into whatever software a course uses, each keyed chapter by chapter and packaged with ready-made datasets. Graphs, printable work space, answer keys, per-part formula sheets, and a cumulative final-exam prep are included throughout.
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Python for Introductory Statistics
Simon Aman · City Colleges of Chicago · 2021
The purpose of this material is to provide an overview of the free programming language, Python, and a few of its software libraries that are most useful for improving Introductory Statistics students' learning and for providing an alternative statistical software package for those who perform statistical data analysis and plotting. This material, along with the companion workbook and a free web-based Python platform, could easily replace the use of other software packages and calculators in an Introductory Statistics course. Part I, Sections 1 to 4, covers the basics of the Python programming language. Part II, Sections 5 to 13, focuses on Python for introductory statistics, and Part III, Section 14, covers selected advanced statistics topics in Python. Additionally, there are demo video links accompanying key steps for further instruction. No prior programming knowledge is required or assumed.
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A Contemporary Approach to Research and Statistics in Psychology
Klaire Somoray · Council of Australian University Librarians · 2023
This book is designed as a short and introductory resource specifically aimed to help students grasp key concepts typically found in undergraduate psychology statistics subjects. It was initially developed for online and intensive programs, which are becoming increasingly popular in psychology education. The book utilises jamovi, a free and open-source statistical software. This peer reviewed book is completely free to download, use, and adapt and it is released using the CC BY-NC 4.0 licence.
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Significant Statistics
John Russell · Virginia Tech Publishing · 2025
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. Instructors reviewing, adopting, or adapting this textbook: please help us understand your use by filling out this form: https://bit.ly/stat-interest.
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Statistics with JASP: First Steps for Psychology Students
Rebecca Denniss; Stanislava Naneva · University of Sheffield · 2025
New to statistics software? This guide is designed just for you. Whether you are studying psychology or any subject that involves analysing data, this easy-to-follow introduction to JASP will help you get to grips with the basics—no previous experience needed. Originally written for first-year psychology students at the University of Sheffield, it walks you through everything from entering data and adjusting settings to running t-tests, correlations, and chi-square analyses. With clear explanations, practical tips, and helpful screenshots, this guide makes learning JASP simple and stress-free.
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Learning Statistics with jamovi: A Tutorial for Beginners in Statistical Analysis
Danielle Navarro; David Foxcroft · Open Book Publishers · 2025
Based on Danielle Navarro’s widely acclaimed and prize-winning book Learning Statistics with R, this elegantly designed textbook offers undergraduate students a thorough and accessible introduction to jamovi, as well as how to get to grips with statistics and data manipulation. Lucid and easy to understand, Learning Statistics with jamovi covers the analysis of contingency tables, t-tests, correlation, regression, ANOVA and factor analysis, while also giving students a firm grounding in descriptive statistics and graphing. It includes learning aids for applying statistical principles using the jamovi interface, as well as embedded data files to accompany the book, and comprehensive chapters on probability theory, sampling and estimation, and null hypothesis testing. Freely available in open access, Learning Statistics with jamovi is an ideal introduction for undergraduate and postgraduate students of psychology, as well as behavioural and health science students and anyone who needs to understand and use statistical analysis in their work.
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Statistics Minus The Math
Nathan Favero · Nathan Favero · 2024
This book was largely adapted from the public domain resource Online Statistics Education: A Multimedia Course of Study (https://onlinestatbook.com Project Leader: David M. Lane, Rice University). A huge thanks to David Lane and his colleagues at Rice University for their creation of this wonderful resource. I use footnotes throughout to indicate precisely where the various sections of each chapter came from. Chapters 11-13 (as well as Section 3.5, Section 4.2.2, most of Section 4.2.3, and Section 9.3.1) were written by me (Nathan). This book is meant to be a free resource and is licensed under CC BY 4.0. You’re welcome to share or adapt it, as long as you provide attribution to any work of mine that you use. This book was made using Quarto and is hosted using GitHub Pages. There are still formatting inconsistencies, and this is ever a work in progress. If you find errors, feel free to reach out (find updated contact info here: https://nathanfavero.com) so I can correct them for the next version I publish.
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Basic Statistics Using R for Crime Analysis
Jaeyoung Choi · The Pennsylvania Alliance for Design of Open Textbooks (PA-ADOPT) · 2024
Limited access to subscription-based statistical software poses obstacles when students want to apply the skills they acquired in college. Although students may learn programs like SPSS or Stata while at the university, they often find themselves unable to continue using these programs after graduation, making their acquired skills obsolete. As an open-source software program, R offers a solution to this challenge. It is freely accessible to anyone, including students, after they graduate. Therefore, I decided to write a freely available book for those interested in becoming crime analysts, focusing on learning statistics without delving too deeply into mathematics. Moreover, this book emphasizes practical applications by utilizing R for data analysis, ensuring students can develop relevant skills beyond the university. I hope that students can easily follow the instructions in this book and replicate the same outcomes using the provided data. This practical experience will demonstrate the value of statistics and R, ideally inspiring students to further their learning in these areas.
![Statistics Through an Equity Lens [Revised Edition]](/api/files/covers/otl-1625.webp)
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Statistics Through an Equity Lens [Revised Edition]
Yvonne Anthony · ROTEL · 2023
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.
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Statistics for Ecologists: A Frequentist and Bayesian Treatment of Modern Regression Models
John Fieberg · University of Minnesota Libraries Publishing · 2024
Ecological data pose many challenges to statistical inference. Most data come from observational studies rather than designed experiments; observational units are frequently sampled repeatedly over time, resulting in multiple, non-independent measurements; response data are often binary (e.g., presence-absence data) or non-negative integers (e.g., counts), and therefore, the data do not fit the standard assumptions of linear regression (Normality, independence, and constant variance). This book will familiarize readers with modern statistical methods that address these complexities using both frequentist and Bayesian frameworks.
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An Intuitive, Interactive, Introduction to Biostatistics
Caitlin Ward; Collin Nolte · University of Iowa · 2023
"An Intuitive, Interactive Introduction to Biostatistics" is an introductory statistics textbook oriented towards towards undergraduate students in the health sciences. While covering the breadth of material typically presented in a first semester statistics course, including introductions to probability and distributions, study design, CLT, hypothesis testing, and inference, IIIB distinguishes itself with its focus on cultivating student intuition through the use of guided questions and interactive simulation-based applets. Written in R, this open-source text has been created with customizability in mind, offering instructors maximal flexibility in arranging and modifying the content.
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Statistics for Research Students
Erich Fein; John Gilmour; Tayna Machin; Liam Hendry · University of Southern Queensland · 2022
This book aims to help you understand and navigate statistical concepts and the main types of statistical analyses essential for research students.
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Introduction to Applied Statistics for Psychology Students
Gordon Sarty · University of Saskatchewan · 2022
Introduction to Applied Statistics for Psychology Students, by Gordon E. Sarty (Professor, Department of Psychology, University of Saskatchewan) began as a textbook published in PDF format, in various editions between 2014-2017. The book was written to meet the needs of University of Saskatchewan psychology students at the undergraduate (PSY 233, PSY 234) level. In 2019-2020, funding was provided through the Gwenna Moss Centre for Teaching and Learning, along with technical assistance from the Distance Education Unit, to update and adapt this book, making it more widely available in an easy-to-use and more adaptable digital (Pressbooks) format. The update also made revisions so that the book could be published with a license appropriate for open educational resources (OER). OERs are defined as “teaching, learning, and research resources that reside in the public domain or have been released under an intellectual property license that permits their free use and re-purposing by others” (Hewlett Foundation). This textbook and other OERs like it are openly licensed using a Creative Commons license, and are offered in various digital and e-book formats free of charge. Printed editions of this book can be obtained for a nominal fee through the University of Saskatchewan bookstore.
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Mostly Harmless Elementary Statistics
Rachel Webb · Portland State University Library · 2023
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.
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Intermediate Statistics with R
Mark Greenwood · Montana State University · 2021
Introductory statistics courses prepare students to think statistically but cover relatively few statistical methods. Building on the basic statistical thinking emphasized in an introductory course, a second course in statistics at the undergraduate level can explore a large number of statistical methods. This text covers more advanced graphical summaries, One-Way ANOVA with pair-wise comparisons, Two-Way ANOVA, Chi-square testing, and simple and multiple linear regression models. Models with interactions are discussed in the Two-Way ANOVA and multiple linear regression setting with categorical explanatory variables. Randomization-based inferences are used to introduce new parametric distributions and to enhance understanding of what evidence against the null hypothesis “looks like”. Throughout, the use of the statistical software R via Rstudio is emphasized with all useful code and data sets provided within the text. This is Version 3.0 of the book.
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PSYC 2200: Elementary Statistics for the Behavioral and Social Sciences
Michelle Oja · LibreTexts · 2021
Welcome to behavioral statistics, a statistics textbook for social science majors!
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Lies, Damned Lies, or Statistics: How to Tell the Truth with Statistics
Jonathan Poritz · Colorado State University Pueblo · 2017
This is a first draft of a free (as in speech, not as in beer, [Sta02]) (although it is free as in beer as well) textbook for a one-semester, undergraduate statistics course. It was used for Math 156 at Colorado State University–Pueblo in the spring semester of 2017.
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Learning Statistics with R: A tutorial for psychology students and other beginners
Danielle Navarro · Danielle Navarro · 2018
Learning Statistics with R 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.