Digital library
Textbooks, references and open learning resources.
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Mike’s Biostatistics Book
Michael R Dohm · Chaminade University
In the contents: 2.1: Why (Bio)Statistics · 2.3: A brief history of (bio)statistics · 2.4: Experimental Design and rise of statistics in medical research
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Statistics Done Wrong
Alex Reinhart · Carnegie Mellon University
In the contents: 02: Statistical Power and Underpowered Statistics
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Introduction to Statistics (RRCC)
Mathematics Department · Red Rocks Community College
In the contents: 1.01: What is Statistics
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Applied Statistics for Social Science
LibreTexts
In the contents: 1.2: Definitions of Statistics, Probability, and Key Terms · 02: Descriptive Statistics · 2.1: Prelude to Descriptive Statistics
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A Contemporary Approach to Research and Statistics in Psychology
Klaire Somoray · James Cook University
In the contents: 1.01: What can Statistics do for us · 1.03: Big Ideas in Statistics · 09: Beyond Research and Statistics
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Statistics Through an Equity Lens (Anthony)
Yvonne Anthony · Massachusetts Bay Community College
In the contents: 1.01: An Overview of Statistics · 1.02: Descriptive Statistics · 1.04: Inferential Statistics- Sampling Methods
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PSYC 330: Statistics for the Behavioral Sciences with Dr. DeSouza
LibreTexts
In the contents: 01: What are Statistics · 1.01: What are statistics · 1.02: Why do we study statistics
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Introductory Statistics
Barbara Illowsky & Susan Dean · De Anza College
In the contents: 1.02: Definitions of Statistics Probability and Key Terms · 02: Descriptive Statistics · 2.01: Prelude to Descriptive Statistics
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Introductory Statistics
Hannah Seidler-Wright · Chaffey College
In the contents: 1.01: Welcome to Statistics · 02: Descriptive Statistics · 2.01: Descriptive Statistics - Dotplots and Histograms
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Lies, Damned Lies, or Statistics - How to Tell the Truth with Statistics
Jonathan A. Poritz · Colorado State University – Pueblo
In the contents: 01: One-Variable Statistics - Basics · 02: Bi-variate Statistics - Basics · 06: Inferential Statistics
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Math 10: Elementary Statistics
Cliff Hwang · Mission College
In the contents: 1.02: Definitions of Statistics Probability and Key Terms · 02: Descriptive Statistics · 2.01: Prelude to Descriptive Statistics
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MGT 235: Introductory Business Statistics
Gettysburg College · LibreTexts
In the contents: 1.02: Definitions of Statistics Probability and Key Terms · 02: Descriptive Statistics · 11.03: C - Reporting Statistics in APA Style
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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.