OpenIntro Statistics

OpenIntro Statistics
OpenIntro Statistics
OpenIntro Statistics
OpenIntro Statistics is a dynamic take on the traditional curriculum, being successfully used at Community Colleges to the Ivy League
all
videos
slides
labs
other
OpenIntro Statistics
is recommended for college courses and self-study.
Getting Started
Amazon KDP raised book print prices by ≈40% in 2023. These changes will net Amazon over $50,000 per year from sales on OpenIntro books, and we expect that OpenIntro will lose money as a result of reduced sales. We are continuing to explore alternative printers to Amazon that provide better quality books as well as selling more books outside of Amazon.
All of our website / resource links to Amazon are affiliate links. When you shop on Amazon using these links, we receive a small commission at no extra charge to you.
FREE -- OpenIntro Statistics PDF
If you want to skip the optional contribution, set the price to $0
$25 -- B&W paperback
Available on Amazon and in select bookstores
$40 -- OpenIntro Statistics, color paperback
Color internal pages, while the B&W version is gray-scaled
FREE -- Book PDF Best for Screen Readers
Extra text to ease aid navigation and "alt text" for all images
Learning objectives
What we hope students will learn from these resources
Data sets
List of data sets and the option to download files
Where to find more data sets
An incredible list of data organized by Shonda Kuiper
Send feedback or report a typo
We appreciate feedback, both positive and negative
List of known textbook typos
Review textbook typos and clarifications
Translations + Other International Distribution
For those using a translated version, please send your warm wishes to the team behind these translations! We deeply appreciate their contributions to the community!
A Japanese translation has been created by a team of Japanese faculty! This translation is available below in both PDF (on Dr. Kunitomo's page) and as an affordable paperback (via the Japanese Statistical Association).
FREE -- Japanese translation of OpenIntro Statistics PDF
Translation by Naoto Kunitomo, Yasushi Yoshida, & Atsuyuki Kogure
Japanese translation, B&W paperback for ¥1980
Translated by Naoto Kunitomo, Yasushi Yoshida, & Atsuyuki Kogure
A Chinese translation is under development by Shiyao Wang and Xueqi Li! A recent draft of the progress is available below.
FREE -- Chinese translation of Ch 1-6 (PDF)
Translation by Shiyao Wang & Xueqi Li
Follow the Chinese translation updates on WeChat
Leads to a WeChat page
A Vietnamese translation is currently under development by a volunteer team led by Associate Professor Do Thi Thanh Toan. A recent draft of the progress is available below. If you notice any typos or errors that need correction, please feel free to contact our corresponding member, Mr. Thanh Hai Pham (email: thanh
ph
hmu
gmail
com). We will do our best to respond promptly.
The team members working on the Vietnamese translation are: Associate Professor Do Thi Thanh Toan; Dr. Le Xuan Hung; Dr. Dinh Thai Son; Dr. Luu Ngoc Minh; Mr. Nguyen Trung Kien (BSc); Mrs. Tran Cat Khanh (BSc); Mr. Vu Gia Huan (MD); Mr. Ngo Gia Huy (MD) (email: huygiango3001
gmail
com); and Mr. Thanh Hai Pham (MSc) - Corresponding member (email: thanh
ph
hmu
gmail
com).
FREE -- Vietnamese translation, Ch 1 (PDF)
Translation by a team led by Professor Do Thi Thanh Toan
FREE -- Vietnamese translation, Ch 2 (PDF)
Translation by a team led by Professor Do Thi Thanh Toan
FREE -- Vietnamese translation, Ch 3 (PDF)
Translation by a team led by Professor Do Thi Thanh Toan
FREE -- Vietnamese translation, Ch 4 (PDF)
Translation by a team led by Professor Do Thi Thanh Toan
FREE -- Vietnamese translation, Ch 5 (PDF)
Translation by a team led by Professor Do Thi Thanh Toan
The paperbacks linked below are for the English version, which is also available in several countries via Amazon.
Click to see all international options
Paperbacks for Canada, UK, India, Germany, and more
English B&W paperback on Amazon.co.jp
See also the Japanese translation option
Amazon.ca -- B&W paperback
Hello, northern neighbor
Amazon.co.uk -- B&W paperback
Hello, from across the Atlantic
Notion Press (India) -- B&W paperback
Price includes shipping cost
Amazon.de -- B&W paperback
Book is in English
Amazon.fr -- B&W paperback
Book is in English
Amazon.es -- B&W paperback
Book is in English
Amazon.it -- B&W paperback
Book is in English
Teachers: General Resources
Resources for teachers, some of which are restricted to
Verified Teachers
only. Slides, labs, and other resources may also be found in the corresponding chapter sections below.
Learn about Teacher Verification
Benefits, options to apply, and the verification process
Request a textbook desk copy (US only)
Available to Verified Teachers, click here to apply for access
OpenIntro Statistics exercise solutions
Available to Verified Teachers, click here to apply for access
Bookstore Ordering (bulk)
Wholesale purchase options
MyOpenMath: online course software
Free course software, OpenIntro course templates are available
MyOpenMath: setting up an OpenIntro course
Course templates exist for some OpenIntro books
OpenIntro Statistics, info on past editions
Content, prices, and availability details
Teachers page with additional resources
Some public resources, others restricted to Verified Teachers
Teachers: Sample Syllabi
OpenIntro Statistics, Syllabus 1
Mine Çetinkaya-Rundel, Duke University
OpenIntro Statistics, Syllabus 2
Curry Hilton, University of Alabama
OpenIntro Statistics, Syllabus 3
Albert Kim, Middlebury College
Teachers: Sample Exams
Restricted to
Verified Teachers
only.
OpenIntro Statistics Exams, Set 1
Available to Verified Teachers, click here to apply for access
Openintro Statistics Exams, Set 2
Available to Verified Teachers, click here to apply for access
Multiple choice exam question bank (RExams)
Available to Verified Teachers, click here to apply for access
OpenIntro Statistics, Sample Exams (Adam Gilbert)
Available to Verified Teachers, click here to apply for access
ISLBS, Sample Midterm and Final Exams (Julie Vu)
Available to Verified Teachers, click here to apply for access
ISRS, Sample Midterms and Final Exam (Albert Kim)
Available to Verified Teachers, click here to apply for access
What is Statistics?
These resources give a taste of what statisticians, also known as
data scientists
, do in the real world.
Videos about applying Statistics
Explore Statistics applications through these short videos!
200 years of history through health & wealth
A tour with Hans Rosling
Bringing life to global health statistics
A longer tour led by Hans Rosling
Building a better NBA team through analytics
Ivana Seric, college basketball player becomes a data scientist
Steven Levitt explores the value of car seats
Disclaimers at the end
Using statistics to treat chronic illnesses
MacArthur Fellow Susan Murphy
Using data to better understand agriculture
MacArthur Fellow David Lobell
Why the term "Data Science" is so confusing
The two main
types
of data scientists:
nalysis and
uilding
Companion Notebook
This new resource is in beta and is an interactive learning experience. This resource can serve many purposes for different students: a way to learn material, study for an exam, check understanding, and so on. If you have feedback, please send us a note on our
Contact page
For Posit Cloud, we recommend starting with a free account and only upgrading to a paid account if you exhaust your monthly free time.
Student Guide for OS4 Companion Notebook
Video guide for a student to make use of the OS4 Companion Notebook
OS4 Companion Notebook
Interactive learning option (in beta)
Frequently Asked Questions
Trouble-shooting tips
Grading functionality
Chapter 1: Intro to Data
Videos for each section
Introduction to Data: 5 videos
1.1 - Using stents to prevent strokes
Real case study with a surprising finding
1.2 - Data basics
Typical data structures and properties
1.3A - Data collection principles
Thoughtful data collection is critical to learning from data
1.3B - Sampling principles and strategies
Different ways to sample from a population
1.4 - Experiments
Basic principles of experimental design
Slides for each section
Google Slides & LaTeX variants available
Slides 1 - Intro to data
LaTeX slides for full chapter on Github
Slides 1.1 - Intro to data, case study
Google Slides version, can export to Powerpoint
Slides 1.2 - Data Basics
Google Slides version, can export to Powerpoint
Slides 1.3 - Sampling principles and strategies
Google Slides version, can export to Powerpoint
Slides 1.4 - Experiments
Google Slides version, can export to Powerpoint
Lab - Intro to Statistical Software
Software: R (Base), R (Tidyverse), Rguroo, Jamovi, JASP, SAS, Stata
Chapter 2: Summarizing Data
Videos for each section
Summarizing Data: 3 videos
2.1 - Examining numerical data
Mean, standard deviation, histograms, box plots, and more
2.2 - Considering categorical data
Table proportions, bar graphs, mosaic plots, and more
2.3 - Case study
Early inference ideas: testing using randomization
Slides for each section
Google Slides & LaTeX variants available
Slides 2 - Summarizing data
LaTeX slides for full chapter on Github
Slides 2.1 - Examining numerical_data
Google Slides version, can export to Powerpoint
Slides 2.2 - Considering categorical data
Google Slides version, can export to Powerpoint
Slides 2.3 - Case study
Google Slides version, can export to Powerpoint
Lab - Introduction to data
Software: R (Base), R (Tidyverse), Rguroo, Jamovi, JASP, Python, SAS, Stata
Class Activity: Descriptive Measures
Collecting and exploring Instagram data
Weighted mean
Supplemental section: How and when to use weighting
Chapter 3: Probability
Videos for some sections
Probability: 3 videos
3.1 - Defining probability
Core concepts, explained in detail
3.2 - Probability trees
Useful tool for conditional probability
Would you take this bet?
Thinking through probability and risk
Slides for each section
Google Slides & LaTeX variants available
Slides 3 - Probability
LaTeX slides for full chapter on Github
Slides 3.1 - Defining probability
Google Slides version, can export to Powerpoint
Slides 3.2 - Conditional probability
Google Slides version, can export to Powerpoint
Slides 3.3 - Sampling from a small population
Google Slides version, can export to Powerpoint
Slides 3.4 - Random variables
Google Slides version, can export to Powerpoint
Slides 3.5 - Continuous distributions
Google Slides version, can export to Powerpoint
Lab - Probability
Software: R (Base), R (Tidyverse), Rguroo, Jamovi, JASP, Python, SAS, Stata
Chapter 4: Distributions
Videos for some sections
Distributions: 3 videos
4.1 - Normal distribution
Core concepts and several examples
4.3A - Binomial distribution
Introduction to the binomial distribution
4.3B - Normal approximation to binomial
A useful technique for some binomial situations
Slides for each section
Google Slides & LaTeX variants available
Slides 4 - Distributions
LaTeX slides for full chapter on Github
Slides 4.1 - Normal distributions
Google Slides version, can export to Powerpoint
Slides 4.2 - Geometric distribution
Google Slides version, can export to Powerpoint
Slides 4.3 - Binomial distribution
Google Slides version, can export to Powerpoint
Slides 4.4 - Negative binomial distribution
Google Slides version, can export to Powerpoint
Slides 4.5 - Poisson distribution
Google Slides version, can export to Powerpoint
Lab - Normal distribution
Software: R (Base), R (Tidyverse), Rguroo, Jamovi, JASP, Python, SAS, Stata
Class Activity: Sampling Distributions
As presented at Women in Stat and DS Conference
Normal distribution calculator
Online tool for normal distribution calculations
Chapter 5: Foundations for Inference
Videos for each section
Foundations for Inference: 4 videos
5.1 - Variability of the sample proportion
Introduces the Central Limit Theorem
5.2 - Confidence intervals
Reporting a range, not just a point estimate
5.3 - Hypothesis testing
Introduced using numerical data (means)
Inference for other estimators
Generalizing the tools of inference
Why do we use 0.05 as a significance level?
Inquiring minds want to know -- let's explore!
Slides for each section
Google Slides & LaTeX variants available
Slides 5 - Foundations for inference
LaTeX slides for full chapter on Github
Slides 5.1 - Point estimates and sampling variability
Google Slides version, can export to Powerpoint
Slides 5.2 - Confidence intervals
Google Slides version, can export to Powerpoint
Slides 5.3 - Hypothesis testing
Google Slides version, can export to Powerpoint
Lab - Intro to inference
Software: R (Base), R (Tidyverse), Rguroo, Jamovi, JASP, Python, SAS, Stata
Lab - Confidence levels
Software: R (Base), R (Tidyverse), Rguroo, Jamovi, JASP, Python, SAS, Stata
One-page inference guide
Covers one-sample and diff of means and proportions
Chapter 6: Inference for Categorical Data
Videos for each section
Inference for categorical data: 3 videos
6.1 + 6.2 - Inference for proportions
Covers both 1 and 2 proportion scenarios
6.3 - Testing for goodness of fit
Chi-square test for one-way tables
6.4 - Chi-square for two-way tables
Testing for homogeneity or independence
Slides for each section
Google Slides & LaTeX variants available
Slides 6 - Inference for categorical data
LaTeX slides for full chapter on Github
Slides 6.1 - Inference for a single proportion
Google Slides version, can export to Powerpoint
Slides 6.2 - Inference for a difference of two props
Google Slides version, can export to Powerpoint
Slides 6.3 - Testing goodness of fit using chi-square
Google Slides version, can export to Powerpoint
Slides 6.4 - Testing for independence in 2-way tables
Google Slides version, can export to Powerpoint
Lab - Inference for categorical data
Software: R (Base), R (Tidyverse), Rguroo, Jamovi, JASP, Python, SAS, Stata
Hypothesis testing for small sample proportions
Supplemental section: When the success-failure condition fails
Online app for Central Limit Theorem for proportions
This is a Shiny app for exploration
Chapter 7: Inference for Numerical Data
Videos for each section
Inference for categorical data: 8 videos
7.1A - t-distribution
Useful new distribution for inference for means
7.1B - Inference for one mean
Covers confidence intervals and hypothesis tests
7.2 - Paired data
Special case for difference of two means
7.3 - Difference of two means
When we have two independent samples
7.4 - Power calculations
Covers the scenario of the difference of two means
7.5A - Intro to ANOVA
Key concepts and ideas
7.5B - Conditions for ANOVA
How to check if ANOVA is reasonable
7.5C - Multiple comparisons
How we determine which groups are different
Slides for each section
Google Slides & LaTeX variants available
Slides 7 - Inference for numerical data
LaTeX slides for full chapter on Github
Slides 7.1 - One-sample means with the t-distribution
Google Slides version, can export to Powerpoint
Slides 7.2 - Paired data
Google Slides version, can export to Powerpoint
Slides 7.3 - Difference of two means
Google Slides version, can export to Powerpoint
Slides 7.4 - Power calculations for difference of means
Google Slides version, can export to Powerpoint
Slides 7.5 - Comparing many means with ANOVA
Google Slides version, can export to Powerpoint
Lab - Inference for numerical data
Software: R (Base), R (Tidyverse), Rguroo, Jamovi, JASP, Python, SAS, Stata
Class Activity: Correlation
Students compare and correlate movie ratings
Sample size and power (one-sample)
Supplemental section: on power in the one-sample scenario
Better understand ANOVA calculations
Supplemental section: Details behind ANOVA
Online app for Central Limit Theorem for means
This is a Shiny app for exploration
Chapter 8: Introduction to Linear Regression
Videos for each section
Intro to linear regression: 5 videos
8.1 - Ideas of fitting a line
Also covers residuals and correlation
8.2 - Fitting a least squares regression line
The notion of a "best fitting" line
8.2 - Detailed Overview: Fitting a least squares regression line
Section 8.2 textbook walkthrough by author
8.3 - Types of outliers in regression
Points of high leverage and influential points
8.4 - Inference for linear regresion
Using the t-distribution for inference in regression
Slides for each section
Google Slides & LaTeX variants available
Slides 8 - Linear regression
LaTeX slides for full chapter on Github
Slides 8.1 - Line fitting, residuals, and correlation
Google Slides version, can export to Powerpoint
Slides 8.2 - Fitting a line by least squares regression
Google Slides version, can export to Powerpoint
Slides 8.3 - Types of outliers in linear regression
Google Slides version, can export to Powerpoint
Slides 8.4 - Inference for linear regression
Google Slides version, can export to Powerpoint
Lab - Linear regression
Software: R (Base), R (Tidyverse), Rguroo, Jamovi, JASP, Python, SAS, Stata
Chapter 9: Multiple and Logistic Regression
Videos for some sections
Multiple & logistic regression: 4 videos
9.1 - Multiple regression basics
Using many predictors in a single model
9.2 - Model selection
How to determine which variables to keep in the model
9.3 - Checking conditions using graphs
Several key graphs to assessing a multiple regression model
9.5 - Intro to logistic regression
When the outcome is binary (e.g. yes/no)
Slides for each section
Google Slides & LaTeX variants available
Slides 9 - Multiple + logistic regression
LaTeX slides for full chapter on Github
Slides 9.1 - Intro to multiple regression
Google Slides version, can export to Powerpoint
Slides 9.2 - Model selection
Google Slides version, can export to Powerpoint
Slides 9.3 - Checking model conditions using graphs
Google Slides version, can export to Powerpoint
Slides 9.5 - Intro to logistic regression
Google Slides version, can export to Powerpoint
Lab - Multiple regression
Software: R (Base), R (Tidyverse), Rguroo, Jamovi, JASP, Python, SAS, Stata
More inference for linear regression
Supplemental section: Confidence and prediction intervals
Interaction terms
Supplemental section: When predictors impact outcomes in complex ways
Regression for nonlinear relationships
Supplemental section: When a straight line doesn't make sense
Online app for better understanding regression
This is a Shiny app for exploration
More Resources
Worked exercise examples (video)
Playlist of a collection of worked exercises
Video guide: Casio fx-9750GII
Playlist covering all intro statistics topics for this calculator
Video guide: TI-83 and TI-84
Playlist for all intro statistics topics for both calculators
Casio fx-9750GII graphing calculator guide
Written guide covering intro statistics functionality
TI-83 / TI-84 graphing calculator guide
Written guide covering intro statistics functionality
Distribution calculators
Covers the normal, t, and chi-square distributions
Probability tables
Covers the normal, t, and chi-square distributions
OpenIntro Statistics LaTeX source files
Leads to the Github repository
Sample Student Projects
These projects were completed in the early years of OpenIntro. We will consider posting new student projects jointly submitted by a Verified Teacher and student(s).
Lobbying and SOPA/PIPA
Intern project completed by Luke Paulsen
Data for Lobbying and SOPA/PIPA
Original data set
R Code for Lobbying and SOPA/PIPA project
Run to reproduce the analysis
Modeling Population Growth in US
Intern project completed by Luke Paulsen
Data for Modeling Population Growth in US
Updated data set
R Code for Modeling Population Growth in US
Data set and variable names may need updates
Fluorescence Resonance Energy Transfer
By Sebastian Raschka
Bootstrapping Simulation
By Yiyang Hu
Our International Image
By Ryan Boone, Kanya Manoj, Jacob Zionce
Modeling Mortality Rates with Env. Var.
By Fernandez XD, Davis K, Weishampel A, McMillan A
More Free Books
Beyond the set of textbooks we offer on openintro.org, many other authors have made their books publicly available. The links below go to the places where these other authors posted their books for free for anyone.
Statistical Inference via Data Science
Paperbacks run about $75
A First Course in Design and Analysis of Experiments
Includes supplemental resources
An Introduction to Statistical Learning
Physical copies are about $80
Elements of Statistical Learning
Physical copies are about $90
Principles of Epidemiology in Public Health Practice
Print version at bookstore.phf.org for about $65
Survival Analysis in R
Workshop materials and a guide for survival analysis in R
Introduction to Probability
Physical copies are about $60
Practical Regression and ANOVA using R
Related publisher title: Linear Models with R
Think Stats
Physical copies are about $30
Collaborative Statistics on CNX.org
Physical copies are about $30 on Lulu
CK-12 Probability and Statistics
CK-12 offers many open-source textbooks
Introduction to Statistical Thought
Upper division or intro grad level
Introduction to Probability and Statistics Using R
Available on R-Forge
Online Statistics Education
An Interactive Multimedia Course of Study
Introduction to Statistical Thinking
With R, Without Calculus