This textbook is part of the OpenIntro Statistics series and offers complete coverage of the high school AP Statistics curriculum. Real data and plenty of inline examples and exercises make this an engaging and readable book. Links to lecture slides, video overviews, calculator tutorials, and video solutions to selected end of chapter exercises make this an ideal choice for any high school or Community College teacher. In fact, Portland Community College recently adopted this textbook for its Introductory Statistics course, and it estimates that this will save their students $250,000 per year. Find out more at: openintro.org/ahss

View our video tutorials here:
openintro.org/casio
openintro.org/TI

We hope readers will take away three ideas from this book in addition to forming a foundation
of statistical thinking and methods.

(1) Statistics is an applied field with a wide range of practical applications.
(2) You don't have to be a math guru to learn from real, interesting data.
(3) Data are messy, and statistical tools are imperfect. But, when you understand the strengths and weaknesses of these tools, you can use them to learn about the real world.
Textbook overview
The chapters of this book are as follows:

1. Data collection. Data structures, variables, and basic data collection techniques.
2. Summarizing data. Data summaries and graphics.
3. Probability. The basic principles of probability.
4. Distributions of random variables. Introduction to key distributions, and how the normal model applies to the sample mean and sample proportion.
5. Foundation for inference. General ideas for statistical inference in the context of estimating the population proportion.
6. Inference for categorical data. Inference for proportions using the normal and chisquare distributions.
7. Inference for numerical data. Inference for one or two sample means using the t distribution, and comparisons of many means using ANOVA.
8. Introduction to linear regression. An introduction to regression with two variables.
Instructions are also provided in several sections for using Casio and TI calculators.

We hope readers will take away three ideas from this book in addition to forming a foundation of statistical thinking and methods.

(1) Statistics is an applied field with a wide range of practical applications.

(2) You don't have to be a math guru to learn from interesting, real data.

(3) Data are messy, and statistical tools are imperfect. However, when you understand the strengths and weaknesses of these tools, you can use them to learn interesting things about the world.

Reviews available here: https://open.umn.edu/opentextbooks/textbooks/introductory-statistics-with-randomization-and-simulation-first-edition

We hope readers will take away three ideas from this book in addition to forming a foundation of statistical thinking and methods.

(1) Statistics is an applied field with a wide range of practical applications.

(2) You don't have to be a math guru to learn from interesting, real data.

(3) Data are messy, and statistical tools are imperfect. However, when you understand the strengths and weaknesses of these tools, you can use them to learn interesting things about the world.

OpenIntro Statistics is a dynamic take on the traditional curriculum, being successfully used at Community Colleges to the Ivy League

OpenIntro Statistics strives to be a complete introductory textbook of the highest caliber. Its core derives from the classic notions of statistics education and is extended by recent innovations. The textbook meets high quality standards and has been used at Princeton, Vanderbilt, UMass Amherst, and many other schools. We look forward to expanding the reach of the project and working with teachers from all colleges and schools.

Table of Contents
1 Introduction to data
2 Probability (special topic)
3 Distributions of random variables
4 Foundations for inference
5 Inference for numerical data
6 Inference for categorical data
7 Introduction to linear regression
8 Multiple and logistic regression

Access also available here: https://www.openintro.org/book/os/

Significant Statistics: An Introduction to Statistics was adapted and original content added by John Morgan Russell. It is adapted from content published by OpenStax Introductory Statistics, OpenIntro Statistics, and Introductory Statistics for the Life and Biomedical Sciences.

Significant Statistics: An Introduction to Statistics is intended for the 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. 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.

Instructors reviewing, adopting, or adapting this textbook, please help us understand your use by filling out this form: https://bit.ly/stat-interest.

Table of Contents:

Chapter 1: Sampling and Data
Chapter 2: Descriptive Statistics
Chapter 3: Basics of Probability
Chapter 4: Discrete Random Variables
Chapter 5: Continuous Random Variables
Chapter 6: Foundations of Inference
Chapter 7: Inference for One Sample
Chapter 8: Inference for Two Samples
Chapter 9: Simple Linear Regression
Class Group Activities