"Rising textbook costs are a potential barrier to student progression and retention. Therefore, a group of faculty in the department of Mathematics at Augusta University has decided to adopt an open textbook for use in an Elementary Statistics course.

We have developed a set of materials to accompany the OpenStax Introductory Statistics textbook by Illowsky and Dean including lecture/study notes and projects.

These materials are meant as a supplement for teachers and learners who are using the OpenStax Introductory Statistics textbook by Illowsky and Dean. These materials also incorporate the use of other technologies (R and Excel) in an open statistics course for students and instructors who wish to use technologies other than the TI-83/84 graphing calcuator."

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.

This course materials are for General Education course Introduction to Statistics. The contents include data collection, frequency distributions, probability and probability distributions, sampling and sampling distributions, hypothesis testing with applications in various fields, regression and correlation analysis.

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. A separate document is provided on the website with examples in
SPSS.

Students new to statistics are sure to benefit from this fully ADA accessible and relevant textbook. The examples resonate with everyday life, the text is approachable, and has a conversational tone to provide an inclusive and easy to read format for students.

This textbook incorporates the compilation of my notes over the years teaching introductory probability and statistics courses used to expand and enhance upon the open educational resource Statistics Using Technology by Kathryn Kozak, with some additional material adapted from OpenIntro Statistics by Diez,
Barr, and Çetinkaya-Rundel. Both texts are licensed under CC BY-SA 4.0. This textbook, except for the cover art, is licensed under a Creative Commons Attribution-Share Alike 4.0 International License (CCBY-SA 4.0).

Review and content editing by Jennifer Ward. Recommended definition edits and glossary terms by Dr. Naghmeh Daneshi. Alternative text for images provided by Whitney Cave. Additional exercises from Whitney Cave and from MyOpenMath: https://www.myopenmath.com/. Copy editing by Walter Benson. Cover art by James Tadlock https://www.artstation.com/redhedron.

For instructors, there is a complete solution manual and two companion online homework courses. An adaptive learning system called Realizeit which has content from the text, videos and homework problems. A free MyOpenMath course with problems divided by chapter. Email Rachel Webb for more information.

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.

This resource contains a news article, a facilitation guide, and two activity handouts. Students flip coins, gather and analize data, and gain an appreciation for the challenge of generating truly random data. Then the students are guided through forming a statistical hypothesis, gathering and analyzing evidence, and interpreting their analysis using p-values. The lesson ends with a discussion of Benford’s Law. This activity aligns with MATH 1342 Learning Outcome 8: Perform hypothesis testing using statistical methods.

This resource contains a news article and a facilitation guide. Students practice data analysis and review the point-slope form of a line. This activity aligns with MATH 1342 Learning Outcome 2: Recognize, examine and interpret the basic principles of describing and presenting data

This is a new approach to an introductory statistical inference textbook, motivated by probability theory as logic. It is targeted to the typical Statistics 101 college student, and covers the topics typically covered in the first semester of such a course. It is freely available under the Creative Commons License, and includes a software library in Python for making some of the calculations and visualizations easier.

This is a list of terms and their definitions related to statistics provided by the Australian Bureau of Statistics, an organ of the government of the Commonwealth of Australia.

Statistical thinking is a way of understanding a complex world by describing it in relatively simple terms that nonetheless capture essential aspects of its structure, and that also provide us some idea of how uncertain we are about our knowledge. The foundations of statistical thinking come primarily from mathematics and statistics, but also from computer science, psychology, and other fields of study.

Introductory statistics course developed through the Ohio Department of Higher Education OER Innovation Grant. The course is part of the Ohio Transfer Module and is also named TMM010. For more information about credit transfer between Ohio colleges and universities please visit: www.ohiohighered.org/transfer.

This resource is an authored, remixed library of statistical content. The content includes Campus Bookshelves, Bookshelves, and Learning Objects.

I hope you find this book useful in teaching statistics. When writing this book, I tried to follow the GAISE Standards (GAISE recommendations. (2014, January 05). Retrieved from http://www.amstat.org/education/gaise/GAISECollege_Recommendations.pdf), which are:

1.) Emphasis statistical literacy and develop statistical understanding.
2.) Use real data.
3.) Stress conceptual understanding, rather than mere knowledge of procedure.
4.) Foster active learning in the classroom.
5.) Use technology for developing concepts and analyzing data.

To this end, I ask students to interpret the results of their calculations. I incorporated the use of technology for most calculations. Because of that you will not find me using any of the computational formulas for standard deviations or correlation and regression since I prefer students understand the concept of these quantities. Also, because I utilize technology you will not find the standard normal table, Student’s t-table, binomial table, chi-square distribution table, and F-distribution table in the book. The only tables I provided were for critical values for confidence intervals since they are more difficult to find using technology. Another difference between this book and other statistics books is the order of hypothesis testing and confidence intervals. Most books present confidence intervals first and then hypothesis tests. I find that presenting hypothesis testing first and then confidence intervals is more understandable for students. Lastly, I have deemphasized the use of the z-test. In fact, I only use it to introduce hypothesis testing, and never utilize it again. You may also notice that when I introduced hypothesis testing and confidence intervals, proportions were introduced before means. However, when two sample tests and confidence intervals are introduced I switched this order. This is because usually many instructors do not discuss the proportions for two samples. However, you might try assigning problems for proportions without discussing it in class. After doing two samples for means, the proportions are similar. Lastly, to aid student understanding and interest, most of the homework and examples utilize real data. Again, I hope you find this book useful for your introductory statistics class.

I want to make a comment about the mathematical knowledge that I assumed the students possess. The course for which I wrote this book has a higher prerequisite than most introductory statistics books. However, I do feel that students can read and understand this book as long as they have had basic algebra and can substitute numbers into formulas. I do not show how to create most of the graphs, but most students should have been exposed to them in high school. So I hope the mathematical level is appropriate for your course.

The technology that I utilized for creating the graphs was Microsoft Excel, and I utilized the TI-83/84 graphing calculator for most calculations, including hypothesis testing, confidence intervals, and probability distributions. This is because these tools are readily available to my students. Please feel free to use any other technology that is more appropriate for your students. Do make sure that you use some technology.

These open-source mathematics homework problems are programmed for the WeBWorK mathematics platform and correspond to chapters in OpenStax Introductory Statistics. They were created through a Round Eight Textbook Transformation Grant.