This book consists of problems which were adapted from an introductory-level statistics course. We aimed  to improve accessibility and rewrite problems which reinforced gender binary, white supremacy, or ageism or were otherwise exclusionary or culturally irrelevant to students.

Our work was supported by the Remixing Open Textbooks through an Equity Lens (ROTEL) project, which is funded by a U.S. federal grant through The Open Textbook Pilot program. Our goal was to sift through the homework sets we currently use to teach Applied Statistics, an introductory course in statistics at Fitchburg State University, and rewrite any problems which were not accessible or did not promote equity and inclusion. The students at Fitchburg State University are racially diverse; approximately 10% of students are Hispanic or Latino, and 10% are Black or African American. About 45% of students are enrolled full-time, more than 40% of which are Pell Grant recipients and many of whom work at least part-time.

The problems in this project originated from WeBWorK (https://openwebwork.org), an open-source online homework platform in which students answer questions in an interactive manner. Problems are randomized for individual students and, for nearly all problems, students receive immediate feedback about their answers. There are over 55,000 problems in the current library that have been written by mathematicians, statisticians and other scientists across the world.

We began with the homework sets on WeBWorK that we currently use when we teach Applied Statistics. We read every problem, keeping a watchful eye on  the following aspects:

• Accessibility. WeBWorK is web-based, and extensive work has been done to promote accessibility online. However, individual problems need to be examined to make sure they comply with current accessibility standards.
• Correct use of language promoting diversity, equity, and inclusivity. We sought to improve problems that used antiquated notions of gender, propagated stereotypes, reinforced eurocentrism, or were otherwise outdated or exclusionary.

Out of 90 problems, we identified 39 problems that fell short in terms of accessibility or diversity, equity, and inclusivity. We revised these problems, and they have been included in this book. We normally use these problems as a companion to the OpenStax textbook Introductory Statistics by Barbara Illowsky and Susan Dean. As such, the numbering and titles of the problem sets align with the sections of the textbook. However, these problems may be used to supplement or replace existing course materials for any introductory statistics course to make the content more inclusive and culturally relevant to students.

The most common way we improved accessibility was to provide alternate text for embedded graphics so that students with visual impairments can access the problems. There were several ways we changed the language in problems to promote diversity, equity, and inclusion. They ran the gamut from rewriting the entire problem to changing the names and pronouns of the people in the problem.

In fact, changing the names and pronouns of the people in a problem was an important aspect of this project. We updated an existing code, called a macro, that chooses names randomly to draw from a more diverse set of names. We also added pronoun information to each name, assuring that about 5-10% of persons in the macro had nonbinary pronouns. In the end, our code allows different versions of the same problem to appear for different users, and in each version the name, pronouns (subject, object, and possessive forms), and verb forms all agree and sound natural. For example, one version of a problem may read, “Amelia has a ribbon that is 22cm long. If she cuts off 6cm, how much does she have left?” We include this example here because problems for which our only change was names and pronouns are not included in this book. In May 2023, this macro was accepted into the WeBWorK codebase for others to use as well.

When a version of a problem is generated on WeBWorK, the version is usually generated with random values for the variables and random names and pronouns, as seen at the end of the previous paragraph. Due to the nature of this publication, however, the problems in this document are a single version of those actually used in courses. If you use the problems on the WeBWorK platform, a randomized version will be generated for each student, adding to the diversity of identities represented in the problems. We invite you to contact one of us (Peter Staab, pstaab@fitchburgstate.edu) for help if you decide to use these problems in a course to ensure that you get the most out of them.

About the Authors

Peter Staab teaches at Fitchburg State University in Massachusetts. He has been using/developing OER for 15 years, long before he knew the term. He comes to this diversity and equity project with a desire for his students, who are increasingly coming to campus with diverse backgrounds. In addition, he looks toward the future as his children, both adopted and African-American, continue through middle and high school and their peer groups are quite diverse in economic, gender and racial background.

Rachael Norton taught mathematics at Fitchburg State University for three years. She greatly enjoyed belonging to a rare, majority female, mathematics department at FSU, but she and her husband ultimately decided to relocate to be closer to family. She now teaches at St. Olaf College in southern Minnesota. She lives in the Twin Cities, a vibrant and diverse community with a high percentage of East Africans, two of whom are her husband and son. On Thursdays, you can find Rachael and her family eating delicious home-made Ethiopian food at her mother-in-law’s house.

Acknowledgments

We want to thank a few people who have been instrumental in getting this project over the finish line. Rachel Graddy, who was the Director of Disability Services at Fitchburg State University, reviewed all problems for accessibility. Junior Peña, Director of Student Diversity, Equity, & Belonging Programs at Fitchburg State University, reviewed all of the problems for DEI language. Both Junior and Rachel gave us crucial feedback to improve this project. Alex Jordan helped tremendously with the random name macro, and Jackie Kremer has been an overall leader at Fitchburg State with ROTEL and a cheerleader for all of us. Lastly, we thank the statewide ROTEL staff for supporting us in the finishing touches, polishing the text, and keeping us organized to the end.