# Broadening Your Statistical Horizons

*Generalized Linear Models and Multilevel Models*

*2019-01-29*

# Preface

**Broadening Your Statistical Horizons (BYSH): Generalized Linear Models and Multilevel Models** is intended to be accessible to undergraduate students who have successfully completed a regression course through, for example, a textbook like *Stat2* (Cannon et al. 2019). We started teaching this course at St. Olaf in 2003 so students would be able to deal with the non-normal, correlated world we live in. It has been offered at St. Olaf every year since; in fact, it is required for all statistics concentrators. Even though there is no mathematical prerequisite, we still introduce fairly sophisticated topics such as likelihood theory, zero-inflated Poisson, and parametric bootstrapping in an intuitive and applied manner. We believe strongly in case studies featuring real data and real research questions; thus, most of the data in the textbook and available at our GitHub repo arises from collaborative research conducted by the authors and their students, or from student projects. Our goal is that, after working through this material, students will not necessarily be expert in these methods and associated theory, but that they will develop an expanded toolkit and a greater appreciation for the wider world of data and statistical modeling.

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

**Acknowledgements.** We would like to thank students of Stat 316 at St. Olaf College since 2010 for their patience as this book has taken shape with their feedback. We would especially like to thank these St. Olaf students for their summer research efforts which significantly improved aspects of this book: Cecilia Noecker, Anna Johanson, Nicole Bettes, Kiegan Rice, Anna Wall, Jack Wolf, and Josh Pelayo. Early editions of this book also benefitted greatly from feedback from instructors who used these materials in their classes, including Matt Beckman, Laura Boehm Vock, Beth Chance, Laura Chihara, Mine Dogucu, and Katie Ziegler-Graham. Finally, we have appreciated the support of two NSF grants (#DMS-1045015 and #DMS-0354308) and of our colleagues in Mathematics, Statistics, and Computer Science at St. Olaf.

### References

Cannon, Ann, George Cobb, Brad Hartlaub, Julie Legler, Robin Lock, Tom Moore, Allan Rossman, and Jeff Witmer. 2019. *Stat2: Modeling with Regression and Anova*. Macmillan.