On this episode, Dr. Mary Ellen Dello Stritto is joined by Patrick Aldrich. Patrick received his bachelor’s degree in Wildlife biology and a minor in Entomology from the University of California, Davis. After graduation, he spent 5 years in various field biology positions, studying a wide array subjects from Bowerbird mating systems in Australia to integrated pest management of ground squirrels in Northern California. He subsequently decided to return to school to pursue a PhD at the University of Hawaii, Manoa, where he studied the spatio-temporal variation of pollination networks in Hawaiian tropical dry forests. Following his graduate work, he was the project director for a project that used spatial analyses to study the random correspondence of fingerprint patterns. Through his work, he has acquired extensive experience in biostatistics. He is currently the data manager and statistician for the Oregon Quality Rating and Improvement System for early childhood and other projects at The Research Institute at Western Oregon University. He continues to apply parametric, non-parametric and likelihood methodologies to analyze various datasets associated with early childhood and educational research. Segment 1: Parametric vs. Non-parametric statistical tests [00:00-18:52] In this first segment, Patrick discusses the differences between parametric and non-parametric statistical tests and the best practices for using non-parametric tests. In this segment, the following resources are mentioned: RIA # 91: Dr. Mary Ellen Dello Stritto and Dr. William D. Marelich on the Applied Quantitative Perspective Segment 2: Using non-parametric tests [18:53-33:31] In segment two, Patrick discusses how he uses non-parametric statistical tests in his research and how other researchers have used them. In this segment, the following resources are mentioned: Anderson, M. J. (2001). A new method for non-parametric multivariate analysis. Austral Ecology 26, 32-46. Oregon’s Quality Rating Improvement System (QRIS) Mann-Whitney U test Additional resources on non-parametric statistics: Wasserman, Larry (2007). All of nonparametric statistics. New York: Springer. Conover, W. J. (1999). Practical nonparametric statistics (3rd ed.). New York: John Wiley & Sons, Inc. Siegel, S. & Castellan Jr., N. J. (1989). Nonparametric statistics for the behavioral sciences (2nd ed.). McGraw-Hill. To share feedback about this podcast episode, ask questions that could be featured in a future episode, or to share research-related resources, post a comment below or contact the “Research in Action” podcast: Twitter: @RIA_podcast or #RIA_podcast Email: [email protected] Voicemail: 541-737-1111 If you listen to the podcast via iTunes, please consider leaving us a review. The views expressed by guests on the Research in Action podcast do not necessarily represent the views of Oregon State University Ecampus or Oregon State University.