SLU Faculty presented at Joint Statistical Meetings
Several St. Lawrence University (SLU) faculty presented at the 2023 Joint Statistical Meeting in Toronto. The Joint Statistical Meeting is the largest gathering of statisticians in North America. Three SLU faculty gave presentations.
Patti Frazer Lock spoke on “Revising the College GAISE Report” with Jamis Perrett, Brigham Young University. GAISE stands for The Guidelines for Assessment and Instruction in Statistics Education and Dr. Frazer Lock currently co-chairs the committee to revise these guidelines.
Professor Robin Lock gave a talk entitled “SCORE Seminar: Undergraduates Producing Sports-related Educational Modules” about a seminar course taught at SLU. SCORE stands for Sports Content for Outreach, Research and Education and is the name of a National Science Foundation funded project (DUE 2142705) that is a collaboration between Carnegie Mellon University, Baylor University, West Point, University of Pittsburgh, Yale University and SLU (www.scorenetwork.org).
Professor Ivan Ramler also gave a talk, “Creating Statistics and Data Science Education Modules for the SCORE Network”, about developing pedagogical materials for inclusion in the SCORE repository of education materials.
Professor Jessica Chapman presented a poster, “Bringing IMDb to the Classroom”. This poster summarized strategies for effectively utilizing IMDb's extensive dataset (over 6 GB) in introductory statistics and data science courses by outlining available data, suggesting methods for data reduction, and providing insights into its current application in education.
Michael Schuckers attended JSM and served as Program Chair for the Statistics in Sports Section of the American Statistical Association, planning and organizing talks around the statistical analysis of sports data for the conference.
Patti Frazer Lock is a Professor of Mathematics and Statistics at St. Lawrence University. She is a co-author of Statistics: Unlocking the Power of Data by Lock, Lock, Lock, Lock, and Lock. She is also a co-author with Deb Hughes-Hallett’s Calculus Consortium of texts in Calculus, Multivariable Calculus, Applied Calculus, Pre-calculus, and College Algebra. She has chaired the SIGMAA on Statistics Education, has served on the ASA-MAA Joint Committee on Statistics Education, served on the Committee on the Undergraduate Program in Mathematics of the MAA, and chaired the Applied Data Analysis course report committee for the MAA Curriculum Guide. She is currently co-chairing the committee to revise the College GAISE report (Guidelines for Assessment and Instruction in Statistics Education) for the ASA. She has won numerous teaching and presentation awards. She is passionate about finding ways to help students succeed in and enjoy introductory courses in mathematics and statistics.
Dr. Robin Lock is a Professor of Statistics at St. Lawrence. He is a Fellow of the ASA, past Chair of the Joint Mathematical Association of America-ASA Committee on Teaching Statistics, a member of the Guidelines for Assessment and Instruction in Statistics Education (GAISE) development committee, and the inaugural winner of the Waller Distinguished Teaching Career Award in 2014. He has led numerous national workshops for faculty to develop a more modern approach to teaching statistics and he is co-author of two textbooks, one of which has pioneered the use of simulation-based inference for teaching introductory statistics. He developed the Datasets and Stories section of the Journal of Statistics Education to help instructors share interesting data and applications for teaching statistics and wrote the Statistical Sports fan column for several years in Stats: The Magazine for Students of Statistics. In 2004, he was awarded both the Mu Sigma Rho Statistics Education Award for ``excellence in undergraduate or graduate statistical education at the institutional, regional, or national level" and the ASA's Statistics in Sports Section Significant Contributor Award.
Ivan Ramler is the Jack and Sylvia Burry Associate Professor of Statistics at St. Lawrence University and holds a Ph.D. and M.S. in Statistics from Iowa State University. Ramler’s academic interests involves applying statistical and machine learning methods to environment and ecology data, as well as in sports and esports (i.e., competitive video games). He teaches many of St. Lawrence’s statistics and data science courses and regularly mentors students through the Liberal Arts Scholars Program, CSTEP & McNair programs, and the St. Lawrence Fellowship program.