JMM 2020

The SIGMAA Stat-Ed held two contributed paper sessions, one invited paper session, two minicourses and a panel discussion. Below are the available slides from the paper sessions and the panel.

Invited Paper Session

Modernizing the Introductory Statistics Course

• GAISE 2016 in action. Beverly Wood, Embry-Riddle Aeronautical University
• How technology facilitates modernizing intro stats. Patti Frazer Lock, St. Lawrence University
• Statistical inference via data science: A “tidy” approach. Albert Y. Kim, Smith College
• Stats for data science. Daniel Kaplan, Macalester College
• The p-value: Replacing 0.05 with understanding. Kari Lock Morgan, Pennsylvania State University
• Conceptual approaches to teaching multivariable statistical thinking: Using simulation methods and visualization. Beth Chance, Cal Poly – San Luis Obispo

Panel

So You Want to Start an Undergraduate Statistics or Data Science Program?

• Judith Canner, California State University, Monterey Bay
• Albert Y. Kim, Smith College
• Kimberly Roth, Juniata College
• Christopher Malone, Winona State University

Slides

Contributed Paper Sessions

Scholarship on Teaching and Learning Statistics

• Videos Lectures to Enhance Student Learning and Performance in an Online Elementary Statistics Course. Cathy M. Frey, Norwich University
• SOTL-driven evolution of a university probability course. J. Todd Lee, Elon University
• Study of Student Performance and Perceptions in Inverted Introductory Statistics. Reza O. Abbasian, Texas Lutheran University, Dept of Math and CS, Michael L Czuchry, Texas Lutheran University, Department of Psychology
• Modeling and Statistical Research with R. Leon Kaganovskiy, Touro College
• Using GeoGebra for Statistics. Heather Pierce, Emmanuel College
• Improving Student Ownership in Introductory Statistics Class through a Project-Based Approach. Vinodh Kumar Chellamuth, Dixie State University, Saint George, Utah

Data Across the Curriculum

• Data, History, and Design: Finding Common Ground in Contested Landscapes. McKenzie Lamb, Ripon College
• Teaching all the Math for Data Science, AI, and Beyond. Tyler J Jarvis, Brigham Young University
• Calculus Through a Data Lens: Broadening Scope Through Data and Modeling. Rachel Grotheer, Goucher College
• Calculus and Epidemics. Annela R Kelly, Regis College
• Using Atmospheric Data to Determine How Well a Separable ODE Models the Vertical Motion of a Dry Air Parcel. Chris Oehrlein, Oklahoma City Community College
• Using Smartphone Sensor Data in the Mathematics Classroom. Albert W Schueller, Whitman College
• Adding data analysis to a mathematical statistics course. Johanna N.Y. Franklin, Hofstra University