Kyle Caudle, South Dakota School of Mines and Technology
Tuesday, June 28, 2016 - 2:00pm ET
This webinar will discuss an activity-based method for teaching permutation goodness of fit tests. Using statistical analysis and computer simulations, I will explore the possibility that the Gamemakers, those in charge of planning the Hunger Games, fixed the lottery. No previous knowledge of randomization tests will be required for this webinar – previous knowledge of basic hypothesis testing would be helpful.
William Finzer, Concord Consortium
Tuesday, June 14, 2016 - 2:00pm ET
The Common Online Data Analysis Platform (CODAP) is an online, free, and open source descendant of Fathom and TinkerPlots (though still far from a replacement for them). We’ll look at ways you can already use CODAP in the classroom and understand where ongoing development at Concord Consortium will take it.
Pamela Fellers, Grinnell College
Tuesday, April 26, 2016 - 2:00pm ET
Many statistics courses incorporate a final project into the semester which typically begins mid-semester with the bulk of the work in the last few weeks. These projects often involve content from the first few weeks of class which students sometimes struggle with application to their final projects (e.g. data collection, numerical and graphical summaries, etc.) This webinar will present an example of how a short-term project has been incorporated into the first few weeks of the class as a way of gaining additional exposure to these early concepts as well as preparing the students for their larger-scale final projects.
Amy Nowacki, Cleveland Clinic and Cleveland Clinic Lerner College of Medicine
Wednesday, November 18, 2015 - 12:00pm ET
Statistics courses that focus on data analysis in isolation, discounting the scientific inquiry process, may not motivate students to learn the subject. By involving students in other steps of the inquiry process, such as generating hypotheses and data, students may become more interested and vested in the analysis step. Additionally, such an approach might better prepare students to tackle real research questions outside of the statistics classroom. Presented here is a classroom activity utilizing the popular Hasbro board game Operation, which requires student involvement in the entire research process. Highlighted are ways this activity uncovers a number of research issues. A number of categorical and continuous variables are collected, making the activity amenable to a variety of statistical investigations and thus easy to imbed into any curriculum. Designed to mimic a real-world research scenario, this fun activity provides a guided yet flexible research experience from start to finish.
Allan Rossman and Beth Chance, Cal Poly - San Luis Obispo
Tuesday, October 27, 2015 - 2:00pm ET
We present an activity for introducing students to the concept of power and factors that influence power. The activity asks students to use a simulation-based approach, with an applet available here http://www.rossmanchance.com/applets/power.html to investigate how likely a baseball player would be to convince a manager that he has improved his probability of getting a hit.
Leigh M. Harrell-Williams, University of Memphis and Rebecca L. Pierce, Ball State University
Wednesday, October 21, 2015 - 12:00pm ET
Based on our March 2015 JSE paper "Identifying Statistical Concepts Associated with High and Low Levels of Self-Efficacy to Teach Statistics in Middle Grades,” we discuss the results of a Rasch modeling analysis of pre-service mathematics teacher responses to the middle grades Self-Efficacy to Teach Statistics (SETS) instrument. We share how we used Rasch measurement theory to develop the middle grades SETS instrument to measure pre-service teachers’ self-efficacy to teach topics at GAISE levels A and B as well as K–8 CCSSM statistics topics. SETS items ask teachers to rate their self-efficacy to teach a particular concept on a Likert scale from 1 (“not confident at all”) to 6 (“completely confident”). From data collected at four public institutions of higher education in the United States, we discuss what statistics topics pre-service teachers felt the most (or least) efficacious about and how that informs our continuing work.
Rob Erhardt and Michael Shuman, Wake Forest University
Wednesday, September 16, 2015 - 12:00pm ET
We describe the assistive technologies used to accommodate a blind student who took a second course in statistics at Wake Forest University. The course covered simple and multiple regression, model diagnostics, model selection, data visualization, and elementary logistic regression. These topics required that the student both interpret and produce three sets of materials: mathematical writing, computer programming, and visual displays of data. We relied heavily on integrating the use of multiple existing technologies. Specifically, this talk will detail the extensive use of screen readers, LaTeX, a modified use of R and the BrailleR package, a desktop Braille embosser, and a modified classroom approach.
Julie Clark (Hollins University), Lacey Echols (Butler University), Dave Klanderman (Trinity Christian College) and Laura Schultz (Rowan University), moderated by Nathan Tintle, Dordt College
Tuesday, September 8, 2015 - 12:00pm ET
In this webinar some recent new adopters of simulation-based inference (SBI) curricula will share their responses to questions such as: What made you switch to SBI from a traditional curriculum? What have you enjoyed most about the switch? What were some of the challenges in switching? What would you do different next time?
Ellen Gundlach, Purdue University
Wednesday, August 19, 2015 - 12:00pm ET
In this presentation, we will compare three delivery methods of an introductory statistical literacy course, all taught by the same instructor in the same semester for over 400 students. The complications of defining specific delivery methods and the pros and cons of choices of assessments will also be discussed.
Michelle Everson, The Ohio State University and Megan Mocko, University of Florida
Tuesday, July 7, 2015 - 12:00pm ET
In 2005, the Guidelines for Assessment and Instruction in Statistics Education (GAISE) College Report was endorsed by the American Statistical Association (ASA). Although the original six recommendations put forward in this report have stood the test of time, we now live in an increasingly data-centric world where our students have access to technologies that were not in existence in 2005. The ASA has therefore made it a priority to revise GAISE so that it continues to be easily and clearly applicable to modern-day teachers of introductory statistics courses. To accomplish this goal, a committee was formed and charged with the task of updating this landmark report. Two members of this committee will facilitate this webinar. In the webinar, we will reflect on how the landscape has changed in Statistics Education over the past 10 years, and we will discuss the process of updating and revising the GAISE report. The audience will have the opportunity to provide feedback and share ideas about the proposed revisions.