Don't Forget: Quantitative Statistics Courses Are Very Qualitative

• Activity Number: 456
• Type: Roundtables
• Date/Time: Wednesday, August 12, 2015 : 7:00 AM to 8:15 AM
• Sponsor: Section on Statistical Education
• Author(s): Leanna House* and Scotland Leman
• Companies: Virginia Tech and Virginia Tech
• Keywords: Education ; Visualization ; Analytics ; Assessment ; Undergraduate

Abstract

We are graduating students from statistics programs who do not know how to problemsolve. That is, when faced with analytical problems that do not conform to textbook constraints, statistics students flounder. They seem unable to phrase the problem in forms that make sense to them, assess what they know, make connections between what they know and the problem, work through problems incrementally, etc. All these tasks require qualitative forms of thinking that students do not practice enough, if at all, in current statistics classes. During this roundtable, we will propose a qualitative-quantitative-qualitative (QQQ) paradigm for developing statistical classes and lessons within. The first Q provides opportunities for students to practice assessing what is known and making conjectures; the second Q includes the application of analytical tools; and the third Q requires that students reflect, assess implications of their results, and make connections with other tools and applications. QQQ may apply at all statistics levels and may be assisted by the use of visual analytics.