Lessons Learned and Data Resources for Quantitative Analysis and Statistics Instruction

Robert Andrews

Virginia Commonwealth University

This presenter did not provide a biography.

William Miller

Georgia College

This presenter did not provide a biography.

Chris Lowery

Georgia College

This presenter did not provide a biography.

Ping Wang

James Madison University

This presenter did not provide a biography.

Binshan Lin

Louisiana State University Shreveport

Dr. Binshan Lin is the BellSouth Professor at Louisiana State University in Shreveport. He received his Ph.D. from the Louisiana State University in 1988.  He is a nine-time recipient of the Outstanding Faculty Award at LSUS. Professor Lin received the Computer Educator of the Year by the International Association for Computer Information Systems (IACIS) in 2005, Ben Bauman Award for Excellence in IACIS 2003, IACIS Directors’ Award in 2012, Distinguished Service Award at the Southwest Decision Sciences Institute (SWDSI) in 2007, Outstanding Educator Award at the SWDSI in 2004, and Emerald Literati Club Awards for Excellence in 2003. Dr. Lin has published over 270 articles in refereed journals.  Currently he serves as Editor-in-Chief of Expert Systems with Applications. Professor Lin served as President of SWDSI (2004-2005) and Program Chair of IACIS Pacific 2005 Conference. He also served as a vice president (2007-2009; 2010-2012) of Decision Sciences Institute (DSI). 

Abstract

Presenters share the knowledge they have learned from quantitative analysis and statistics classes taught traditionally and online.  The session will address suggestions for engaging students and encouraging learning as well... [ view full abstract ]

Authors

Robert Andrews (Virginia Commonwealth University), William Miller (Georgia College), Chris Lowery (Georgia College), Ping Wang (James Madison University), Binshan Lin (Louisiana State University Shreveport)

Topic Area

Topics: Data, Analytics and Statistics Instruction (DASI)

Session

DA1 » Lessons Learned and Data Resources for Quantitative Analysis and Statistics Instruction (08:45 - Thursday, 23rd February, Edisto)

Paper

Effective_use_of_Software_for_Statistics_Instruction.pdf

Presentation Files

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