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StatWire: Visual Flow-based Statistical Programming


Subramanian, Krishna; Maas, Johannes; Ellers, Michael; Wacharamanotham, Chat; Voelker, Simon; Borchers, Jan (2018). StatWire: Visual Flow-based Statistical Programming. In: Extended Abstracts of the 2018 CHI Conference on Human Factors in Computing Systems, Montreal QC, Canada, 21 April 2018 - 26 April 2018, LBW104:1-LBW104:6.

Abstract

Statistical analysis is a frequent task in several research fields such as HCI, Psychology, and Medicine. Performing statistical analysis using traditional textual programming languages like R is considered to have several advantages over GUI applications like SPSS. However, our examination of 40 analysis scripts written using current IDEs for R shows that such scripts are hard to understand and maintain, limiting their replication. We present StatWire, an IDE for R that closely integrates the traditional text-based editor with a visual data flow editor to better support statistical programming. A preliminary evaluation with four R users indicates that this hybrid approach could result in statistical programming that is more understandable and efficient.

Abstract

Statistical analysis is a frequent task in several research fields such as HCI, Psychology, and Medicine. Performing statistical analysis using traditional textual programming languages like R is considered to have several advantages over GUI applications like SPSS. However, our examination of 40 analysis scripts written using current IDEs for R shows that such scripts are hard to understand and maintain, limiting their replication. We present StatWire, an IDE for R that closely integrates the traditional text-based editor with a visual data flow editor to better support statistical programming. A preliminary evaluation with four R users indicates that this hybrid approach could result in statistical programming that is more understandable and efficient.

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Additional indexing

Item Type:Conference or Workshop Item (Paper), refereed, original work
Communities & Collections:03 Faculty of Economics > Department of Informatics
Dewey Decimal Classification:000 Computer science, knowledge & systems
Language:English
Event End Date:26 April 2018
Deposited On:30 Aug 2018 07:44
Last Modified:24 Sep 2019 23:35
Publisher:ACM
Series Name:CHI EA '18
OA Status:Green
Other Identification Number:merlin-id:16710

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