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Abstract Details
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Activity Number:
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561
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Type:
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Topic Contributed
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Date/Time:
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Wednesday, August 3, 2011 : 2:00 PM to 3:50 PM
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Sponsor:
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Section on Statistical Graphics
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| Abstract - #301759 |
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Title:
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Visual Statistical Inference for Regression Parameters
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Author(s):
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Mahbubul Amin Majumder*+ and Heike Hofmann and Dianne Cook
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Companies:
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Iowa State University and Iowa State University and Iowa State University
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Address:
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1418 Snedecor Hall, Ames, IA, 50010, USA
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Keywords:
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Statistical graphics ;
Visual inference
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Abstract:
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Statistical graphics play a crucial role in exploratory data analysis, model checking and diagnosis. Until recently there were no formal visual methods in place for determining statistical significance of findings. This changed, when Buja et al.(2009) conceptually introduced two protocols for formal tests of visual findings. In this paper we take this a step further by comparing the lineup protocol (Buja et al.2009) against classical statistical testing of the significance of regression model parameters. A human subjects experiment is conducted using simulated data to provide controlled conditions. Results suggest that the lineup protocol provides results equivalent to the uniformly most powerful (UMP) test and for some scenarios yields better power than the UMP test.
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