Document Detail


Statistical inference for exploratory data analysis and model diagnostics.
MedLine Citation:
PMID:  19805449     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
We propose to furnish visual statistical methods with an inferential framework and protocol, modelled on confirmatory statistical testing. In this framework, plots take on the role of test statistics, and human cognition the role of statistical tests. Statistical significance of 'discoveries' is measured by having the human viewer compare the plot of the real dataset with collections of plots of simulated datasets. A simple but rigorous protocol that provides inferential validity is modelled after the 'lineup' popular from criminal legal procedures. Another protocol modelled after the 'Rorschach' inkblot test, well known from (pop-)psychology, will help analysts acclimatize to random variability before being exposed to the plot of the real data. The proposed protocols will be useful for exploratory data analysis, with reference datasets simulated by using a null assumption that structure is absent. The framework is also useful for model diagnostics in which case reference datasets are simulated from the model in question. This latter point follows up on previous proposals. Adopting the protocols will mean an adjustment in working procedures for data analysts, adding more rigour, and teachers might find that incorporating these protocols into the curriculum improves their students' statistical thinking.
Authors:
Andreas Buja; Dianne Cook; Heike Hofmann; Michael Lawrence; Eun-Kyung Lee; Deborah F Swayne; Hadley Wickham
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Publication Detail:
Type:  Journal Article; Research Support, U.S. Gov't, Non-P.H.S.    
Journal Detail:
Title:  Philosophical transactions. Series A, Mathematical, physical, and engineering sciences     Volume:  367     ISSN:  1364-503X     ISO Abbreviation:  Philos Trans A Math Phys Eng Sci     Publication Date:  2009 Nov 
Date Detail:
Created Date:  2009-10-06     Completed Date:  2010-01-29     Revised Date:  2013-04-24    
Medline Journal Info:
Nlm Unique ID:  101133385     Medline TA:  Philos Trans A Math Phys Eng Sci     Country:  England    
Other Details:
Languages:  eng     Pagination:  4361-83     Citation Subset:  IM    
Affiliation:
Wharton School, University of Pennsylvania, Philadelphia, PA 19104, USA.
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MeSH Terms
Descriptor/Qualifier:
Data Interpretation, Statistical*
Housing / statistics & numerical data
Humans
Models, Theoretical*

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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