Abstract
Research and development in computer science and statistics have produced increasingly sophisticated software interfaces for interactive and exploratory analysis, optimized for easy pattern finding and data exposure. But design philosophies that emphasize exploration over other phases of analysis risk confusing a need for flexibility with a conclusion that exploratory visual analysis is inherently âmodel freeâ and cannot be formalized. We describe how without a grounding in theories of human statistical inference, research in exploratory visual analysis can lead to contradictory interface objectives and representations of uncertainty that can discourage users from drawing valid inferences. We discuss how the concept of a model check in a Bayesian statistical framework unites exploratory and confirmatory analysis, and how this understanding relates to other proposed theories of graphical inference. Viewing interactive analysis as driven by model checks suggests new directions for software and empirical research around exploratory and visual analysis. For example, systems might enable specifying and explicitly comparing data to null and other reference distributions and better representations of uncertainty. Implications of Bayesian and other theories of graphical inference can be tested against outcomes of interactive analysis by people to drive theory development.
Highlights
IntroductionIt may seem quite obvious that if you are doing data analysis, the interface you use should above all prioritize representation and easy access to the data
A key question that often remains unstated in research in interactive visual analysis is: How much of the statistical inference process that an analyst engages in should be left implicit in order to preserve cognitive load? We acknowledge that it is difficult to answer this question without first making concerted attempts in research to realize the forms of integration we describe above
We propose a research program that pursues a tighter integration between models, graphics, and data querying, motivated by a view of interactive analysis as a process of users comparing intuitive pseudo-statistical models to data via model checks
Summary
It may seem quite obvious that if you are doing data analysis, the interface you use should above all prioritize representation and easy access to the data This way of thinking owes much of its motivation to the exploratory data analysis movement pioneered by John Tukey in the 1960s. Tukey (1962) popularized the idea of exploratory data analysis (EDA) as a natural complement to confirmatory data analysis (CDA), writing: “The simple graph has brought more information to the data analyst’s mind than any other device. It specializes in providing indications of unexpected phenomena.”. The proposal of EDA is memorable in part because he directly addressed a tension between the flexibility in thinking required to learn from one’s data through construction of graphiSyntax Error (1040505): Dictionary key must be a name object
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