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    Priming and anchoring effects influence human perception in data visualization. Judgments of scatterplot class separability can change based on previously viewed visualizations.

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    Area of Science:

    • Human-Computer Interaction
    • Cognitive Psychology
    • Data Visualization

    Background:

    • Priming and anchoring effects describe how prior stimuli influence current judgments.
    • These cognitive phenomena can impact perceptual and cognitive tasks.
    • Understanding these effects is crucial for accurate interpretation of visual data.

    Purpose of the Study:

    • To investigate the presence and impact of priming and anchoring effects in data visualization.
    • To examine how prior visual stimuli affect judgments of class separability in scatterplots.
    • To provide empirical evidence for context-dependent perception in visualization tasks.

    Main Methods:

    • Conducted five experimental studies using scatterplots as the primary visualization type.
    • Manipulated the preceding visual stimuli presented to participants.
    • Measured participants' judgments of visual class separability.

    Main Results:

    • Confirmed the existence of priming and anchoring effects under specific conditions.
    • Demonstrated that the same scatterplot can be judged differently based on prior exposure.
    • Quantified the influence of preceding visualizations on perceptual judgments.

    Conclusions:

    • Priming and anchoring effects are demonstrably present in visualization perception.
    • These findings necessitate considering contextual influences in visualization design and analysis.
    • Future research should focus on modeling these perceptual biases for improved human-data interaction.