Measuring Lineup Difficulty By Matching Distance Metrics With Subject Choices in Crowd-Sourced Data

DOI10.1080/10618600.2017.1356323OpenAlexW2736329022WikidataQ63346903 ScholiaQ63346903MaRDI QIDQ3391137

Niladri Roy Chowdhury, Dianne Cook, Mahbubul Majumder, Heike Hofmann

Publication date: 28 March 2022

Published in: Journal of Computational and Graphical Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/10618600.2017.1356323

zbMATH Keywords

data miningexploratory data analysisinformation visualizationdata sciencestatistical graphicsdata visualizationdistance metricscognitive perceptionvisual inference

Mathematics Subject Classification ID

Statistics (62-XX)

Uses Software

• ggplot2
• knitr

Cites Work

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• Using visual statistical inference to better understand random class separations in high dimension, low sample size data
• Validation of Visual Statistical Inference, Applied to Linear Models
• Statistical inference for exploratory data analysis and model diagnostics
• Error Detecting and Error Correcting Codes
• Visual Error Criteria for Qualitative Smoothing
• An analysis of variance test for normality (complete samples)

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