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A Validated Visual Decision-Support Tool for Inferential Statistical Test Selection: The Velarde-Camaqui Diagram (#2371)

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Date of Conference

July 15-17, 2026

Published In

"Engineering without Borders: Artificial Intelligence, Knowledge, Innovation, and Alliances for a Future from the Americas"

Location of Conference

Santiago (Chile)

Authors

Velarde-Camaqui, Davis

Lopez-Caudana, Edgar Omar

Valerio-Ureña, Gabriel

Ramirez-Montoya, Maria-Soledad

Pelaez-Sanchez, Iris Cristina

Alvarez-Icaza Longoria, Ines

Abstract

Selecting the correct statistical test is a frequent challenge for students and researchers with limited mathematical backgrounds. Incorrect choices can undermine analytical rigor and threaten research validity. This study presents the design and expert validation of the Velarde-Camaqui Diagram, a visual decision-support tool that guides users in selecting inferential statistical tests. A mixed-methods validation was conducted with 14 PhD experts in education and statistics from several countries. Experts assessed clarity, coherence, relevance, and usability using a 12-item Likert-scale questionnaire (1–3) and provided qualitative feedback. Quantitative analysis revealed high acceptance rates (93–100%), confirming strong perceived relevance, while coherence for correlations and associations scored lowest (85%), indicating room for structural refinement. Qualitative feedback suggested improvements in color coding, visual hierarchy, and instructional clarity. Overall, the results provide initial evidence supporting the diagram’s content validity and perceived usability as a structured aid for statistical decision-making in higher education.

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