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From Clicks to Conversations: Evaluating the Effectiveness of Conversational Agents in Statistical Analysis.

Title: From Clicks to Conversations: Evaluating the Effectiveness of Conversational Agents in Statistical Analysis.
Authors: Wen, Qifu; Kochhar, Prishita; Zeyada, Sherif; Javaheri, Tahereh; Rawassizadeh, Reza
Source: International Journal of Human-Computer Interaction; Jun2026, Vol. 42 Issue 11, p7832-7849, 18p
Subject Terms: STATISTICS; STATISTICAL accuracy; USER experience; DATA science; GRAPHICAL user interfaces; TASK performance; SATISFACTION; CHATBOTS
Abstract: The rapid evolution of data science forced individuals with different backgrounds to adapt to statistical analysis. We hypothesize that conversational agents are better suited for statistical analysis than traditional graphical user interfaces (GUI). In this work, we propose a novel conversational agent, StatZ, for statistical analysis. We evaluate StatZ relative to statistical software—SPSS, SAS, Stata, and JMP—in terms of accuracy, task completion time, user experience, and user satisfaction. We experimented with 51 participants from diverse backgrounds with proposed analysis question.Our design assessed each participant's ability to perform statistical tasks using GUI-based tools and our conversational agent. Results indicate that conversational agents significantly outperform GUI statistical software in all assessed metrics, including quantitative (task completion time, accuracy, and user experience), and qualitative (user satisfaction). Our findings underscore the potential of conversational agents to enhance statistical analysis, reducing cognitive load and learning curves enabling data analysis capabilities. [ABSTRACT FROM AUTHOR]
: Copyright of International Journal of Human-Computer Interaction is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Complementary Index