From Clicks to Conversations: Evaluating the Effectiveness of Conversational Agents in Statistical Analysis
Qifu Wen, Prishita Kochhar, Sherif Zeyada, Tahereh Javaheri, Reza, Rawassizadeh

TL;DR
This study introduces StatZ, a conversational agent for statistical analysis, which outperforms traditional GUI-based software in accuracy, efficiency, and user satisfaction across diverse user backgrounds.
Contribution
The paper presents a novel conversational agent, StatZ, and empirically evaluates its effectiveness against established statistical software, demonstrating significant improvements.
Findings
StatZ significantly reduces task completion time.
StatZ improves accuracy in statistical tasks.
Users report higher satisfaction with StatZ.
Abstract
The rapid proliferation of data science forced different groups of 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 the efficacy of StatZ relative to established statistical software:SPSS, SAS, Stata, and JMP in terms of accuracy, task completion time, user experience, and user satisfaction. We combined the proposed analysis question from state-of-the-art language models with suggestions from statistical analysis experts and tested with 51 participants from diverse backgrounds. Our experimental design assessed each participant's ability to perform statistical analysis tasks using traditional statistical analysis tools with GUI and…
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Taxonomy
TopicsData Visualization and Analytics · Data Analysis with R · Data Mining Algorithms and Applications
