Cover Image

A Survey on Large Language Model-based Agents for Statistics and Data Science

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Sun, Maojun, Han, Ruijian, Jiang, Binyan, Qi, Houduo, Sun, Defeng, Yuan, Yancheng, Huang, Jian
Format:	Preprint
Published:	2024
Subjects:	Artificial Intelligence Computation and Language Machine Learning Other Statistics
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

LAMBDA: A Large Model Based Data Agent
by: Sun, Maojun, et al.
Published: (2024)

DSAEval: Evaluating Data Science Agents on a Wide Range of Real-World Data Science Problems
by: Sun, Maojun, et al.
Published: (2026)

DARE: Aligning LLM Agents with the R Statistical Ecosystem via Distribution-Aware Retrieval
by: Sun, Maojun, et al.
Published: (2026)

Framework for Accessible and Inclusive Teaching Materials for Statistics and Data Science Courses
by: Dogucu, Mine, et al.
Published: (2021)

Cognitive Constructivism and the Epistemic Significance of Sharp Statistical Hypotheses in Natural Sciences
by: Stern, J. M.
Published: (2010)

Random Text, Zipf's Law, Critical Length,and Implications for Large Language Models
by: Berman, Vladimir
Published: (2025)

Towards a Unified Framework for Statistical and Mathematical Modeling
by: Zivich, Paul N
Published: (2025)

Making Uncertainty Visible: Multiverse Analysis for Robust Computational Social Science
by: Linde, Maximilian, et al.
Published: (2026)

Advancing Employee Behavior Analysis through Synthetic Data: Leveraging ABMs, GANs, and Statistical Models for Enhanced Organizational Efficiency
by: Jayashankar, Rakshitha, et al.
Published: (2024)

A Survey: Potential Dimensionality Reduction Methods
by: Chang, Yuan-chin Ivan
Published: (2025)

Philosophy within Data Science Ethics Courses
by: Colando, Sara, et al.
Published: (2023)

A Mathematical Lens for Teaching Data Science
by: Hardin, Johanna
Published: (2025)

Statistics 101, 201, and 202: Three Shiny Apps for Teaching Probability Distributions, Inferential Statistics, and Simple Linear Regression
by: Soetewey, Antoine
Published: (2026)

Which Type of Statistical Uncertainty Helps Evidence-Based Policymaking? An Insight from a Survey Experiment in Ireland
by: Suzuki, Akisato
Published: (2021)

Understanding Pedagogical Content Knowledge of Data Science Instructors: An Inaugural Framework
by: Demirci, Sinem, et al.
Published: (2025)

A Systematic Literature Review of Undergraduate Data Science Education Research
by: Dogucu, Mine, et al.
Published: (2024)

Near-Peer Mentoring in Data Science: A Plot for Mutual Growth
by: Sabatti, Chiara, et al.
Published: (2022)

Data Jamboree: A Party of Open-Source Software Solving Real-World Data Science Problems
by: McGowan, Lucy D'Agostino, et al.
Published: (2025)

Perceptions and Utilization of GenAI Tools among Data Science Students and Faculty
by: Hasan, Abeer M., et al.
Published: (2026)

The Need for a Recurring Large-Scale Benchmarking Survey to Continually Evaluate Sampling Methods and Administration Modes: Lessons from the 2022 Collaborative Midterm Survey
by: Enns, Peter K., et al.
Published: (2024)

Internalist Reliabilism in Statistics and Machine Learning: Thoughts on Jun Otsuka's Thinking about Statistics
by: Lin, Hanti
Published: (2024)

A Bureaucratic Theory of Statistics
by: Recht, Benjamin
Published: (2025)

The Design and Implementation of a Bayesian Data Analysis Lesson for Pre-Service Mathematics and Science Teachers
by: Dogucu, Mine, et al.
Published: (2023)

Statistical Compatibility, Refutational Information, and Acceptability
by: Rovetta, Alessandro
Published: (2026)

Statistical Methodology Groups in the Pharmaceutical Industry
by: Devenport, Jenny, et al.
Published: (2026)

My Statistics is Better than Yours
by: Benhaïem, Simon
Published: (2024)

Statistics at a Crossroads; Who is for the Challenge?
by: He, Xuming, et al.
Published: (2025)

A Statistical Case Against Empirical Human-AI Alignment
by: Rodemann, Julian, et al.
Published: (2025)

An empirical exploration of the diversified R ecosystem
by: Huang, Tian-Yuan, et al.
Published: (2022)

Reflections on the Future of Statistics Education in a Technological Era
by: Alexander, Craig, et al.
Published: (2026)

Statistical estimation of $π$: varying choices over dimensions
by: Bhattacharjee, Syon, et al.
Published: (2025)

The Future of Data Science Education
by: Wright, Brian, et al.
Published: (2024)

Generative AI for Data Science 101: Coding Without Learning To Code
by: Bien, Jacob, et al.
Published: (2024)

LLteacher: A Tool for the Integration of Generative AI into Statistics Assignments
by: Furfaro, Emanuela, et al.
Published: (2025)

Integrating Deep Learning and Spatial Statistics in Marine Ecosystem Monitoring
by: Sangiovanni, Gian Mario, et al.
Published: (2025)

Beyond Correctness: Evaluating and Improving LLM Feedback in Statistical Education
by: Ippisch, Niklas, et al.
Published: (2025)

Survey Data Integration for Distribution Function Estimation
by: Flood, Jeremy, et al.
Published: (2024)

More than Formulas -- Integrity, Communication, Computing and Reproducibility in Statistics Education
by: Furrer, Eva, et al.
Published: (2024)

Factors Associated with Unit-Specific Failure in a University-Level Statistics Course
by: Sierra, Biviana Marcela Suarez
Published: (2025)

Developing Consistency Among Undergraduate Graders Scoring Open-Ended Statistics Tasks
by: Beckman, Matthew D., et al.
Published: (2024)