AI and Statistics: An Examination of the Capabilities of AI Models to Perform Data Science
Location
Room 232, Schewel Hall
Access Type
Campus Access Only
Presentation Type
Oral presentation
Entry Number
107
Start Date
4-16-2026 3:30 PM
End Date
4-16-2026 3:45 PM
School
School of Liberal Arts and Sciences
Department
Mathematics
Keywords
AI, artificial intelligence, statistics, data science, mathematics, machine learning
Abstract
Artificial intelligence has become one of the fastest growing modern technologies, with publicly available AI chatbots becoming particularly popular since the 2022 launch of OpenAI’s ChatGPT. Due to their seemingly endless applications and unrivalled ease of use, these AI models present a new and often highly efficient method of approaching problems, completing tasks, but with some many marketed models available, it is challenging to know which is the best one to use. This experiment tests 4 of the most popular AI models at performing data science tasks with given datasets, a common application of AI. These models are OpenAI’s ChatGPT, Anthropic’s Claude, Microsoft’s Copilot, and Perplexity AI Inc.’s Perplexity. The results reveal which model actually performs with the least errors, where the overall benchmark lies, and how capable AI is at performing statistical data analysis with minimal human input.
Primary Faculty Mentor(s)
Dr. Danny Cline
Primary Faculty Mentor(s) Department
Mathematics
Additional Faculty Mentor(s)
Dr. Paul McClure Dr. Ju Wang Dr. Will Briggs
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AI and Statistics: An Examination of the Capabilities of AI Models to Perform Data Science
Room 232, Schewel Hall
Artificial intelligence has become one of the fastest growing modern technologies, with publicly available AI chatbots becoming particularly popular since the 2022 launch of OpenAI’s ChatGPT. Due to their seemingly endless applications and unrivalled ease of use, these AI models present a new and often highly efficient method of approaching problems, completing tasks, but with some many marketed models available, it is challenging to know which is the best one to use. This experiment tests 4 of the most popular AI models at performing data science tasks with given datasets, a common application of AI. These models are OpenAI’s ChatGPT, Anthropic’s Claude, Microsoft’s Copilot, and Perplexity AI Inc.’s Perplexity. The results reveal which model actually performs with the least errors, where the overall benchmark lies, and how capable AI is at performing statistical data analysis with minimal human input.