LLM Transcript
Overview
This document provides a transcript of interactions with a large language model used to assist with the DATA 607 Beachhead Assignment. The AI was used for debugging R and Quarto syntax, understanding error messages, and refining the structure of the analysis. All code and analysis were reviewed and executed by the author.
Transcript
User
How should I approach the Beachhead assignment? I need to identify the dataset source, describe what it contains, and explain my motivation.
Assistant
Provided guidance on selecting a public dataset, structuring a Quarto document, and aligning sections with the assignment rubric.
User
Where can I find datasets to use? Is this Kaggle dataset on best-selling albums a good choice?
Assistant
Confirmed Kaggle as an appropriate source and explained why the best-selling albums dataset is suitable for practicing data acquisition and transformation.
User
I am using a Quarto document. Where do I put code blocks and text?
Assistant
Explained Quarto structure, including YAML headers, Markdown text outside code chunks, and R code inside fenced {r} chunks.
User
I keep getting errors when rendering. Why does it work with the green arrow but not Render?
Assistant
Explained the difference between running individual chunks and rendering the full document in a clean R session. Guided debugging by fixing chunk structure and execution order.
User
I am getting errors like “object not found” and “column does not exist.”
Assistant
Diagnosed errors related to missing objects and incorrect column names. Guided the use of colnames() to identify exact column names and corrected mutate() and slice_max() usage.
User
My dataset column names are: Album, Artist, Year, Sales_Millions, Decade, Country, Genre.
Assistant
Updated data preparation code to correctly reference Sales_Millions and ensured numeric conversion and missing value handling.
User
What should I add next once the code runs without errors?
Assistant
Guided the addition of a visualization using ggplot2, optional summary analysis, and a Conclusions and Recommendations section aligned with the rubric.
User
Where should I include AI use disclosure and the transcript?
Assistant
Advised including a short AI disclosure section in the Quarto document and submitting the transcript separately, per syllabus guidance. Confirmed Quarto as the preferred document format based on instructor clarification.
User
Can you help with a submission note and transcript export?
Assistant
Provided a one-sentence submission note and step-by-step instructions for exporting and submitting the transcript.
Citation
OpenAI. (2026). ChatGPT (Version 5.2) [Large language model].
https://chat.openai.com. Accessed February 2026.