Lesson 351 of 2116
Quantitative Analysis Prompting: Asking For Reproducible Code
When you ask an LLM to 'analyze this data,' you get a guess. When you ask it to write reproducible code, you get a collaborator.
Lesson map
What this lesson covers
Learning path
The main moves in order
- 1Why LLM-as-calculator is dangerous
- 2reproducibility
- 3R
- 4Python
Concept cluster
Terms to connect while reading
Section 1
Why LLM-as-calculator is dangerous
If you paste a CSV into an LLM and ask for 'the mean and a regression,' it will produce numbers. You cannot audit those numbers. You cannot reproduce them. You cannot defend them. The right move is to ask for CODE that computes the numbers, then run the code yourself.
The reproducible-code prompt
- 1Ask for code, not answers
- 2Specify the style guide (tidyverse, pandas, base R) explicitly
- 3Require inline comments on non-obvious steps
- 4Ask for diagnostic plots, not just numbers
- 5Run the code yourself and report any errors back
The audit checklist
- Does the code run without error on your data?
- Are the output numbers reasonable given your domain knowledge?
- Did you spot-check one calculation by hand or in a spreadsheet?
- Is the code version-controlled alongside the data?
- Can a colleague run it and get the same result?
Key terms in this lesson
The big idea: use LLMs to write analysis code, not to BE the analysis. Code is auditable. A conversation is not.
End-of-lesson quiz
Check what stuck
15 questions · Score saves to your progress.
Tutor
Curious about “Quantitative Analysis Prompting: Asking For Reproducible Code”?
Ask anything about this lesson. I’ll answer using just what you’re reading — short, friendly, grounded.
Progress saved locally in this browser. Sign in to sync across devices.
Related lessons
Keep going
Creators · 10 min
Reproducibility: Making Your AI-Assisted Work Re-Runnable
AI-assisted research is especially vulnerable to reproducibility failures. Model versions shift, prompts drift, outputs vary. Here's how to lock it down.
Creators · 40 min
Literature Review With LLMs: Scope First, Search Second
Use an LLM to define the scope of your lit review before touching a search engine — the single highest-leverage move in modern research workflow.
Creators · 40 min
Grant Writing Assistance: Specific Aims, Specifically
Grant writing rewards structural discipline. AI is a near-perfect drafting partner — if you feed it the right scaffolds.