Quantitative Analysis Prompting: Asking For Reproducible Code

End-of-lesson check

15 questions · take it digitally for instant feedback at tendril.neural-forge.io/learn/quiz/end-research-quantitative-analysis-prompting-creators

1. What is the core idea behind "Quantitative Analysis Prompting: Asking For Reproducible Code"?

   1. 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.
   2. keywords
   3. For quotes, paste the exact quoted string into Google with quotation marks
   4. Ask AI to suggest where in the paper to disclose vs in citations

2. Which term best describes a foundational idea in "Quantitative Analysis Prompting: Asking For Reproducible Code"?

   1. tidyverse
   2. reproducibility
   3. assumption checking
   4. diagnostic plot

3. A learner studying Quantitative Analysis Prompting: Asking For Reproducible Code would need to understand which concept?

   1. reproducibility
   2. assumption checking
   3. tidyverse
   4. diagnostic plot

4. Which of these is directly relevant to Quantitative Analysis Prompting: Asking For Reproducible Code?

   1. reproducibility
   2. tidyverse
   3. diagnostic plot
   4. assumption checking

5. Which of the following is a key point about Quantitative Analysis Prompting: Asking For Reproducible Code?

   1. Ask for code, not answers
   2. Specify the style guide (tidyverse, pandas, base R) explicitly
   3. Require inline comments on non-obvious steps
   4. Ask for diagnostic plots, not just numbers

6. Which of these does NOT belong in a discussion of Quantitative Analysis Prompting: Asking For Reproducible Code?

   1. Require inline comments on non-obvious steps
   2. Specify the style guide (tidyverse, pandas, base R) explicitly
   3. keywords
   4. Ask for code, not answers

7. Which statement is accurate regarding Quantitative Analysis Prompting: Asking For Reproducible Code?

   1. Are the output numbers reasonable given your domain knowledge?
   2. Did you spot-check one calculation by hand or in a spreadsheet?
   3. Does the code run without error on your data?
   4. Is the code version-controlled alongside the data?

8. Which of these does NOT belong in a discussion of Quantitative Analysis Prompting: Asking For Reproducible Code?

   1. Did you spot-check one calculation by hand or in a spreadsheet?
   2. keywords
   3. Does the code run without error on your data?
   4. Are the output numbers reasonable given your domain knowledge?

9. What is the key insight about "Template" in the context of Quantitative Analysis Prompting: Asking For Reproducible Code?

   1. I have a dataset with these columns: [list]. Write R code (tidyverse style) that: loads the data from 'data.
   2. keywords
   3. For quotes, paste the exact quoted string into Google with quotation marks
   4. Ask AI to suggest where in the paper to disclose vs in citations

10. What is the key insight about "Double-check the assumptions" in the context of Quantitative Analysis Prompting: Asking For Reproducible Code?

    1. keywords
    2. LLMs love to run a t-test whether or not your data meets t-test assumptions.
    3. For quotes, paste the exact quoted string into Google with quotation marks
    4. Ask AI to suggest where in the paper to disclose vs in citations

11. What is the key warning about "Maintain methodological rigour" in the context of Quantitative Analysis Prompting: Asking For Reproducible Code?

    1. keywords
    2. For quotes, paste the exact quoted string into Google with quotation marks
    3. AI-assisted research requires transparent disclosure of tools used, validation of outputs against primary sources, and p…
    4. Ask AI to suggest where in the paper to disclose vs in citations

12. Which statement accurately describes an aspect of Quantitative Analysis Prompting: Asking For Reproducible Code?

    1. keywords
    2. For quotes, paste the exact quoted string into Google with quotation marks
    3. Ask AI to suggest where in the paper to disclose vs in citations
    4. 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.

13. What does working with Quantitative Analysis Prompting: Asking For Reproducible Code typically involve?

    1. The big idea: use LLMs to write analysis code, not to BE the analysis. Code is auditable. A conversation is not.
    2. keywords
    3. For quotes, paste the exact quoted string into Google with quotation marks
    4. Ask AI to suggest where in the paper to disclose vs in citations

14. Which best describes the scope of "Quantitative Analysis Prompting: Asking For Reproducible Code"?

    1. It is unrelated to research workflows
    2. It focuses on When you ask an LLM to 'analyze this data,' you get a guess. When you ask it to write reproducible c
    3. It applies only to the opposite beginner tier
    4. It was deprecated in 2024 and no longer relevant

15. Which section heading best belongs in a lesson about Quantitative Analysis Prompting: Asking For Reproducible Code?

    1. keywords
    2. For quotes, paste the exact quoted string into Google with quotation marks
    3. The reproducible-code prompt
    4. Ask AI to suggest where in the paper to disclose vs in citations