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Prompt course · 8 lessons · 24 prompts · 1 hour · Beginner

AI for Statisticians

This prompt course walks statisticians through eight lessons, from framing a question to presenting results. Each lesson gives you prompts to try in ChatGPT, Claude, or Gemini and a clear way to check the output.

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What you'll learn

  • Frame questions: Turn a vague request into a hypothesis, an analysis plan, and a sample size estimate with AI help.
  • Design studies: Draft survey items, spot leading wording, and plan experiments that can answer the question.
  • Clean data: Create reproducible cleaning steps, catch errors, and document every variable change.
  • Run tests: Choose a suitable test, check assumptions, and read the output with a careful eye.
  • Build models: Plan features, write training code, and find out why a model fails.
  • Explain uncertainty: Translate results into effect sizes, stress-test conclusions, and prepare honest insights.
  • Make charts: Pick the right chart, write plotting code, and improve clarity without hiding uncertainty.
  • Report clearly: Draft report sections, write plain-English summaries, and get ready for stakeholder talks.

What's inside

8 lessons · 24 prompts
  1. Before you start · framework course RACE Prompt Framework: Role, Action, Context, ExpectationRACE fits statisticians because specifying Role, Action, Context, and Expectation helps you request a regression analysis with clear assumptions and output criteria.
  2. Start here Daniel's Wednesday, Two WaysA day in the life of a Statistician, before and after these prompts.
  3. 01 Lesson 1 · 3 prompts Framing Statistical Questions
  4. 02 Lesson 2 · 3 prompts Designing Surveys And Experiments
  5. 03 Lesson 3 · 3 prompts Cleaning Data And Code
  6. 04 Lesson 4 · 3 prompts Running Statistical Tests
  7. 05 Lesson 5 · 3 prompts Building Predictive Models
  8. 06 Lesson 6 · 3 prompts Interpreting Results And Uncertainty
  9. 07 Lesson 7 · 3 prompts Visualizing Data And Results
  10. 08 Lesson 8 · 3 prompts Reports And Stakeholder Talks

About this course

7 topics

Prompts for Statisticians: From Question to Report

Prompts are just clear instructions you give an AI assistant. In this course you will write them for the statistical work you already do: planning, cleaning, testing, modeling, and explaining.

Each lesson is short and practical. You bring a real task, try the prompt, and review what comes back with the same care you use for any draft.

  1. The lessons
    1. Framing Statistical Questions: You turn vague stakeholder requests into clear hypotheses, analysis plans, and sample size estimates with AI help.
    2. Designing Surveys And Experiments: You draft better survey items, spot bias, and plan sound experimental designs with AI assistance.
    3. Cleaning Data And Code: You create reproducible cleaning scripts, catch data errors, and document variable changes with AI support.
    4. Running Statistical Tests: You choose appropriate tests, check assumptions, and interpret output more carefully with AI help.
    5. Building Predictive Models: You plan features, write training code, and troubleshoot model failures with AI assistance.
    6. Interpreting Results And Uncertainty: You translate statistical findings into honest effect sizes, stress-tested conclusions, and decision-ready insights.
    7. Visualizing Data And Results: You pick the right chart, write plotting code, and improve clarity and honesty in statistical graphics.
    8. Reports And Stakeholder Talks: You draft report sections, create plain-English summaries, and prepare for stakeholder meetings with AI help.
  2. What the Course Covers

    This course follows the eight lessons in order. It starts with framing the question and ends with reports and stakeholder talks. Every lesson includes prompts you can adapt to your own data and your own tools.

  3. How the Lessons Connect

    Good statistics is a chain. A weak question ruins the design, a messy dataset ruins the test, and a confusing chart ruins the message. The lessons connect so you can see where AI helps and where it cannot.

  4. Using Prompts Well

    Give context: the goal, the data type, the audience, and any rules you must follow. Ask for steps, assumptions, and checks. Then test the answer on a small example before you trust it on the full analysis.

  5. Who This Course Is For

    This course is for statisticians, analysts, and data-minded professionals who want to use AI without giving up rigor. It works for people who write code and for people who mostly review code and results.

  6. Safety and Privacy

    Never paste private data into a tool your workplace has not approved. Remove names, addresses, and other identifiers before you ask for help. Keep your notes about what you shared and why.

  7. Your Next Step

    Pick one task from this week, such as a cleaning script or a report summary. Write a prompt using the lesson structure. Compare the AI draft with your own work, then keep what is useful.