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DS 104 Apply

Turn what you learned into your own Exploratory Data Analysis Report

What the final artifact is for

The Exploratory Data Analysis Report is DS 104's final artifact. You choose a real dataset you actually face, run the matching exploratory analysis, and write the problem, audience, data, method, verification, evidence, limitations, governance considerations, human reviewer and next step. It becomes the starting point for later practice discussions.

Info

Human, AI, Human: a person defines the question and the audience, AI may help with calculation or drafting the narrative, and a person verifies the evidence, the claims and the conclusion, and remains responsible for the result.

What to fill in

  • The problem, audience and data (source, grain, time coverage, key definitions)
  • The method and workflow
  • At least three verification checks
  • Evidence and output: what the analysis or workflow actually produced
  • Limitations
  • Risk and governance considerations, as relevant
  • The human reviewer
  • The next step

A structurally complete Exploratory Data Analysis Report

A structurally complete artifact includes: a clear, checkable question; a stated data source and grain; a reproducible method; at least three verification checks; evidence and claims that match the observed distribution and associations; at least one limitation.

Info

The platform never automatically judges whether your statistical judgments or claims were correct. This artifact feeds learning feedback and later discussion, and is reviewed by people.

Exit Ticket

Finally, use the Exit Ticket to record the most important idea from today, the step you are still unsure about, where you would apply this in a real context, the risk you most need to verify, and your difficulty and usefulness ratings.

Before you submit

Warning

Do not enter company secrets, client data, personal data, or other unauthorized sensitive information. Unless authorized, never upload confidential institutional or company data to an AI tool; confirm your institution's rules before using real survey or operations data.

Open the forms

What you need to complete

  • Complete both DS 104 modules
  • Score 80% or higher on the course post-test
  • To earn the Exploratory Data Analysis & Statistical Thinking Capability Certificate, also submit the Exploratory Data Analysis Report and have it reviewed and passed by a Credential Admin against the rubric

What is assessed

The Exploratory Data Analysis Report is scored by a Credential Admin across five weighted domains: Question & Data Framing, Method & Verification Rigor, Evidence, Distribution & Outlier Grounding, Association, Confounding & Significance Framing, and Limitations, Governance & Human Review. A PASS requires at least 12 of 15 points and no triggered critical-fail rule; 9 points or fewer, or any triggered critical-fail rule, is a FAIL.

Info

This human-review rubric is different from the self-check list shown right after you submit: the self-check is your own immediate reference, but the Capability Certificate is only ever issued after a Credential Admin reviews the report against this rubric.

Info

This scoring logic is published so you know what is being assessed. It is not the same as the answer key for the quiz.

Evidence of practice

  • A recorded rubric result (PASS, REVISION_REQUIRED, or FAIL) with no triggered critical-fail rule
  • A PASS records competency evidence separately for all six fine-grained DS 104 competencies (robust distribution judgment, outlier investigation and sampling limits, target population and association framing, confounding and interval-estimate intuition, data quality vs statistical/practical significance, and EDA rigor and AI-assisted review)

What you can earn

DS 104 Course Completion Certificate: earned once you complete both modules and pass the post-test, with no Exploratory Data Analysis Report submission required. Exploratory Data Analysis & Statistical Thinking Capability Certificate: requires submitting the report separately and passing review. The two are independent and do not affect each other.

What this does not mean

This credential confirms the holder completed DS 104's required learning and post-test, or (for the Capability Certificate) demonstrated judgment on distribution reasoning, outlier investigation, sampling and association framing, and statistical significance in the Exploratory Data Analysis Report.

  • It does not represent a formal data-analysis or statistics professional certification or hiring qualification
  • It does not mean any specific future analysis conclusion by the holder is necessarily correct
  • It does not mean human review can be skipped before a high-impact or irreversible decision (Human, AI, Human)

What next?