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Skills

Biology Data Collection and Statistical Analysis

8 weeks · 0 milestones

Execute a real biological investigation by collecting data from a controlled experiment OR from a named publicly available citizen science or genomics platform (iNaturalist, GBIF, NCBI GenBank/SRA) using a documented sampling methodology. The proof is the raw data with full metadata (location, time, conditions, collection method), a statistical analysis with appropriate tests (t-test, ANOVA, chi-squared, regression, or equivalent), and a written interpretation of results. Data collection from open platforms is not lesser proof — a documented GBIF biodiversity dataset with a rigorous sampling protocol and correct statistical analysis demonstrates the same analytical competency as lab-collected data. Reviewed by a biologist who examines both the raw data for methodological consistency and the statistical analysis for appropriate test selection. Fabricated data has characteristic distributional anomalies that a biologist reviewer detects — raw data submission is required.

Milestone map

Milestone map

3 milestones

Either design a field or laboratory data collection protocol with clear variables and sampling strategy, or select and justify a public biodiversity or biological dataset. Accessible alternative: public repositories (iNaturalist, GBIF, NCBI) contain peer-quality data that fully satisfies this outcome — no field access required. The proof standard is identical whichever route you take.

Proof required

Submit a written protocol or dataset justification (2–3 pages) covering: your biological question, your variables and sampling strategy (field/lab) or dataset source and accession, your rationale for the collection design or dataset selection, and your planned statistical analysis approach.

What gets checked

  • Biological question is specific and testable — 'Does species diversity correlate with habitat edge distance in urban parks?' not 'What lives in parks?'
  • Protocol or dataset selection includes a clear justification — why this design or dataset can answer the question, not just that it exists
  • Statistical approach is named at proposal stage — t-test, ANOVA, regression, species diversity index — confirms the submitter has thought through the analysis before collecting

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