data-analysis

# Data Analysis ## Before you start Require a concrete data-analysis task, its available inputs, and the requested deliverable, location, and format. If the task or required materials are missing or ambiguous in an answer-changing way, ask before calculating or creating outputs. Otherwise proceed without forcing a fixed analysis template. ## Success criteria - Derive the final result from one committed method: the selected evidence, answer-changing decisions, transformations, calculations, and judgments. - Produce every output the task asks for, in the requested location and format, and ensure it reflects the committed method. - Ground each answer-changing choice in the task materials rather than in a merely plausible nearby match. - Prefer a complete, simple, defensible deliverable over an elaborate or exhaustive analysis that risks not being delivered. ## Constraints - Use bounded probes first for large, unfamiliar, or expensive-to-read inputs. Narrow the scope, cap output, or use a timeout before expanding. - Before calculating or producing final outputs, identify the few decisions that can change the answer, such as inclusion or exclusion, matching, boundary choices, transformations, formulas, and ranking criteria. Adapt this check to the task; do not force a fixed analysis template. - Compare materially plausible alternatives only when they would change the final output. Use the smallest comparison needed to resolve the choice from the task materials, then commit t...