A ready-to-run, 75-minute in-class data activity (instructor guide plus two-page student handout) that teaches measurement and composite indices through federalism and state politics. Every group receives the same open dataset, all 50 states scored 0-10 on ten policy categories, but a different set of weights. Students first replicate the published ranking from its components, then reweight it, and discover that their “top five” differs from the group beside them. The disagreement is the lesson: a ranking is an argument about what matters, expressed as arithmetic.

The guide includes learning objectives, a minute-by-minute session plan, six assignable weighting profiles, seven debrief questions, a methods-memo assignment with a four-criterion rubric, and extensions for research methods (Spearman rank correlation, correlation matrices), state and local politics, comparative politics, civic engagement, and graduate seminars. The handout gives step-by-step spreadsheet formulas, with optional starter code in R and Python.

The activity takes no position on what states should do. It treats the index as an object of critique, asks students to identify the value judgments embedded in category selection and weighting, and works with any composite index an instructor prefers. It requires only a spreadsheet: the dataset is free, needs no account, and is licensed CC BY 4.0. A 20-minute no-laptop version using interactive weight sliders is included.

Suitable for Introduction to American Government, State and Local Politics, Public Policy, and Research Methods, from AP and dual-enrollment through upper-division courses.

Keywords: federalism, state politics, public policy, measurement, composite index, index construction, weighting, sensitivity analysis, robustness, replication, data literacy, quantitative reasoning, research methods, rankings, civil liberties, economic policy, active learning, group work, open data, R, Python.