Students investigate: What story do the data tell about daily life, opportunity, and community wellbeing in La Palma? They also ask: How well does La Palma meet the needs of its residents today, and what evidence supports your conclusion? Using indicators such as housing costs, income, commute time, park access, and demographics, students evaluate visualizations and statistical claims, apply mean and standard deviation when appropriate, and identify missing data, uncertainty, and ethical concerns. They communicate an evidence-based assessment of La Palma’s strengths and needs while acknowledging the limitations of the synthesized dataset.

Students will analyze and visualize La Palma indicators—including housing, income, commuting, demographics, education, and park access—to determine what the data reveal about daily life, opportunity, and community wellbeing. They will evaluate whether La Palma meets residents’ needs by comparing measures, calculating population estimates and rates, and using mean and standard deviation to test whether a normal-distribution model is appropriate. Students will assess data reports and visualizations for accuracy, missing information, sampling years, rounding, and limitations, then examine ethical and societal implications of large-scale data collection and AI-supported analysis. They will communicate an evidence-based conclusion, listen to alternative interpretations, and propose additional data needed to support community decision-making.

Teams will create a concise data audit that checks calculations, source dates, rounding, missing variables, privacy and ethical concerns, and whether a normal-distribution model is appropriate. They will build two clear spreadsheet visualizations using selected La Palma indicators, such as housing costs, income, commuting, population density, age, or park acreage, and annotate each with its limitations. Each team will produce a one-page community wellbeing brief answering what the data reveal about daily life and opportunity, how well La Palma meets residents’ needs, and which additional data are needed for a fair conclusion. The final product will be a three-minute evidence-based presentation that recommends one community action and responds to peer questions.

Display a “La Palma by the Numbers” gallery featuring population density, median income and home value, commute time, park acreage, and educational attainment. In teams, students examine the visualizations, identify one strength and one concern, and flag missing context such as collection year, neighborhood differences, income distribution, or transportation access. Teams then evaluate a provocative claim—“La Palma meets residents’ needs”—by citing two indicators and naming a limitation or ethical concern related to collecting and representing community data. Close with a class discussion: “What story do the data tell about daily life, opportunity, and community wellbeing in La Palma?” and “How well does La Palma meet the needs of its residents today, and what evidence supports your conclusion?”

Teams host a “State of La Palma” gallery walk for classmates, families, and local community representatives, presenting a concise data report and interactive visualization. Each exhibit answers both essential questions using evidence such as housing costs, commute time, park access, demographics, and education, including an appropriate mean-and-standard-deviation analysis or a clear explanation of why a normal model does not fit. Presenters identify limitations involving sampling years, rounding, missing neighborhood-level data, and the ethical implications of collecting or using demographic data and AI. Visitors leave evidence-based questions and feedback, and each team closes with one practical recommendation for improving community wellbeing.