Activity 01
Wage Gap Data Analysis: Correlation and Causation
Students receive wage data broken down by education, occupation, gender, and race. Working in pairs, they calculate wage gaps between categories, identify patterns, and propose explanations that distinguish correlation from causation. The class discusses which explanations are supported by human capital theory and which require other frameworks.
Does a higher minimum wage help or hurt low-skilled workers?
Facilitation TipDuring Wage Gap Data Analysis, have students work in pairs to calculate correlation coefficients and then switch roles to explain how correlation differs from causation in their own words.
What to look forPose the question: 'If a company can hire a robot to do a job for less than a human worker, what economic factors should guide their decision?' Guide students to consider labor costs, productivity, maintenance, and the value of human skills like creativity or complex problem-solving.