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This paper describes a simple and interesting application of structural equation modeling for a single lecture in an undergraduate econometrics course to introduce students to the concept of using data to recover latent variables. The application centers around using hourly observations on ride wait times at Disney’s Magic Kingdom to infer how crowded it is at the theme park. Pedagogically, the material is presented in the context of the linear regression model, so the discussion works to enhance students’ understanding of core material, not to introduce new disparate methods. The application provides interesting economic-based insights, like which ride’s wait times are categorically most informative about how crowded it is at the park.