Does TV Make You Smarter? — Modeling Causality and Confounding with GeoGebra

This GeoGebra example presents a fictional statistical study scenario to explore the causal question of whether watching TV makes people smarter. It demonstrates how to build a geometric and algebraic model using polygons, points, vectors, segments, and length measurements to represent treatment and response groups, while introducing a lurking variable (e.g., hearing aid) to illustrate the difference between correlation and causation. The core mathematical concepts involved include parabolas, sequences and series, Poisson distribution, algebra, and 3D shapes, but the construction focuses on using GeoGebra commands such as Polygon, Point, Vector, Segment, and Length to create visual comparisons, with dynamic variables (treatmentVariable, responseVariable, lurkingVariable) for parameter adjustment. This example is suitable for high school or introductory college statistics and probability courses, serving as an interactive tool for teachers to demonstrate experimental design, randomization, confounding control, and data visualization, and for students to grasp the fundamentals of causal inference.