Anscombe's Quartet: Same Statistics, Different Visual Stories

①This example demonstrates four datasets that share nearly identical simple statistical properties (mean, variance, correlation, and regression line) yet appear strikingly different when plotted, highlighting the importance of data visualization in statistical analysis. ②Core mathematical concepts include descriptive statistics, linear regression, correlation, and the role of graphical representation in revealing data structure, falling under probability and statistics. ③Construction details: The GeoGebra construction uses the TableText command to generate data tables, the Distance command to compute distances between points and regression lines, and defines multiple point objects (e.g., B1, D1, E1, etc.) to create four scatterplots with their corresponding regression lines, enabling visual comparison of the datasets. ④This is suitable for high school to undergraduate statistics courses, data literacy training, or math lab activities, helping students understand the complementarity between statistical summaries and graphical displays and fostering critical thinking in data analysis.