HIGH SCHOOL STATISTICS TEACHERS’ UNDERSTANDING OF HYPOTHESIS TESTING THROUGH SIMULATION

Abstract

It is a growing trend in statistics education to use simulations for hypothesis testing due to the belief that simulations help make the abstract ideas behind hypothesis testing become more concrete and understandable. Using simulations involves randomizing data production, repeating by simulation to see what is typical, and rejecting the null hypothesis if your data falls in the tails of the simulated distribution. This explanatory multiple case study sought to answer the following questions, “How does engaging in simulation tasks for hypothesis testing influence high school statistics teachers’ understanding of traditional hypothesis testing?” and “How do simulation tasks influence high school statistics teachers’ understanding of simulations and how do they make connections between traditional and simulation approaches for hypothesis testing?” The results of this study revealed that teachers’ understanding of hypothesis testing was positively impacted because of engaging in simulation tasks. The focus of the simulation tasks on concepts and logic instead of procedures helped the participants develop their understanding of the logic of hypothesis testing. Additionally, simulation approaches focus on visualizations, which helped develop the understanding of the probabilistic nature of hypothesis testing. Finally, how teachers understood simulations and made connections between traditional and simulation approaches was directly influenced by the lesson plan design.