summary of this statement. According to the central limit theorem, all data collected over time will accumulate to reach a normal distribution, otherwise known as the bell curve (Wagner & Gillespie, 2019). This theorem can, should, and often does apply to student achievement, but should be handled carefully. Firstly, in America's current public-school setting, structure, and design, secondary teachers may have as many as 250 different students in their classrooms each year. Consider the many factors outside of classroom teachers' control that affect student achievement scores, such as attendance (Ancheta et al., 2021), parent perceptions and support (Osburn et al., 2004), student's personal enjoyment of the learning (Camacho-Morles et al., 2021), and homelessness (De Gregorio et al., 2021), to name just a few. Also, evidence indicates that the effect sizes of various strategies implemented with secondary students decrease overall as students grow older (Scammacca et al., 2015). Evidence indicates that high-performing students demonstrate smaller growth with evidence-based instruction than struggling or learning-disabled students (Wexler et al., 2023), showing up as data points in the tails. For these reasons and more, the normal distribution might appear to demonstrate unfair testing or inequality in education, but it is generally a fair and logical representation of the sample's achievement given all mediating factors