ABSTRACT
Understanding and reasoning about variability is viewed by statisticians as the core component of statistical thinking (e.g., Hoerl & Snee, 2001; Moore, 1990; Snee, 1990), which, in turn, is the goal of most statistics instruction. Statisticians have a “complex relationship” with variability: in various circumstances they attempt to minimize it, maximize it, estimate it, or simply analyze it (Gould, 2004). Wild and Pfannkuch (1999) developed a model of statistical thinking, based on an empirical study of how statisticians solve problems, which confirms that understanding and reasoning about variability is a key aspect of statistical thinking. They describe how statisticians distinguish between explained and unexplained variation, trying to model and find meaning in explained variation.
