simple response for this We generate this type of data by participating in large standardized tests like MAP testing. In which students can see how they perform versus others at their age and determine what quartile they are in. In my opinion, I do believe that students in the upper and lower of those two quartiles do qualify as normative data. No matter what group you have or what task you perform there will always exist an upper and lower quartile. These data points can still be used as a comparison tool to compare other students to, thus fitting the definition of normative data to me. Although there will always be four quartiles, that doesn't mean that the lower one is not accomplishing the task. When looking at student scores on MAP testing a school can have students in lower quartiles yet some of those students could still be meeting minimum learning standards. This generally creates a skew left or right on a bell curve chart (ACE, 2025). I do not believe skewed data is necessarily a bad thing, but only because it helps highlight the problems in a classroom. For example, if there is a positive skew on exam data this could be due to the exam being skill based and if students do not possess the skill I would expect them to do very poorly, while others (even novices) who have the skill