In the context of Advanced Placement Psychology, this term refers to the difference between the highest and lowest scores in a distribution. It provides a rudimentary measure of variability within a dataset. As an illustration, consider a set of test scores ranging from a lowest score of 60 to a highest score of 95; in this scenario, the value is 35 (95 – 60 = 35). This calculation offers a basic understanding of the spread of data points.
Although simple to calculate, this measure holds significance in psychological research and assessment. It allows for a quick estimation of how dispersed or clustered the data are. Historically, it has been used as an initial step in data analysis, providing a foundation for more sophisticated statistical measures of variability. However, its sensitivity to outliers makes it less robust than other measures, such as standard deviation or interquartile interval.