FBLA Data Science & AI Practice Test 2026 – Complete Prep Guide

The term for the squared deviation from the mean divided by the number of observations in a dataset is referred to as variance. Variance is a statistical measurement that helps to quantify the degree of variation or spread in a set of data points. It is calculated by taking each data point, subtracting the mean of the dataset, squaring the result (to avoid negative values), and then averaging those squared differences. This provides a clear view of how much the individual data points differ from the mean.

Understanding variance is essential in data analysis because it plays a crucial role in various statistical methods, including hypothesis testing and the calculation of standard deviation, which is the square root of variance. While other options mention different statistical concepts, they do not apply to the specific definition provided in the question. For instance, the standard deviation refers to the square root of variance, while range and interquartile range are measures of dispersion that focus on the spread of data without incorporating the mean. Thus, variance is the most appropriate term for the description given in the question.