IAAO Mass Appraising Practice Exam 2025 – All-In-One Guide to Mastering Your Certification!

The correct measure used to assess spread or variation that typically requires normally distributed data is standard deviation. Standard deviation quantifies the amount of variation or dispersion in a set of values. When data is normally distributed, standard deviation serves as an effective measure of how much individual data points deviate from the mean of the dataset. It is the square root of the variance, which is useful for understanding the distribution and assessing the likelihood of data points falling within certain ranges around the mean.

In normally distributed data, the standard deviation can provide significant insights into the behavior of the data set, such as identifying the proportion of data within one, two, or three standard deviations away from the mean, thus allowing for inferences to be made about the entire population based on sample data. While other measures, such as the range or the coefficient of variation, can also provide insights into data variability, they do not specifically require a normal distribution to be utilized effectively.