Which classification method defines classes based on how far values are from the mean?

The classification method that defines classes based on how far values are from the mean is Standard Deviation. This approach utilizes statistical analysis to create classes that reflect the variation and distribution of data relative to the average.

When employing the Standard Deviation method, data values are divided into classes that are set distances from the mean, allowing for a clear representation of how values relate to this central point. This means that values can be classified into categories like "within one standard deviation," "within two standard deviations," etc. This method is particularly useful for data that is normally distributed, as it effectively highlights the spread and any potential outliers relative to the mean.

In contrast, Natural Breaks focuses on finding natural groupings or clusters within the data, Quantile divides data into equal-sized groups regardless of the data distribution, and Equal Interval divides the range of data into equal segments regardless of how data clusters around certain values. Each of these methods serves specific purposes but does not specifically focus on the mean and its standard deviation as the method of classification.