What is the term for the difference between an observation and the measure of central tendency without regard to the sign?

The term that describes the difference between an observation and a measure of central tendency, without considering the sign, is known as absolute deviation. This concept is essential in statistics as it quantifies how far a data point is from the central value (like the mean or median) regardless of whether the observation is above or below that central value.

Calculating the absolute deviation involves taking the absolute value of the difference between the observation and the measure of central tendency. Therefore, this measurement reflects the magnitude of deviation without indicating direction, which is crucial when assessing variability or consistency within a dataset.

In contrast, range refers to the difference between the maximum and minimum values in a dataset, outlier describes an observation that lies far from the other observations, and degree of freedom pertains to the number of values in a calculation that are free to vary. These terms do not convey the specific idea of measuring the absolute difference from a central tendency. Thus, absolute deviation provides clarity in understanding how individual data points relate to the overall distribution.