What is Absolute Standard Deviation?
There isn’t a clear definition for the term “absolute standard deviation.” You might sometimes see in a text book, lab notes, lecture notes, or some other in-class materials; the author is usually referring the traditional standard deviation. However, it might also refer to error propagation, relative standard deviation, or the absolute deviation.
Read your text or notes and try to figure out which of these the author is talking about. If it’s in lab notes, lecture notes, or some other in-class materials, then ask your instructor to clarify the term.
These brief definitions might make it clear which term your book/paper is actually talking about. Click on the italicized link at the end of each definition for more information about the term, and how to calculate each term.
- Standard deviation: Standard deviation is a measure of how much your data is spread out. The formula to calculate it by hand is cumbersome, but possible if you follow the directions step-by-step. See: How to calculate the standard deviation.
- Error propagation: Error propogation (sometimes called propagation of uncertainty) happens when you use uncertain measurements to calculate something else. For example, you might use length to find area. “Propogation” is when these errors grow much more quickly than the sum of the individual errors. Several formulas exist to take calculate these errors. See: Formulas for Error Propogation (Propogation of Uncertainty).
- Relative standard deviation: The RSD is a special form of the standard deviation. It tells you whether the “regular” std dev is a small or large quantity when compared to the mean for the data set. It’s reported as a positive percentage. See: What is the relative standard deviation?
- Absolute deviation: the distance between each value in the data set and that data set’s mean or median. See: Average Deviation (Average Absolute Deviation)
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