What is Standard error?
[[Image:standard deviation diagram.svg|325px|thumb|For a value that is sampled with an unbiased [[normal distribution|normally distributed]] error, the above depicts the proportion of samples that would fall between 0, 1, 2, and 3 standard deviations above and below the actual value.]] The '''standard error''', sometimes abbreviated as <math>SE</math>,<ref>{{Cite web|date=2020-04-26|title=List of Probability and Statistics Symbols|url=https://mathvault.ca/hub/higher-math/math-symbols/probability-statistics-symbols/|access-date=2020-09-12|website=Math Vault|language=en-US}}</ref> is the [[standard deviation]] of the [[sampling distribution]] of a [[statistic]].<ref>Everitt B.S. 2003. ''The Cambridge Dictionary of Statistics'', CUP. {{ISBN|0-521-81099-X}} </ref> The term may also be used for an [[Estimation|estimate]] (good guess) of that standard deviation taken from a [[Sample (statistics)|sample]] of the whole group. The [[mean|average]] of some part of a group (called a sample) is the usual way to estimate the average for the whole group. It is often too hard or too costly to measure the whole group. But if a different sample is measured, it will have an average that is a little bit different from the first sample. The '''standard error of the mean''' is a way to know how close the average of the sample is to the average of the whole group. It is a way of knowing how sure one can be about the average from the sample. In real measurements, the true value of the standard deviation of the mean for the whole group is usually not known. So the term ''standard error'' is often used to mean a close guess to the true number for the whole group. The more measurements there are in a sample, the closer the guess will be to the true number for the whole group. ==How to find standard error of the mean== One way to find the standard error of the mean is to have lots of samples. First, the average for each sample is found. Then the average and [[standard deviation]] of those sample averages is found. The standard deviatio