In most cases, the relation between SD and SEM is expressed as, where the circumflex (^) represents estimation. Thus, SD is a constant that is independent of the sampling process, and SEM is random and influenced by sampling, especially by the sample size ( n). In contrast, the SEM indicates how precisely the mean of the population can be estimated from the sample that was drawn. The SD describes the spread of a population from which the sample was drawn and represents an inherent feature of the cohort being studied. Both SD and SEM are important concepts in statistical inference however, they are not interchangeable. The work cannot be changed in any way or used commercially without permission from the journal.Įrror bars are frequently used in biomedical and clinical publications to describe the variation in observed data, with standard deviation (SD) and standard error of the mean (SEM) being the most common measures of variability. This is an open access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND), where it is permissible to download and share the work provided it is properly cited. A note on error bars as a graphical representation of the variability of data in biomedical research: choosing between standard deviation and standard error of the mean. How to cite this article: Tang L, Zhang H, Zhang B. ∗Corresponding author: Bo Zhang, Department of Population and Quantitative Health Sciences, University of Massachusetts Medical School, Worcester, MA01605. Jude Children's Research Hospital, Memphis, TNīDepartment of Population and Quantitative Health Sciences, University of Massachusetts Medical School, Worcester, MA01605.
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