The difference between standard deviation (SD) and standard error of mean (SEM) in statistics
First look at an explanation:
The standard deviation (SD) represents variation in the values of a variable, whereas the standard error of the mean (SEM) represents the spread that the mean of a sample of the values would have if you kept taking samples. So the SEM gives you an idea of the accuracy of the mean, and the SD gives you an idea of the variability of single observations. The two are related: SEM = SD/(square root of sample size).
The standard deviation (SD) represents the change in the value of the variable, while the standard error of the mean (SEM) represents the distribution that the mean of the sample will have if sampling continues. So SEM gives you a concept about the accuracy of the mean, and standard deviation gives you a concept about the variability of a single observation. The two are related: SEM = SD / (square root of sample size).
That is:, which
indicates the number of samples.
Reference link:
http://www.sportsci.org/resource/stats/meansd.html
