ABSTRACT
Standard error is another term for the standard deviation of a sampling distribution, rather than just a sample. For example, if we took a large number of samples of a particular size from a population and recorded the mean for each sample, we could calculate the standard deviation of all their means – this is called the standard error. Because it is based on a very large number of samples, it should be more precise and therefore smaller than the standard deviation. Standard error is used in a range of applications, including hypothesis testing and the calculation of confidence intervals. To calculate the standard error, follow the steps: calculate the standard deviation of the sample mean, count the number of observed values, find the square root of the sum and divide the standard deviation by the certain number. We can see that the standard error is very much smaller than the standard deviation.
