Concept of standard error:
The standard error (SE) of a statistic is the approximate standard deviation of a statistical
sample population.
The standard error is a statistical term that measures the accuracy with which a sample
distribution represents a population by using standard deviation. In statistics, a sample mean
deviates from the actual mean of a population; this deviation is the standard error of the mean.
Formula and Calculation of Standard Error:
The standard error of an estimate can be calculated as the standard deviation divided by the
square root of the sample size:
SE = σ / √n
where
σ = the population standard deviation
√n = the square root of the sample size
If the population standard deviation is not known, you can substitute the sample standard
deviation, s, in the numerator to approximate the standard error.
Requirements for Standard Error :
When a population is sampled, the mean, or average, is generally calculated. The standard error
can include the variation between the calculated mean of the population and one which is
considered known, or accepted as accurate. This helps compensate for any incidental
inaccuracies related to the gathering of the sample.
