Question

What is meant by standard error?

Answer 1

Hint: The standard error is a statistical term which measures the accuracy with which a sample distribution represents a population which uses the standard deviation. Here we will understand the standard error and its significance.

Complete step by step solution:
In statistics, a sample mean deviates from the actual mean of the population and this deviation is known as the standard error of the mean.
Standard errors are important which reflect how much sampling fluctuation a statistic will show. The inferential statistics involved in the construction of the confidence intervals with the significance testing are based on the standard errors. Standard errors are based on the sample size.
In other words, Standard error is calculated by taking the standard deviation and dividing it by the square root of the sample size. The standard error gives the accuracy of the sample mean which measures the sample to sample variability of the sample means.

Note: Always remember that the bigger the standard error, the less accurate the statistic. Always understand that anything for which we calculate in the sample data which is subject to the random errors.
Always remember the difference between the sampling error and the standard error and apply accordingly. Sampling error is the difference in the size between the sample estimate and the population parameter. The standard error of the mean is also known as the standard error which provides the measure of the accuracy of the sample mean as an estimate of the population parameter.