In statistics, the standard error (SE) is a measure of sampling error, which is the difference between a population parameter and a sample statistic. It is the approximate standard deviation of a statistical sample population and measures the accuracy with which a sample distribution represents a population by using standard deviation. The standard error is a statistical term that describes the variation between the calculated mean of the population and one which is considered known or accepted as accurate. The standard error is commonly used to estimate how well sample data represents the whole population. The standard error of the mean (SEM) is the most commonly reported type of standard error. It tells you how much the sample mean would vary if you were to repeat a study using new samples from within a single population. The standard error is calculated using the standard deviation and the sample size. The larger the sample size, the smaller the standard error, because the sample statistic will be closer to approaching the population parameter.