The Standard Error (SE) measures the accuracy of a sample mean compared to the true population mean. It indicates how much the sample mean is expected to vary from the actual population mean if different samples are taken. A smaller SE suggests that the sample mean is a more reliable estimate of the population mean. Standard Error is calculated by dividing the Standard Deviation (SD) of the sample by the square root of the sample size (n). As the sample size increases, the SE decreases, reflecting greater confidence in the sample mean as an estimate of the population mean.