What is the standard error of estimation, and why is it important in statistics?

The standard error of estimation (SEE) is a measure of the precision of a statistical estimate. Specifically, it quantifies the variability of sample statistics (like the mean or regression coefficients) if the same sample were repeatedly drawn from the population. It's important because it tells you how much the estimate is likely to vary from the true population parameter – a smaller SEE indicates a more precise estimate.