### Standard error

The standard error can be used to measure how trustworthy our samples are. It indicates how close the sample mean is from the true population mean, giving us an idea of how reliable the results of our experiment will be. A standard error of 0.01, for example, means that on average our results are likely to be 1% out from the true population and statistically very reliable.

Standard error is calculated as se = s / n (where se is the standard error, s is the sample’s standard deviation and n is the square root of the total number of observations).