In: Statistics and Probability
Let’s imagine you take a random sample of individuals from a target population, measure something and then calculate a sample statistic “mean”.
You calculate the mean in the sample because what you really want to know is the mean in the population, and the sample mean is a point estimate of this population parameter.
Then you take another independent random sample and calculate another mean.it is highly likely it would be different to the first mean because it is a different sample - the sample was selected completely independently of the first sample, and individuals were selected by a random process.
Then you keep doing this over and over again, each time calculating a mean and recording its value.
The sample means would vary from sample to sample and you could plot their distribution with a histogram. We call this distribution the sampling distribution.
The spread or variation of this sampling distribution would capture the sample-to-sample variability of your estimate of the population mean.
It would thus be a measure of the amount of uncertainty in your estimate of the population mean or “sampling variation”.
So it may be called the variability between the means of sample.