A more specific answer will include more numerical references, and requires prior knowledge of information gathering, and cannot be explained at all briefly if general readers are to understand it. The sample mean is taken from the raw data and the probability that accompanies each piece of data. The mean is the sum of each value times its probability. The distribution is a curve that describes the probability of an event happening. The pattern of variation of the sample mean with a fixed sample size is called a sampling distribution.
Variation is the differences of the data.
It is important to understand how spread out the data are. Extremities and variations are not revealed in configurations such as average, mode, mean,or median alone. By knowing the sampling distribution of the sample mean, we can understand the data more completely. The sampling error is the standard deviation of this sampling distribution. The standard error is the standard deviation of means from many different samples.