Explain what is meant by the concept of sampling distribution

What will be an ideal response?

A population measure is called a parameter. It is a fixed value as long as the population does not change. A corresponding value computed from a sample is called a statistic. Depending on which sample we select we will get a different statistic. The difference between the statistic and the parameter due to the sample not being a perfect representative of the population is called sampling error. Each sample will generate a different amount of sampling error. For instance, if we are dealing with the mean, and were to take all possible samples of a given size, the distribution of the resulting sample means is called the sampling distribution. It represents the distribution of potential sampling error. The mean of the sampling distribution will equal the population mean and the standard deviation of the sampling distribution will equal the population standard deviation divided by the square root of the sample size.