A sampling distribution describes the probabilities associated with an estimator, when a random sample is drawn from a population. The random sample is considered as one of the many samples that might have been taken. Each would have given a different value for the estimator. The distribution of these different values is called the sampling distribution of the estimator. Deriving the sampling distribution is the first step in calculating a confidence interval, or in conducting a hypothesis test.