In statistical analysis, a sampling distribution examines the range of differences in results obtained from studying multiple samples from a larger population.

The Central Limit Theorem (CLT) surmises that the average of the sample means and standard deviations equals the population mean and standard deviation.

Central Limit Theorem: A sampling distribution of the mean is approximately normally distributed if the sample size is sufficiently large. This is true no matter what the population distribution is.

The distribution of the sample correlation coefficient is derived when the population is a mixture of two bivariate normal distributions with zero mean but different covariances and mixing proportions ...

The estimator for this design had the smallest variance and a sampling distribution most similar to a normal distribution. Systematic sampling is a good second choice if an auxiliary variable on which ...