Sampling errorThe natural discrepancy, or amount of error, between a sample statistic and its corresponding population parameter.distribution of sample means<span>The collection of sample means for all of the possible random samples of a particular size (n) that can be obtained from a population.</span>sampling distributionA distribution of statistics obtained by selecting all of the possible samples of a specific size from a population.central limit theorem<span>For any population with mean μ and standard deviation σ, the distribution of sample means for sample size n will have a mean of μ and a standard deviation of σ/√n and will approach a normal distribution as n approaches infinity.</span><span>expected value of M</span>The mean of the distribution of sample means is equal to the mean of the population of scores, μ, and is called this.<span>standard error of M</span><span>The standard deviation for the distribution of sample means. Identified by the symbol σ˯M. This standard error provides a measure of how much distance is expected on average between a sample mean (M) and the population mean (μ).</span>law of large numbers<span>States that the larger the sample size (n), the more probable it is that the sample mean is close to the population mean.</span>
