Review: The Burger Problem

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• A sampling distribution is obtained by taking a randon sample of a certain size multiple times, taking a sample statistic, and plotting the distribution of this sample statistic.
• The Central Limit Theorem establishes that the sampling distribution of the mean will be normally distributed (even if the original population was not normally distributed).
• A statistic is called an unbiased estimator of a population parameter if the mean of the sampling distribution of the statistic is equal to the value of the statistic for the population. The mean is an umbiased estimator.
• We can use the Standard Error of our sample mean distribution in order to calculate probabilities of obtaining a sample with a certain statistic using the CDF.