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Statistics Week 9 Notes Key terms Equations Key Notes Sampling error- The error resulting from using a sample to estimate a population characteristic. ẋ - µ (sample mean – population) For a given variable x and a given sample size, the distribution of the variable ẋ is called the sampling distribution of sample size. ẋ gets closer to the mean as we increase the number (n) Mean of sample means = population mean μ xμ Standard Deviation of the sample mean: σ x σ √n If the variable of the population is normal, then sample size (n) is normally distributed. Central Limit Theorem: For a relatively large sample size, ẋ is approximately normal, regardless of the distribution of the variable under consideration. Approximation becomes better with a larger sample size. General rule for sample: X > 30