EAS100 Lecture Notes - Lecture 2: Confidence Interval, Sampling Distribution, Statistical Inference
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Now that we know how to create confidence intervals and test hypotheses about proportions, it"d be nice to be able to do the same for means. Just as we did before, we will base both our confidence interval and our hypothesis test on the sampling distribution model. Recall: if we use the statistic y for estimating the population mean , we can use the following information from the clt in order to obtain a confidence interval for . =y y n standard deviation of y , If the population distribution is originally normal, then the sampling distribution is also normal or. If the population distribution is non normal, but it has n . 30, then we can assume that the sampling distribution of y is approximately normal. Until now, all statistical tools that were introduced were based on the assumption that population standard deviation is known.