![]() ![]() Table - Z-Scores for Commonly Used Confidence Intervals Thus, P( - margin of error 30), then the sample standard deviations can be used to estimate the population standard deviation. This means that there is a 95% probability that the confidence interval will contain the true population mean. Suppose we want to generate a 95% confidence interval estimate for an unknown population mean. Another way of thinking about a confidence interval is that it is the range of likely values of the parameter (defined as the point estimate + margin of error) with a specified level of confidence (which is similar to a probability). Rather, it reflects the amount of random error in the sample and provides a range of values that are likely to include the unknown parameter. The confidence interval does not reflect the variability in the unknown parameter. ![]() Consequently, the 95% CI is the likely range of the true, unknown parameter. The observed interval may over- or underestimate μ. In practice, however, we select one random sample and generate one confidence interval, which may or may not contain the true mean. Strictly speaking a 95% confidence interval means that if we were to take 100 different samples and compute a 95% confidence interval for each sample, then approximately 95 of the 100 confidence intervals will contain the true mean value ( μ).
1 Comment
|
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |