Note that the width of the entire confidence interval is 307.25 – 292.75 = 14.5. The standard error would be calculated as: Standard error = s/√n = 18.5/√25 = 3.7 This means that, for example, a 99% confidence interval will be wider than a 95% confidence interval for the same set of data. Notice that higher confidence levels correspond to larger z-values, which leads to wider confidence intervals. The following table shows the z-value that corresponds to popular confidence level choices: Confidence Level The z-value that you will use is dependent on the confidence level that you choose. The formula to calculate this confidence interval is as follows: Now suppose we’d like to create a 95% confidence interval for the true population mean weight of turtles. Suppose we collect a random sample of turtles with the following information: Let’s check out an example to illustrate this idea. z: Z value that corresponds to a given confidence level. The margin of error measures the half-width of a confidence interval for a population mean. The standard error measures the preciseness of an estimate of a population mean. Two terms that students often confuse in statistics are standard error and margin of error.
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