![]() You probably already understand margin of error as it is related to survey results. The margin of error quantifies this error and indicates the precision of your estimate. When you use statistics to estimate a value, it's important to remember that no matter how well your study is designed, your estimate is subject to random sampling error. Point Estimate This single value estimates a population parameter by using your sample data. The confidence interval is determined by calculating a point estimate and then determining its margin of error. Therefore, they can be 95% confident that the mean length of all pencils is between 50 and 54 millimeters. The manufacturer takes a random sample of pencils and determines that the mean length of the sample is 52 millimeters and the 95% confidence interval is (50,54). For example, a manufacturer wants to know if the mean length of the pencils they produce is different than the target length. Use the confidence interval to assess the estimate of the population parameter. A 95% confidence interval indicates that 19 out of 20 samples (95%) from the same population will produce confidence intervals that contain the population parameter. The red confidence interval that is completely below the horizontal line does not. ![]() The vertical blue confidence intervals that overlap the horizontal line contain the value of the population mean. Here, the horizontal black line represents the fixed value of the unknown population mean, ยต. But if you repeated your sample many times, a certain percentage of the resulting confidence intervals would contain the unknown population parameter. ![]() Because of their random nature, it is unlikely that two samples from a particular population will yield identical confidence intervals. A confidence interval is a range of values, derived from sample statistics, that is likely to contain the value of an unknown population parameter.
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