Title: Estimation in Statistics
Headings: Estimation in Statistics
Estimation in Statistics
Point Estimate vs. Interval Estimate
Confidence Intervals
Confidence Level
Margin of Error
Test Your Understanding
Solution

Content: For example, suppose we compute an interval estimate of a population  parameter. We might describe this interval estimate as a 95%  confidence interval. This means that if we used the same  sampling method to select different samples and compute different  interval estimates, the true population parameter would fall within a range defined by the sample statistic + margin of error 95% of the time. Confidence intervals are preferred to point estimates, because confidence intervals indicate (a) the precision of the estimate and (b) the uncertainty of the estimate. Confidence Level
The probability part of a confidence interval is called a confidence level. The confidence level describes  the likelihood that a particular sampling method will produce a confidence interval that includes the true population parameter. Here is how to interpret a confidence level. Suppose we collected all possible samples from a given population, and computed confidence intervals for each  sample. Some confidence intervals would include the true  population parameter; others would not.