Title: Point and interval estimation > Inferences about distribution parameters > Continuous distributions > Distribution > Statistical Reference Guide | Analyse-it® 5.65 documentation
Headings: Point and interval estimation
Point and interval estimation
Content: If repeated random samples were taken from the population, the point estimate would be expected to vary from sample to sample. A confidence interval is an estimate constructed on the basis that a specified proportion of the confidence intervals include the true parameter in repeated sampling. How frequently the confidence interval contains the parameter is determined by the confidence level. 95% is commonly used and means that in repeated sampling 95% of the confidence intervals include the parameter. 99% is sometimes used when more confidence is needed and means that in repeated sampling 99% of the intervals  include the true parameter. It is unusual to use a confidence level of less than 90% as too many intervals would fail to include the parameter. Likewise, confidence levels larger than 99% are not used often because the intervals become wider the higher the confidence level and therefore require large sample sizes to make usable intervals. Many people misunderstand confidence intervals. A confidence interval does not predict with a given probability that the parameter lies within the interval. The problem arises because the word confidence is misinterpreted as implying probability.