Title: 
Headings: 

Content: This gives a range of values for an unknown parameter(for example, a population mean). The interval has an associated confidence levelthat gives the probability with which the estimated interval will contain the true value of the parameter. The confidence level is chosen by the investigator. For a given estimation in a given sample, using a higher confidence level generates a wider (i.e., less precise) confidence interval. In general terms, a confidence interval for an unknown parameter is based on sampling the distributionof a corresponding estimator. [ 1]
This means that the confidence level represents the theoretical long-run frequency(i.e., the proportion) of confidence intervals that contain the true value of the unknown population parameter. In other words, 90% of confidence intervals computed at the 90% confidence level contain the parameter, 95% of confidence intervals computed at the 95% confidence level contain the parameter, 99% of confidence intervals computed at the 99% confidence level contain the parameter, etc.[2]
The confidence level is designated before examining the data. Most commonly, a 95% confidence level is used.[3] However, other confidence levels, such as 90% or 99%, are sometimes used. Factors affecting the width of the confidence interval include the size of the sample, the confidence level, and the variability in the sample.