In contrast to point estimators, confidence interval estimate a parameter by specifying a range of possible values.
The interval is linked to a confidence level, which describes the the probability that the sampling procedural will produce an interval containing the true parameter. In other words, a 95% confidence interval means that if we perform the sampling process a bunch of times and work out the confidence interval, we expect 95% of the confidence intervals to contain the true unknown population parameter.
Computation of the Confidence Intervals
The confidence interval is typically calculated as the point estimate (e.g., sample mean) plus or minus a multiple of the standard error 1:
where
Resources
- Seeing Theory - Frequentist Inference - An interactive visualization of confidence interval
- Interpreting Confidence intervals - Another visualization of confidence interval