Understanding Confidence Intervals

tags: #statistical_application #inferential_statistics #hypothesis_testing

What are confidence intervals?

The confidence interval (CI)  provides a range of values of where the true estimate of the population parameter will lie with a certain degree of confidence (note: the estimated sample statistic is only an average estimate of the real value).

Why is it important?

• By constructing a confidence interval, we can provide a range of plausible values for the population parameter, along with an associated level of confidence in the estimation.

• For example, if we calculate a 95% confidence interval for the population mean, it means that we are 95% confident that the true population parameter falls within the range of values specified by the interval.

Interpreting Confidence Intervals

• If the CI at a given confidence level/alpha, CONTAINS the null hypothesis, we fail to reject the null.

• If the CI at a given confidence level/alpha, DOES NOT contain the null hypothesis, we can reject the null.