Coverage probability

What Coverage probability is

Coverage probability is a measure of the accuracy of a confidence interval. It is the probability that a confidence interval contains the true population parameter.

The steps for calculating coverage probability are as follows:

  1. Specify the population parameter of interest.

  2. Specify the confidence level, such as 95%.

  3. Calculate the lower and upper bounds of the confidence interval.

  4. Calculate the probability that the true population parameter lies within the confidence interval. This is the coverage probability.

  5. Compare the coverage probability to the confidence level. If the coverage probability is close to the confidence level, then the confidence interval is accurate.

Examples

  1. Coverage probability can be used to assess the accuracy of a confidence interval, by determining the probability that the interval contains the true population parameter.

  2. Coverage probability can be used to calculate the probability that a sample size is sufficient to detect an effect that is present in the population.

  3. Coverage probability can be used to calculate the probability that a hypothesis test will correctly reject a false null hypothesis.

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