ABSTRACT
This chapter presents the notion of interval estimation in which a random interval will be used to estimate a parameter. The difference between the confidence interval and the credible interval is not only in the interpretation. The probabilities they try to measure are also different. There are several bootstrap methods for interval estimation. The chapter introduces one that is called the bootstrap-t method. A confidence interval may give a range of values that the blood pressure may change after taking the new drug. The patients or their physicians may be able to use this range to judge if the new drug will clinically elevate a patient's blood pressure. There is a close connection between hypothesis testing and the confidence intervals. Every confidence interval corresponds to a hypothesis test and every hypothesis test corresponds to a confidence interval.
