Bootstrapping Using JMP® Pro with Applications to Six Sigma Projects and Academic Statistics Courses
Philip J. Ramsey, PhD, Owner, North Haven Group, and Professor, University of New Hampshire Mia Stephens, JMP Academic Ambassador, SAS
In the talk, we will discuss and demonstrate the JMP Pro implementation of bootstrapping via applications in Six Sigma projects using actual case studies, and in academic statistic courses to motivate concepts of sampling distributions and statistical inference. In addition, a number of easy-to-implement extensions of the JMP Pro bootstrapping capabilities will be provided, such as generating bootstrapped t confidence intervals and bootstrapped hypothesis tests as discussed by Hall and Wilson (1991). These bootstrapped t confidence intervals and hypothesis tests do not require distributional assumptions and therefore often have a distinct advantage over more conventional inferential methods.