This paper explains the underlying assumptions of the sampling distribution and its role in significance testing. To compute statistical significance, estimates of population parameters must be obtained so that only one sampling distribution is defined. A sampling distribution is the underlying distribution of a statistic. Sampling distributions…

The wide availability of large amounts of inexpensive computing power has encouraged statisticians to explore many approaches to a basis for inference. This paper presents one such "computer-intensive" approach: the bootstrap of Bradley Efron. This methodology fits between the cases where it is assumed that the form of the distribution…

This paper examined the rank transformation approach to analysis of variance as a solution to the Behrens-Fisher problem. Using simulation methodology four parameters were manipulated for the two group design: (1) ratio of population variances; (2) distribution form; (3) sample size and (4) population mean difference. The results indicated that…

The purpose of this study is to help define the precise nature and limits of the tolerable range in which a researcher may be relatively confident about the statistical validity of his or her research findings, focusing specifically on the statistical validity of results when violating the assumptions associated with the one-way, fixed-effects…