It is widely but incorrectly believed that the t-test and linear regression are valid only for Normally distributed outcomes. The t-test and linear regression compare the mean of an outcome variable for different subjects. While these are valid even in very small samples if the outcome variable is Normally distributed, their major usefulness comes from the fact that in large samples they are va...

In order to circumvent the influence of correlation in paired-samples and repeated measures experimental designs, researchers typically perform a one-sample Student t test on difference scores. That procedure entails some loss of power, because it employs N – 1 degrees of freedom instead of the 2N – 2 degrees of freedom of the independent-samples t test. In the case of non-normal distributions,...

Many Six Sigma practitioners use “Student’s” independent two-sample t-test when investigating differences in means. This type of test is based upon drawing random samples from two independent normal (Gaussian) distributions. Often, however, the assumption of normality and/or random sampling is violated. This article discusses when and why the two-sample t-test may be considered robust to these ...

Its utility is occasioned by the fact that scientific research very often examines the phenomena of nature two variables at a time, with an eye toward answering the basic question: Are these two variables related? If we alter the level of one, will we thereby alter the level of the other? Or alternatively: If we examine two different levels of one variable, will we find them to be associated wi...

We report the results of an evaluation of the LIAISON Treponema pallidum-specific assay, a one-step sandwich chemiluminescence immunoassay (CLIA), as a screening test and as a confirmatory test for the diagnosis of syphilis. The assay was compared with the CAPTIA Syphilis-G enzyme immunoassay (EIA) and with a testing algorithm that also included the rapid plasma reagin (RPR) and T. pallidum par...