Cross-over designs are popular in the assessment of equivalence. In this case, the effectiveness of a new treatment formulation (drug) is to be compared against the effectiveness of the currently used (reference) formulation. When showing equivalence, it is not necessary to show that the new treatment is better than the current treatment. Rather, the new treatment need only be shown to be as go...

F tests which test jointly for a unit root and a zero intercept, and so compete against Dickey−Fuller t tests, are shown not to enhance power because they are invariant to the intercept value in the absence of a unit root. Monte Carlo results in the literature that indicate otherwise are shown to have resulted from the use of special starting values. Testing procedures that employ these F tests...

The R function t.test() can be used to perform both one and two sample t-tests on vectors of data. The function contains a variety of options and can be called as follows: > t.test(x, y = NULL, alternative = c("two.sided", "less", "greater"), mu = 0, paired = FALSE, var.equal = FALSE, conf.level = 0.95) Here x is a numeric vector of data values and y is an optional numeric vector of data values...