Using JMP - SAS

424 Formula Functions Reference Appendix B
Probability Functions
Tukey HSD Quantile
Accepts a probability argument 1-alpha, and returns the 1-alphath quantile from Tukey’s HSD test for the
parameters that you specify. The alpha argument is the significance level that you want. nGroups is the
number of groups in a study. dfe is the error degrees of freedom (based on the total study sample). This is the
quantile used to calculate least significant difference in Tukey’s multiple comparisons test.
Tukey HSD P Quantile
Returns the p-value from Tukey's HSD multiple comparisons test.
F Power and F Sample Size
The F Power function calculates the power from a given situation that involves an F-test or t-test, and the F
Sample Size function computes the sample size. The arguments are the values that you specify for
computation of a prospective power analysis. (These functions perform the same computations as if you
selected DOE > Sample Size and Power. See the Design of Experiments for a discussion of power and
sample size.) The arguments include:
• alpha The significance level that you are willing to tolerate (often 0.05).
• dfh The hypothesis degrees of freedom. It is one (1) for a t-test.
• dfm The model degrees of freedom (such that dfe = n – dfm).
• SquaredSize The squared effect size scaled by the error variance, which is used for making the
noncentrality argument for the F-distribution. For this argument, use squared size = Δ 2 /σ 2 where σ 2 is
the error variance. That is, use:
Δ 2 = ( x – μ) 2 for a one-sample t-test
Δ 2 ( x 1 – x 2 ) 2
= ----------------------
4
for a two-sample t-test
Δ 2 k ( x i – x) 2
= -------------------
k
i = 1 for a k-sample F-test
• n (found only in the F Power function) The total number of observations (runs, experimental units,
or samples) you expect to have. Power (in the F Sample Size function) is the probability that you want
to have of declaring a significant result.