Basic Analysis and Graphing - SAS

84 Performing Univariate Analysis Chapter 2
Statistical Details for the Distribution Platform
If the estimate of δ is 0, the formulas do not work. In that case, the Beta Binomial has reduced to the
Binomial(n,p), and pˆ is the estimate of p.
The confidence intervals for the Beta Binomial parameters are profile likelihood intervals.
Comparing All Distributions
The ShowDistribution list is sorted by AICc in ascending order.
The formula for AICc is as follows:
AICc = -2logL + 2ν + 2ν( ν+
1)
n ------------------------- – ( ν + 1)
where:
– logL is the logLikelihood
– n is the sample size
– ν is the number of parameters
Statistical Details for Fitted Quantiles
The fitted quantiles in the Diagnostic Plot and the fitted quantiles saved with the Save Fitted Quantiles
command are formed using the following method:
1. The data are sorted and ranked. Ties are assigned different ranks.
2. Compute the p [i] = rank [i] /(n+1).
3. Compute the quantile [i] = Quantile d (p [i] ) where Quantile d is the quantile function for the specific fitted
distribution, and i = 1,2,...,n.
Statistical Details for Fit Distribution Options
This section describes Goodness of Fit tests for fitting distributions and statistical details for specification
limits pertaining to fitted distributions.
Goodness of Fit
Table 2.20 Descriptions of JMP Goodness of Fit Tests
Distribution Parameters Goodness of Fit Test
Normal a μ and σ are unknown Shapiro-Wilk (for n ≤ 2000)
Kolmogorov-Smirnov-Lillefors (for
n > 2000)
μ and σ are both known
either μ or σ is known
Kolmogorov-Smirnov-Lillefors
(none)