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Using JMP - SAS

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420 Formula Functions Reference Appendix B<br />

Probability Functions<br />

Logistic Quantile<br />

Returns the quantile associated with a cumulative probability p of the logistic distribution with location mu<br />

and scale sigma.<br />

Loglogistic Density<br />

Returns the density at x of the loglogistic distribution with location mu and scale sigma.<br />

Loglogistic Distribution<br />

Returns the probability that the loglogistic distribution with location mu and scale sigma is less than x.<br />

Loglogistic Quantile<br />

Returns the quantile associated with a cumulative probability p of the loglogistic distribution with location<br />

mu and scale sigma.<br />

Lognormal Density<br />

Returns the density at x of the lognormal distribution with location mu and scale sigma.<br />

Lognormal Distribution<br />

Returns the probability at x of the lognormal distribution with location mu and scale sigma.<br />

Lognormal Quantile<br />

Returns the quantile associated with a cumulative probability p of a lognormal distribution with location<br />

mu and scale sigma.<br />

Normal Density<br />

Accepts a quantile argument from the range of values for the standard normal distribution. It returns the<br />

value of the standard normal probability density function (pdf) for the argument. For example, you can<br />

create a column of quantile values (x) with the formula count(-3, 3, nrow()). A second column is computed<br />

as Normal Density(X) to generate density values. Then select Graph > Overlay to plot the normal density<br />

by x.<br />

Normal Distribution<br />

Accepts a quantile argument from the range of values for the standard normal distribution with mean 0 and<br />

standard deviation 1. It returns the probability that an observation from the standard normal distribution is<br />

less than or equal to the specified quantile. For example, the expression Normal Distribution(1.96) returns<br />

0.975, the probability that an observation from the standard normal distribution is less than or equal to the<br />

1.96 th quantile. Also, you can specify mean and standard deviation parameters to obtain probabilities from<br />

nonstandard normal distributions. The Normal Distribution function is the inverse of the Normal Quantile<br />

function.

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