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476 Formula Functions Reference Appendix C
Probability Functions
Normal Biv Distribution
Computes the probability that an observation is less than or equal to (x,y) with correlation coefficient r
where the observation is marginally normally distributed. You can specify the mean and standard
deviation for the X and Y coordinates of the observation. The default values are 0 for both means and 1
for both standard deviations.
Figure C.12 Overlay Plots of Normal Density Curves
Normal (0,0.75)
Normal (0, 1)
Normal (1, 1)
GLog Density
Returns the density or pdf at a particular quantile q of a generalized logarithm distribution with
location mu, scale sigma, and shape lambda. When the shape parameter is equal to zero, the distribution
reduces to a Lognormal(mu, sigma).
GLog Distribution
Returns the probability or cdf that a generalized logarithm distributed random variable is less than q.
When the shape parameter is equal to zero, the distribution reduces to a Lognormal(mu, sigma).
GLog Quantile
Returns the quantile, the value for which the probability is p that a random value would be lower.
When the shape parameter is equal to zero, the distribution reduces to a Lognormal(mu, sigma).
t Density
Accepts a quantile argument from the range of values for the t-distribution, a degrees of freedom
argument, and an optional noncentrality parameter. It returns the value of the t-density function (pdf)
for the arguments. To compare a t-density with 5 df with a standard normal distribution, you can create
a column of quantile values (x) with the formula count(-3, 3, nrow()), a second column computed as t
Density(X), and a third column computed as Normal Density(X). Then select Graph > Overlay to plot
the t-density and the normal density by x to see the plot shown in Figure C.13. You can see that the
t-density has slightly more spread than the normal.
t Distribution
Accepts three arguments: a quantile, a degrees of freedom, and a noncentrality parameter. It returns the
probability that an observation from the Student’s t-distribution with the specified noncentrality