Graphing function for Continuous Distributions.

Handles how continuous distributions are graphed. Users should not use this function. Instead, users should use visualize.it().

Usage

visualize.continuous(dist, stat = c(0, 1), params, section = "lower")

Arguments

dist

contains a supported continuos distribution shortname.

stat

a statistic to obtain the probability from. When using the "bounded" condition, you must supply the parameter as stat = c(lower_bound, upper_bound). Otherwise, a simple stat = desired_point will suffice.

params

A list that must contain the necessary parameters for each distribution. For example, params = list(mu = 1, sd = 1) would be for a normal distribution with mean 1 and standard deviation 1. If you are not aware of the parameters for the distribution, consider using the visualize.dist_name functions listed under the "See Also" section.

section

Select how you want the statistic(s) evaluated via section= either "lower","bounded", "upper", or"tails"

See also

visualize.it(), visualize.beta(), visualize.chisq(), visualize.exp(), visualize.gamma(), visualize.norm(), visualize.unif(), visualize.cauchy(), visualize.f(), visualize.lnorm(), visualize.t(), visualize.wilcox(), visualize.logis().

Author

James Balamuta

Examples

# Function does not have dist look up, must go through visualize.it
visualize.it(dist='norm', stat = c(0,1), params = list(mu = 1, sd = 1), section = "bounded")