# gghistostats

0th

Percentile

##### histogram for distribution of a numeric variable

Histogram with statistical details from one-sample test included in the plot as a subtitle.

##### Arguments
data

Dataframe from which variables specified are preferentially to be taken.

x

A numeric variable.

xlab

Label for x axis variable.

title

The text for the plot title.

subtitle

The text for the plot subtitle if you don't want results from one sample test to be displayed.

caption

The text for the plot caption.

type

Type of statistic expected ("parametric" or "nonparametric"). Abbreviations accepted are "p" or "np".

test.value

A number specifying the value of the null hypothesis.

k

Number of decimal places expected for results.

results.subtitle

Decides whether the results of statistical tests are to be displayed as subtitle.

density.plot

Decides whether kernel density estimate, which is a smoothed version of the histogram, is to be overlayed on top of the histogram.

density.colour

Decides colour for the density plot.

centrality.para

Decides which measure of central tendency ("mean" or "median") is to be displayed as a vertical line.

centrality.colour

Decides colour for the vertical line.

If set to TRUE, you can use it to pick better value with the binwidth argument to stat_bin().

binwidth

The width of the bins. Can be specified as a numeric value, or a function that calculates width from x. The default is to use bins bins that cover the range of the data. You should always override this value, exploring multiple widths to find the best to illustrate the stories in your data.

messages

Decides whether messages references, notes, and warnings are to be displayed (Default: TRUE).

• gghistostats
##### Examples
# NOT RUN {
library(datasets)
library(ggplot2)

# most basic function call with the defaults
ggstatsplot::gghistostats(
data = ggplot2::diamonds,
x = carat)

# more detailed function call
ggstatsplot::gghistostats(
data = datasets::iris,
x = Sepal.Length,
type = "parametric",
test.value = 3,
centrality.para = "mean",
density.plot = TRUE,