normalHist generates a histogram with a density curve and a normal density curve.

```
normalHist(
vector,
histColor = "#0000CC",
distributionColor = "#0000CC",
normalColor = "#00CC00",
distributionLineSize = 1,
normalLineSize = 1,
histAlpha = 0.25,
xLabel = NULL,
yLabel = NULL,
normalCurve = TRUE,
distCurve = TRUE,
breaks = 30,
theme = ggplot2::theme_minimal(),
rug = NULL,
jitteredRug = TRUE,
rugSides = "b",
rugAlpha = 0.2,
returnPlotOnly = FALSE
)
# S3 method for normalHist
print(x, ...)
```

- vector
A numeric vector.

- histColor
The colour to use for the histogram.

- distributionColor
The colour to use for the density curve.

- normalColor
The colour to use for the normal curve.

- distributionLineSize
The line size to use for the distribution density curve.

- normalLineSize
The line size to use for the normal curve.

- histAlpha
Alpha value ('opaqueness', as in, versus transparency) of the histogram.

- xLabel
Label to use on x axis.

- yLabel
Label to use on y axis.

- normalCurve
Whether to display the normal curve.

- distCurve
Whether to display the curve showing the distribution of the observed data.

- breaks
The number of breaks to use (this is equal to the number of bins minus one, or in other words, to the number of bars minus one).

- theme
The theme to use.

- rug
Whether to add a rug (i.e. lines at the bottom that correspond to individual datapoints.

- jitteredRug
Whether to jitter the rug (useful for variables with several datapoints sharing the same value.

- rugSides
This is useful when the histogram will be rotated; for example, this can be set to 'r' if the histogram is rotated 270 degrees.

- rugAlpha
Alpha value to use for the rug. When there is a lot of overlap, this can help get an idea of the number of datapoints at 'popular' values.

- returnPlotOnly
Whether to return the usual

`normalHist`

object that also contains all settings and intermediate objects, or whether to only return the`ggplot2::ggplot()`

plot.- x
The object to print.

- ...
Any additional arguments are passed to the default

`print`

method.

An object, with the following elements:

- input
The input when the function was called.

- intermediate
The intermediate numbers and distributions.

- dat
The dataframe used to generate the plot.

- plot
The histogram.

```
normalHist(mtcars$mpg)
```