# powerHist

##### powerHist

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

- Keywords
- utilities

##### Usage

```
powerHist(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 = dlvTheme(),
rug = NULL, jitteredRug = TRUE, rugSides = "b",
rugAlpha = .2, returnPlotOnly = FALSE)
```

##### Arguments

- 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

`powerHist`

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

plot.

##### Value

An object, with the following elements:

The input when the function was called.

The intermediate numbers and distributions.

The dataframe used to generate the plot.

The histogram.

##### Examples

```
# NOT RUN {
powerHist(mtcars$mpg)
# }
```

*Documentation reproduced from package userfriendlyscience, version 0.7.2, License: GPL (>= 3)*