# How to add a normal curve to a Histogram plot in R

A normal curve, also known as a Gaussian curve, is a smooth bell-shaped curve that is often used to represent the probability distribution of a dataset. It is a useful tool for understanding the distribution of a dataset and can help to identify patterns, outliers, and skewness. In this blog post, we will discuss how to add a normal curve to a histogram plot in R.

To add a normal curve to a histogram plot in R, you first need to create the histogram plot using the `hist()`

function or the `ggplot2`

package. Once the histogram plot is created, you can use the `lines()`

function or `geom_line()`

to add the normal curve to the plot. The `lines()`

function or `geom_line()`

takes several arguments such as the mean and standard deviation of the dataset, and the range of x-values to be plotted.

The `lines()`

function or `geom_line()`

will plot the normal curve based on the mean and standard deviation of the data passed to it. You can also use the `curve()`

function to plot the normal curve. The `curve()`

function takes the mean and standard deviation as arguments, and plots the normal curve for the given range of x-values.

To add the normal curve to the histogram plot, you need to pass the mean and standard deviation of the data to the `lines()`

function or `geom_line()`

. If you are using the `curve()`

function, you need to pass the mean and standard deviation of the data and the range of x-values.

It’s important to note that the normal curve is added based on the mean and standard deviation of the data, so it’s important to calculate those values before adding the normal curve to the histogram plot.

In summary, adding a normal curve to a histogram plot in R can provide a better understanding of the distribution of a dataset. You can use the `lines()`

function or `geom_line()`

or `curve()`

function to add the normal curve to the histogram plot. These functions take the mean and standard deviation of the dataset as arguments and plot the normal curve for the given range of x-values. It’s important to calculate the mean and standard deviation of the data before adding the normal curve to the histogram plot.

In this Applied Machine Learning Recipe, you will learn: How to add a normal curve to a Histogram plot in R.

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