### Introduction to Greek Letters in R Plot

The post is about writing Greek letters in R plot, their labels, and the title of the plots. There are two main ways to include Greek letters in your R plot labels (axis labels, title, legend):

**Using the**`expression`

Function

This is the recommended approach as it provides more flexibility and control over the formatting of the Greek letters and mathematical expressions.**Using raw Greek letter Codes**

This method is less common and requires memorizing the character codes for each Greek letter.

## Table of Contents

**Question:** How one can include Greek letters (symbols) in R plot labels?**Answer:** Greek letters or symbols can be included in titles and labels of a graph using the expression command. Following are some examples

Note that in these examples random data is generated from a normal distribution. You can use your own data set to produce graphs that have symbols or Greek letters in their labels or titles.

### Greek Letters in R Plot

The following are a few examples of writing Greek letters in R plot.

**Example 1: Draw Histogram**

mycoef <- rnorm (1000) hist(mycoef, main = expression(beta) )

where beta in expression is the Greek letter (symbol) of $latex \beta$. A histogram similar to the following will be produced.

**Example 2:**

sample <- rnorm(mean=5, sd=1, n=100) hist(sample, main=expression( paste("sampled values, ", mu, "=5, ", sigma, "=1" )))

where mu and sigma are symbols of $latex \mu$ and $latex \sigma$ respectively. The histogram will look like

**Example 3:**

curve(dnorm, from= -3, to=3, n=1000, main="Normal Probability Density Function")

will produce a curve of Normal probability density function ranging from $latex -3$ to $latex 3$.

### Normal Density Function

To add a normal density function formula, we need to use the text and paste command, that is

text(-2, 0.3, expression(f(x) == paste(frac(1, sqrt(2*pi* sigma^2 ) ), " ", e^{frac(-(x-mu)^2, 2*sigma^2)})), cex=1.2)

Now the updated curve of the Normal probability density function will be

**Example 4:**

x <- dnorm( seq(-3, 3, 0.001)) plot(seq(-3, 3, 0.001), cumsum(x)/sum(x), type="l", col="blue", xlab="x", main="Normal Cumulative Distribution Function")

The Normal Cumulative Distribution function will look like,

To add the formula, use the text and paste command, that is

text(-1.5, 0.7, expression(phi(x) == paste(frac(1, sqrt(2*pi)), " ", integral(e^(-t^2/2)*dt, -infinity, x))), cex = 1.2)

### The curve of Normal Cumulative Distribution Function

The Curve of the Normal Cumulative Distribution Function and its formula in the plot will look like this,