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Triangular Distribution in R, A continuous probability distribution with a triangle-shaped probability density function is known as the triangular distribution.

The following three values describe it:

• The bare minimum of a
• The highest value b
• The maximum value c

## Triangular Distribution in R

To calculate probabilities for the triangular distribution in R, use the ptri() function from the EnvStats package. Its syntax is as follows.

`ptri(q, min = 0, max = 1, mode = 1/2)`

where:

q: Quantile of interest

min: The distribution’s smallest possible value

max: The distribution’s top value at its maximum

mode: The distribution’s highest point

The examples that follow demonstrate how to actually utilize this function in R.

### Example 1:- Calculating the Probability Less Than Some Value

Consider a restaurant that anticipates a minimum \$20,000, a maximum \$40,000, and most likely \$35,000 in total revenues for the forthcoming week.

What is the chance that the restaurant’s overall sales would be less than \$30,000?

To determine this probability, we can use the code below:

`library(EnvStats)`

Let’s calculate the probability

```ptri(q = 30000, min = 20000, max = 40000, mode = 35000)
[1] 0.3333333```

The likelihood that the restaurant’s total sales fall below \$30,000 is.333.

### Example 2:-Calculating Probability Greater Than Some Value

Let’s say a store predicts that in any given week, there would be a minimum of 600, a maximum of 3,000, and a likelihood of 2,200 customers.

What is the likelihood that the store will receive more than 2,500 visitors in a given week?

```1 - ptri(q = 2500, min = 600, max = 3000, mode = 2200)
[1] 0.1302083```

About 0.1302083 percent of customers over 2,500 will enter the store.

Further Resources:-
The following tutorials provide guidance on using R to manipulate various probability distributions:

The Multinomial Distribution in R – Data Science Tutorials

The Uniform Distribution in R – Data Science Tutorials

Test for Normal Distribution in R-Quick Guide – Data Science Tutorials

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