Compute Cumulative Log Normal Probability Density in R Programming - plnorm() Function

Perform Probability Density Analysis on t-Distribution in R Programming - dt() Function

Last Updated : 19 Jun, 2020

dt() function in R Language is used to return the probability density analysis on the Student t-distribution with random variable x and degree of freedom df.

Syntax: dt(x, df) Parameters: x: Random Variable df: Degree of Freedom

Example 1:

Python3 1==

# R Program to perform
# Probability Density Analysis

# Calling dt() Function
dt(0, 10)
dt(1, 15)
dt(3, 40)

Output:

[1] 0.3891084
[1] 0.2341248
[1] 0.006185947

Example 2:

Python3 1==

# R Program to perform
# Probability Density Analysis

# Creating a vector
x <- seq(1, 10, by = 1)

# Calling dt() Function
y <- dt(x, 2)

# Plotting probability distribution graph
plot(x, y, type ="l")

Output: PDA-graph

PDA-graph

Compute Cumulative Log Normal Probability Density in R Programming - plnorm() Function

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