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How to Find Probability Density Function of a Continuous Random Variable

A function whose value at any given sample in the sample space can be explained as providing a relative likelihood that the value of the random variable would be equal to that sample is called a probability density function (PDF). It gives the probability that any value in a continuous set of values might occur. Its magnitude gives an idea of the likelihood of finding a continuous random variable near a certain point. A function defined on the outcomes of some probabilistic experiment which takes values in a continuous set is termed as a continuous random variable. These describe outcomes in probabilistic situations where the possible values some quantity can take form a continuum. In this article, we will discuss how to find the probability density function of a continuous random variable.

How To Find PDF of a Continuous Random Variable

We can find PDF using the formula

\(\begin{array}{l}P(a\leq X\leq b) = \int_{a}^{b}f_{X}(x)dx\end{array} \)

If the random variable can be any real number, then PDF is normalized such that

\(\begin{array}{l}\int_{-\infty }^{\infty }f_{X}(x)dx = 1\end{array} \)

The probability that X takes value between -∞ to +∞ is 1.

Example

The non-normalized probability density function of a certain continuous random variable X is F(x) = 1/(1 + x2). Find the probability that X is greater than 1, P(X > 1).

Solution:

The probability density function should be normalized.

\(\begin{array}{l}\int_{-\infty }^{\infty }\frac{1}{1+x^{2}}dx = arc \: tan(x)_{-\infty }^{\infty } = \pi\end{array} \)

The normalized Probability density function is

\(\begin{array}{l}\tilde{f} = \frac{1}{\pi (1+x^{2})}\end{array} \)

 

\(\begin{array}{l}P(X>1) = \int_{1}^{\infty }\frac{1}{\pi (1+x^{2})}\end{array} \)
\(\begin{array}{l}= \frac{1}{\pi } \ arc \ tan (x)_{1}^{\infty }\end{array} \)
\(\begin{array}{l}=\frac{1}{\pi} (\frac{\pi}{2}-\frac{\pi}{4})\end{array} \)

= 1/4

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Frequently Asked Questions

Q1

What do you mean by Probability Distribution in probability theory?

A mathematical function that gives the probabilities of occurrence of different possible outcomes for an experiment is a probability distribution.

Q2

What do you mean by Probability Density Function?

A function that defines the relationship between a random variable and its probability, so that we can find the probability of the variable using the function, is called a Probability Density Function (PDF).

Q3

What do you mean by Continuous Random Variable?

A random variable X is continuous if possible values contain either a single interval on the number line or a union of disjoint intervals.

Q4

Give the formula to find the PDF of a continuous random variable.

The formula to find PDF of a continuous random variable is given by P(a≤ X ≤ b) = ∫ab f(x) dx.

Test your Knowledge on Random variables

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