**Probability Distribution**: Probability Distribution can be described as a statistical function which describes all the possible values and likelihoods than a random variable can take within given range. This range lies between the minimum and maximum statistical possible values.

Probability distribution can be classified into two categories parametric and nonparametric.

**Parametric Distribution**: Distributions, such as a normal distribution which can be described by using a mathematical function and makes assumptions about the parameters of data from which sample can be drawn. These types of distributions make it easier to draw conclusions about the data however; they also make restrictive assumptions which are not necessarily supported by real-world patterns.

**Nonparametric distributions: **Distributions such as a historical distribution cannot be described by using a mathematical function. Instead of making restrictive assumptions, these types of distributions fit the data perfectly however, without generalizing the data, it can be difficult for a researcher to draw any conclusions.

In the following Sections we will study several Parametric Distributions like:

- Uniform Distribution
- Exponential Distribution
- Log Distribution
- Normal Distribution
- Log-Normal Distribution
- Binomial /Bernoulli Distribution
- Poisson Distribution

We would also look into the application of distribution in finance: Credit Risk or Market Risk.