The "Random Stochastic Distributions" dataset is a collection of random numbers generated from various common stochastic distributions. The dataset was created by sampling random values from distributions such as Normal, Uniform, Exponential, Gamma, Poisson, Binomial, Geometric, Lognormal, Beta, and Negative Binomial. Each distribution has its own set of parameters, providing a diverse range of data patterns.

This Notebook shows how the data was generated, and also includes an EDA.

Note: It's important to mention that the dataset was generated for educational and exploratory purposes, and while it provides representative samples from the specified distributions, it does not cover the entire parameter space or represent real-world data distributions in all contexts.