Why Data Scientists love Gaussian

<img src="/84c39d16-38f9-5696-9a6a-188e027aeb47.jpg">
 Gaussian distribution model, often identified with its iconic bell shaped curve, also referred as Normal distribution, is so popular mainly because of three reasons.1. Ubiquitous in natural phenomena
Incredible number of processes in nature and social sciences naturally follows the Gaussian distribution. Even when they don’t, the Gaussian gives the best model approximation for these processes. Some examples include our height, blood pressure of adult human and intelligence, position of a particle that experiences diffusion, measurement errors.2. Mathematical Reason: Central Limit TheoremCentral limit theorem states that when we add large number of independent random variables, irrespective of the original distribution of these variables, their normalized sum tends towards a Gaussian distribution. For example, the distribution of total distance covered in an random walk tends towards a Gaussian probability distribution. The theorem can also been seen as a explanation why many natural phenomena follow Gaussian distribution. Unlike many other distribution that changes their nature on transformation, a Gaussian tends to remain a Gaussian.3. Simplicity (Occam Razor)For every Gaussian model approximation, there may exist a complex multi-parameter distribution that gives better approximation. But still Gaussian is preferred because it makes the math a lot simpler! Its mean, median and mode are all same. The entire distribution can be specified using just two parameters - mean and variance.

Why Data Scientists love Gaussian

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