This blog post provides a comprehensive guide to understanding normal distributions, often referred to as Gaussian distributions. It covers foundational concepts such as discrete and continuous variables, probability distribution, expectation, variance, standard deviation, the normal distribution equation, the 68-95-99 rule, and z-scores. The post employs practical examples and Python code to illustrate these mathematical concepts, pertinent to both engineering and machine learning contexts.