Figoal: Normal Distributions in Science and Everyday Data
Understanding normal distributions is fundamental to interpreting patterns across science, engineering, and daily life. At its core, a normal distribution—also known as the Gaussian distribution—is defined by its symmetric bell-shaped curve, mathematically expressed as:
f(x) = (1 / (σ√(2π))) e–(x–μ)²/(2σ²)
where μ is the mean and σ the standard deviation. This elegant formula captures how values cluster tightly around the center, with probabilities decreasing evenly in both tails. The smooth continuity of this curve arises from *e*, the base of natural logarithms, ≈2.718, enabling seamless modeling of continuous phenomena from measurement errors to biological traits.
The Central Role of Normal Distributions in ModelingNatural systems often conform to normal distributions due to the Central Limit Theorem,