Basic statistical tests - normal distribution

Definition

The normal (Gaussian) distribution is a symmetric, bell-shaped probability distribution underlying the assumptions of many common parametric statistical tests - many biological measurements approximate a normal distribution, but confirming this assumption (rather than assuming it) is an essential step before applying parametric statistical methods
A true normal distribution is fully described by just two parameters (mean and standard deviation) and follows the predictable 68-95-99.7 rule for data spread - many real biological measurements approximate this pattern reasonably well (e.g. height, blood pressure in a general population), but many others (length of stay, income, many biomarker concentrations) are meaningfully skewed and do not, making distribution shape an empirical question requiring assessment rather than an assumption

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