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Commonly used continuous distributions include normal (Gaussian), log‐normal, exponential, gamma, X2, t, F, and extreme value. The normal distribution is most frequently (and often incorrectly) used. It's selected because the math is easiest and it's the default for spreadsheet tools. The normal distribution is typically good for quality control activities like SPC. Reliability applications include calculating the lifetimes of items subject to wearout and the sizes of machined parts. The log‐normal distribution is usually a better fit for reliability data; simply transform the data by taking a logarithm. It's also a good distribution to use for wearout items. The exponential distribution is extremely important in reliability work; it applies well to life‐cycle statistics and assumes a constant hazard or failure rate. The gamma distribution is used in situations where partial failures can exist, such as when multiple subsystems must fail before the full system fails.

The X2, t, and F sampling distributions are used for statistical testing, fit, and confidence and used to make decisions, not to model physical characteristics. The Weibull distribution is the most widely used distribution in reliability applications, especially at the end of the infant mortality period. Adjusting the distribution shape parameter makes it fit many different life distributions. Finally, the extreme value distribution is used when the concern is with extreme values that can lead to failure. It is less concerned with the bulk of a population.