The continuous uniform distribution models a random variable that is equally likely to fall anywhere between two finite bounds, denoted (a) and (b). It is often used to represent situations where there is no reason to prefer one outcome over another within a given interval.
Its probability density function (PDF) is constant over the interval ([a, b]) and zero elsewhere, while the cumulative distribution function (CDF) grows linearly from 0 to 1 across the same range.
Key summary statistics are straightforward: the mean is the midpoint ((a+b)/2) and the variance measures the spread as ((b-a)^2/12). These simple formulas make the uniform distribution a handy baseline model.
What is a uniform distribution?
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What is the probability density function (PDF) in a uniform distribution?
How does the cumulative distribution function (CDF) behave in a uniform distribution?
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Results are for informational purposes only and do not constitute professional advice.
