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The standard deviation of a continuous uniform distribution on the interval [a, b] is calculated using the formula $\sigma = \frac{b - a}{\sqrt{12}}$. It is derived by dividing the width of the interval by the square root of 12.

Conditions: The distribution is continuous and uniform on the interval [a, b].; b is the upper bound and a is the lower bound.

The standard deviation of a continuous uniform distribution on the interval [a, b] is calculated using the formula $\sigma = \frac{b - a}{\sqrt{12}}$. It is derived by dividing the width of the interval by the square root of 12.

Conditions: The distribution is continuous and uniform on the interval [a, b].; b is the upper bound and a is the lower bound.

The mean and standard deviation have no predictive power for a uniform distribution because every event within the support interval is equally likely to occur. Unlike distributions that cluster around a central value, a uniform distribution spreads probability evenly, so summary statistics do not single out any specific outcome as more probable.

Conditions: The distribution is uniform.; All outcomes within the support interval are equally likely.

The mean and standard deviation have no predictive power for a uniform distribution because every event within the support interval is equally likely to occur. Unlike distributions that cluster around a central value, a uniform distribution spreads probability evenly, so summary statistics do not single out any specific outcome as more probable.

Conditions: The distribution is uniform.; All outcomes within the support interval are equally likely.

The mean of a continuous uniform distribution on the interval [a, b] is calculated using the formula $\mu = \frac{a + b}{2}$. It represents the exact midpoint of the interval endpoints.

Conditions: The distribution is continuous and uniform on the interval [a, b].; a is the lower bound and b is the upper bound.

The mean of a continuous uniform distribution on the interval [a, b] is calculated using the formula $\mu = \frac{a + b}{2}$. It represents the exact midpoint of the interval endpoints.

Conditions: The distribution is continuous and uniform on the interval [a, b].; a is the lower bound and b is the upper bound.