How to use the uniform distribution calculator
Find the probability a value falls in an interval for a uniform distribution between two bounds. Enter lower bound, upper bound, interval start, interval end in the fields above; the probability in interval, mean, standard deviation are computed instantly and plotted on the chart so you can see how the answer changes.
Common searches this calculator answers include “uniform distribution probability”, “equally likely outcomes”, “uniform mean and standard deviation”, “calculate uniform distribution”, “find probability in interval”.
Formula
Variables
- a — Lower bound
- b — Upper bound
- c — Interval start
- d — Interval end
Worked example
With lower bound = 2, upper bound = 8, interval start = 3, interval end = 5, the calculator gives probability in interval ≈ 33.33333 %; mean ≈ 5; standard deviation ≈ 1.732051.
Frequently asked questions
What is the uniform distribution calculator used for?
Find the probability a value falls in an interval for a uniform distribution between two bounds. It helps with questions such as “uniform distribution probability”, “equally likely outcomes”, “uniform mean and standard deviation”.
What is the formula for the uniform distribution calculation?
Probability in interval (%) = 100 × (d-c) / (b-a). Mean = (a+b) / 2. Standard deviation = (b-a) / √(12). Here a is lower bound, b is upper bound, c is interval start, d is interval end.
What inputs do I need for the uniform distribution calculator?
You need lower bound, upper bound, interval start, interval end. Each field is pre-filled with a typical example so you can see how the result responds as you edit the numbers.
How do I use the uniform distribution calculator?
Type values into the input fields. Results and the chart update instantly. Use Reset to restore the example values, Copy results to paste them elsewhere, or Share to copy a link that preserves your inputs.
Is the uniform distribution result exact?
Calculations use standard formulas and double-precision arithmetic, then display about seven significant figures. Real-world measurements carry uncertainty, so treat results as estimates unless your inputs are exact.