Exponential Probability Distribution Calculator
Exponential Probability Distribution Calculator helps determine probabilities for events following exponential distribution, commonly used in reliability engineering and queueing theory. It calculates either the Probability Density Function (PDF) or Cumulative Distribution Function (CDF) for given rate parameter (λ) and time value (x).
Calculator
Formula
PDF: f(x; λ) = λe-λx
CDF: F(x; λ) = 1 - e-λx
How to Use
Enter the rate parameter (λ > 0) and x value (≥ 0). Click either PDF to get the probability density at x, or CDF to get the probability of X ≤ x. The clear button resets all fields. Results appear instantly with calculation details.
Derivation Process
The exponential distribution models time between events in Poisson processes. Derived from Poisson's axioms, it assumes events occur continuously/independently at constant rate λ. The PDF represents event likelihood at exact time x, while CDF accumulates probabilities from 0 to x, derived using integration of PDF.
FAQs
What's the difference between PDF and CDF?
PDF gives probability density at exact point x, while CDF gives cumulative probability up to x. PDF shows likelihood at specific moment, CDF shows accumulated likelihood over interval.
Can λ be zero?
No, λ must be positive. It represents event rate - zero would mean no events occur, making probability calculations meaningless in this context.
What real-world applications use this?
Common in reliability analysis (equipment lifespan), queuing systems (customer arrival times), and radioactive decay modeling. Any memoryless process with constant event rate.
Why does x need to be ≥ 0?
Exponential distribution models time intervals - negative time values don't exist in this context. All events occur after time zero.
How accurate are the calculations?
Results are precise to machine floating-point precision. Accuracy depends on correct input values and valid λ > 0, x ≥ 0.