Exponential Distribution Calculator

Calculate probabilities and statistics for exponential distribution with rate parameter

Calculate Exponential Distribution

Average rate of events per time unit (λ > 0)

Time period for probability calculations

Example: Bus Stop Waiting Time

Problem

Scenario: Buses arrive at a stop every 15 minutes on average

Question: What's the probability of waiting less than 3 minutes?

Rate parameter: λ = 1/15 = 0.0667 buses per minute

Time value: X = 3 minutes

Solution

P(x ≤ 3) = 1 - e^(-0.0667 × 3)

P(x ≤ 3) = 1 - e^(-0.2)

P(x ≤ 3) = 1 - 0.8187

P(x ≤ 3) = 0.1813 = 18.13%

There's an 18.13% chance of waiting less than 3 minutes

Key Properties

M

Memoryless

Future probability independent of past

C

Continuous

Models continuous time intervals

S

Skewed

Right-skewed distribution

Common Applications

Waiting times between events

Time until machine failure

Customer service times

Time between accidents

Radioactive decay intervals

Statistical Tips

Rate parameter λ must be positive

Mean = Standard Deviation = 1/λ

Higher λ means shorter waiting times

P(x > X) + P(x ≤ X) = 1

Understanding Exponential Distribution

What is Exponential Distribution?

The exponential distribution describes the time between events in a Poisson process, where events occur continuously and independently at a constant average rate. It's characterized by the "memoryless" property - the probability of an event occurring in the next time interval is independent of how much time has already elapsed.

Key Characteristics

  • Continuous probability distribution
  • Only one parameter: rate λ (lambda)
  • Domain: x ≥ 0 (non-negative values)
  • Right-skewed with long tail

Mathematical Formulas

Probability Density Function (PDF):

f(x) = λe^(-λx)

Cumulative Distribution Function (CDF):

F(x) = 1 - e^(-λx)

Key Statistics:

  • Mean: μ = 1/λ
  • Median: ln(2)/λ ≈ 0.693/λ
  • Variance: σ² = 1/λ²
  • Standard Deviation: σ = 1/λ

Real-World Examples

Customer Service

Time between customer arrivals at a service desk, assuming customers arrive randomly at a constant average rate.

Equipment Reliability

Time until failure of electronic components or machinery, widely used in reliability engineering.

Natural Phenomena

Time between earthquakes, radioactive decay events, or phone calls to a call center.