Exponential Distributions
Learning Objectives
Understand the shape, statistical properties and probability formulas for exponential distributions.
Properties of Exponential Distributions
An exponential distribution is:
- A highly used ‘continuous’ distribution
- Often used to model the time elapsed between events (we call this ).
- It is ‘memoryless’ (see more in the ‘MEMORYLESS’ section below)
- We call the average lambda (). It measures the average number of events per time unit.
- It is right skewed (mean > median), and and can never be negative.

We can calculate the probabilities using formulas or Excel. The formulas are:
The Excel calculations are:
- Memoryless means that it does not matter how much time has elapsed previously.
- When calculating the odds of a certain amount of time elapsing going forward,
- It’s although the clock resets to zero.
- See Wikipedia‘s explanation of memoryless:
It describes situations where the time you’ve already waited for an event doesn’t affect how much longer you’ll have to wait
The following metrics apply to exponential distributions:
- The mean is:
- The standard deviation is also:
- The variance is:
- The distribution is right skewed and the skewness = 2.
Key Takeaways: Exponential Distributions
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