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The exponential distribution is a continuous probability distribution with probability density definded by:

f(x) = ke-kx for x ≥ 0


f(x) = 0 otherwise.

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Q: What is exponential distribution?
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Related questions

Why belong exponential family for poisson distribution or geometric distribution?

Why belong exponential family for poisson distribution

What is the history of exponential distribution?

Exponential DistributionThe exponential distribution is a very commonly used distribution in reliability engineering. Due to its simplicity, it has been widely employed even in cases to which it does not apply. The exponential distribution is used to describe units that have a constant failure rate.

What kind of distribution is exponential distribution?

Exponential distribution is a function of probability theory and statistics. This kind of distribution deals with continuous probability distributions and is part of the continuous analogue of the geometric distribution in math.

Whose distribution belong exponential family?

Poisson distribution or geometric distribution

Which distribution function has equal mean and variance?

The exponential distribution and the Poisson distribution.

What is the mode of an Exponential distribution?


Is the exponential distribution discrete or continuous?


What type of probability distribution is the normal distribution?

It is a continuous parametric distribution belonging to the family of exponential distributions. It is also symmetric.

How do you express hypoexponential distribution in terms of exponential distribution?

The hypoexponential distribution is two or more exponential distribution convolved together, so:hypo[x] = integral of A*exp(-A*x)*B*exp(-B*(t-x)) from 0 to t.If you have more stages you do more convolutions.

How do you derive the moment generating function of an exponential distribution?

To derive the moment generating function of an exponential distribution, you can use the definition of the moment generating function E(e^(tX)) where X is an exponential random variable with parameter λ. Substitute the probability density function of the exponential distribution into the moment generating function formula and simplify the expression to obtain the final moment generating function for the exponential distribution, which is M(t) = λ / (λ - t) for t < λ.

How does the shape of the normal distribution differ from the shapes of the uniform and exponential distributions?

the normal distribution is a bell shape and expeonential is rectangular

When does a researcher use exponential distribution?

he uese it when he is lost like a hungry man