What is the integral method for finding the mean in exponential distribution?

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SUMMARY

The integral method for finding the mean (μ) in an exponential distribution is defined by the formula μ = ∫₀^∞ x * f(x) dx, where f(x) = λ * e^(-λx). This method confirms that the mean is 1/λ, with λ being the rate parameter of the distribution. The variance is calculated using the formula σ² = E[X²] - (E[X])², where E[X] is the expected value. This approach is applicable for the interval 0 ≤ x < ∞.

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kliker
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in the exponential distribution we know that

μ = 1/λ and σ = 1/λ^2

also f(x) = λ*e^-λχ

how can i find the mean (μ) using integrals?

generally what we do is this

we integrate from a point to another the x*f(x) (EX)

And the variance is EX^2-(EX)^2

but here we have no points, so how can i prove that the mean is 1/λ?
 
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I assume that your distribution is defined for [itex]0\leq x<\infty[/itex]? If so, you integrate over that entire interval:

[tex]\mu=\int_0^{\infty}xf(x)dx[/tex]
 

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