Find Expected Value of X(n) from Uniform Distribution

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To find the expected value of the largest observation X(n) from a uniform distribution on the interval [0, θ], first determine its distribution function F(t) as F(t) = (t/θ)^n for a sample size n. The density function f(t) is obtained by differentiating F(t) with respect to t. The expected value of X(n) can then be calculated using the integral ∫_0^θ t f(t) dt. This method provides a clear approach to deriving the expected value from the uniform distribution.
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I swear that I used to know this.

If you have an independent sample of size n, from the uniform distribution (interval [0,\theta]), how do you find the Expected Value of the largest observation(X(n))?
 
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If X_{(n)} is the maximum in the sample, you first find its distribution. Since you have a random sample of size n, you can write

<br /> F(t) = \Pr(X_{(n)} \le t) = \prod_{i=1}^n \Pr(X_i \le t) = \left(\frac{t}{\theta}\right)^n<br />

Differentiate this w.r.t. t to find the density f(t), and the expected value is

<br /> \int_0^{\theta} t f(t) \, dt<br />
 
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