Page 328, 5.2.2.* Let Y₁ denote the minimum of a random sample of size n from a distribution chat has pdf (x) = exp{-(x-30)}, x > 30, -∞ < 0 < ∞, f(x) = 0, elsewhere. Let Zn = n(Y₁ - 30). Investigate the imiting distribution of Z

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page 328 5.2.2

Page 328, 5.2.2.* Let Y₁ denote the minimum of a random sample of size n from a distribution
that has pdf
f(x) = exp{-(x-30)}, × > 30, -∞ << ∞, , f(x) = 0, elsewhere. Let Z₁ = n(Y₁ – 30). Investigate the
limiting distribution of Zn.
Transcribed Image Text:Page 328, 5.2.2.* Let Y₁ denote the minimum of a random sample of size n from a distribution that has pdf f(x) = exp{-(x-30)}, × > 30, -∞ << ∞, , f(x) = 0, elsewhere. Let Z₁ = n(Y₁ – 30). Investigate the limiting distribution of Zn.
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