Probability and Statistics for Engineering and the Sciences
Probability and Statistics for Engineering and the Sciences
9th Edition
ISBN: 9781305251809
Author: Jay L. Devore
Publisher: Cengage Learning
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Chapter 6.1, Problem 18E

Let X1, X2,..., Xn be a random sample from a pdf f(x) that is symmetric about μ, so that X ˜ is an unbiased estimator of μ. If n is large, it can be shown that V( X ˜ ) ≈ 1/(4/n[f(μ)]2).

  1. a. Compare V( X ˜ ) to V( X ¯ ) when the underlying distribution is normal.
  2. b. When the underlying pdf is Cauchy (see Example 6.7), V( X ¯ ) = ∞, so X ¯ is a terrible estimator. What is V( X ˜ ) in this case when n is large?
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Chapter 6 Solutions

Probability and Statistics for Engineering and the Sciences

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