Mathematical Statistics with Applications

7th Edition

ISBN: 9781133384380

Author: Dennis Wackerly; William Mendenhall; Richard L. Scheaffer

Publisher: Cengage Learning US

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Estimation

A new framework of data analysis where the new statistical methods are used for interpreting the results and analyzing the data is known as estimation in statistics.

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Textbook Question

Chapter 9.3, Problem 27E

Use the method described in Exercise 9.26 to show that, if Y₍₁₎ = min(Y₁, Y₂, . .., Y_n) when Y₁, Y₂, … , Y_n are independent uniform random variables on the interval (0, θ) , then Y₍₁₎ is not a consistent estimator for θ. [Hint: Based on the methods of Section 6.7 , Y₍₁₎ has the distribution function

F ( 1 ) ( y ) = { 0 , y < 0 , 1 − ( 1 − y / θ ) n , 0 ≤ y ≤ θ , 1 , y > θ . ]

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Chapter 9.3, Problem 26E

Chapter 9.3, Problem 28E

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Chapter 9 Solutions

Mathematical Statistics with Applications

Ch. 9.2 - Prob. 1E Ch. 9.2 - Let Y1, Y2,, Yn denote a random sample from a...Ch. 9.2 - Let Y1, Y2, , Yn denote a random sample from the...Ch. 9.2 - Let Y1, Y2, , Yn denote a random sample of size n...Ch. 9.2 - Suppose that Y1, Y2, , Yn is a random sample from...Ch. 9.2 - Prob. 6E Ch. 9.2 - Prob. 7E Ch. 9.2 - Let Y1, Y2, , Yn denote a random sample from a...Ch. 9.3 - Applet Exercise How was Figure 9.1 obtained?...Ch. 9.3 - Applet Exercise Refer to Exercise 9.9. Scroll down...

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Solution Summary: The author proves that Y_(1) is not a consistent estimator of.

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