Pearson eText for Probability and Statistical Inference -- Instant Access (Pearson+)

10th Edition

ISBN: 9780137538461

Author: Robert Hogg, Elliot Tanis

Publisher: PEARSON+

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Textbook Question

Chapter 3.1, Problem 11E

The pdf of Y is g ( y ) = c y 3 , 1 < y < ∞ .

(a) Calculate the value of c so that g(y) is a pdf.

(b) Find E(Y).

Definition Definition Probability of occurrence of a continuous random variable within a specified range. When the value of a random variable, Y, is evaluated at a point Y=y, then the probability distribution function gives the probability that Y will take a value less than or equal to y. The probability distribution function formula for random Variable Y following the normal distribution is: F(y) = P (Y ≤ y) The value of probability distribution function for random variable lies between 0 and 1.

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Chapter 3.1, Problem 10E

Chapter 3.1, Problem 12E

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Chapter 3 Solutions

Pearson eText for Probability and Statistical Inference -- Instant Access (Pearson+)

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The pdf of Y is g ( y ) = c y 3 , 1 < y < ∞ . (a) Calculate the value of c so that g(y) is a pdf. (b) Find E(Y). (c) Show that var(Y) is not finite.

Solution Summary: The author explains how the value of d can be computed as: cE(Y)=displaystyle

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Chapter 3 Solutions

The pdf of Y is g ( y ) = c y 3 , 1 &lt; y &lt; ∞ . (a) Calculate the value of c so that g(y) is a pdf. (b) Find E(Y). (c) Show that var(Y) is not finite.

Solution Summary: The author explains how the value of d can be computed as: cE(Y)=displaystyle

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Chapter 3 Solutions

The pdf of Y is g ( y ) = c y 3 , 1 < y < ∞ . (a) Calculate the value of c so that g(y) is a pdf. (b) Find E(Y). (c) Show that var(Y) is not finite.