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Walpole ch04

Chapter 4 covers Mathematical Expectation, including the mean, variance, and covariance of random variables. It presents various definitions and theorems related to these concepts, as well as discussions on linear combinations of random variables and Chebyshev’s Theorem. The chapter also addresses potential misconceptions and relates the material to other chapters.

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0% found this document useful (0 votes)
17 views35 pages

Walpole ch04

Chapter 4 covers Mathematical Expectation, including the mean, variance, and covariance of random variables. It presents various definitions and theorems related to these concepts, as well as discussions on linear combinations of random variables and Chebyshev’s Theorem. The chapter also addresses potential misconceptions and relates the material to other chapters.

Uploaded by

ilhan.haluk02
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© © All Rights Reserved
We take content rights seriously. If you suspect this is your content, claim it here.
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Chapter 4

Mathematical
Expectation

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Section 4.1
Mean of a
Random Variable

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Definition 4.1

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Theorem 4.1

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Definition 4.2

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Section 4.2
Variance and
Covariance of
Random
Variables

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Figure 4.1 Distributions with equal
means and unequal dispersions

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Definition 4.3

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Theorem 4.2

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Theorem 4.3

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Definition 4.4

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Theorem 4.4

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Definition 4.5

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Section 4.3
Means and
Variances of
Linear
Combinations of
Random
Variables

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Theorem 4.5

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Corollary 4.1

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Corollary 4.2

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Theorem 4.6

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Theorem 4.7

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Corollary 4.3

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Corollary 4.4

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Theorem 4.8

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Corollary 4.5

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Theorem 4.9

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Corollary 4.6

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Corollary 4.7

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Corollary 4.8

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Corollary 4.9

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Corollary 4.10

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Corollary 4.11

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Section 4.4
Chebyshev’s
Theorem

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Figure 4.2 Variability of continuous
observations about the mean

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Figure 4.3 Variability of discrete
observations about the mean

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Theorem 4.10

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Section 4.5
Potential
Misconceptions
and Hazards;
Relationship to
Material in Other
Chapters

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