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Probability statistics for engineers and scientists 9th by walpole myers chapter 08

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Copyright © 2010 Pearson Addison-Wesley.. Copyright © 2010 Pearson Addison-Wesley.. Copyright © 2010 Pearson Addison-Wesley.. Copyright © 2010 Pearson Addison-Wesley.. Copyright © 2010 P

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Section 8.1

Random

Sampling

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Definition 8.1

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Definition 8.2

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Definition 8.3

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Section 8.2

Some Important Statistics

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Definition 8.4

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Theorem 8.1

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Section 8.3

Sampling

Distributions

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Definition 8.5

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Theorem 8.2

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Figure 8.1 Illustration of the Central

Limit Theorem (distribution of X for

n = 1, moderate n, and large n)

_

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Figure 8.2 Area for Example 8.4

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Figure 8.3 Area for Case Study

8.1

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Figure 8.4 Area for Example 8.5

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Theorem 8.3

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Figure 8.5 Area for Case Study

8.2

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Figure 8.6 Area for Example 8.6

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Section 8.5

Sampling

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Theorem 8.4

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Figure 8.7 The chi-squared

distribution

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Section 8.6

t-Distribution

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Theorem 8.5

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Corollary 8.1

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Figure 8.8 The t-distribution

curves for v = 2, 5, and

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Figure 8.9 Symmetry property

(about 0) of the t-distribution

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Figure 8.10 The t-values for

Example 8.10

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Section 8.7

F-Distribution

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Theorem 8.6

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Figure 8.11 Typical F-distributions

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Figure 8.12 Illustration of the f  for

the F-distribution

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Theorem 8.7

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Theorem 8.8

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Figure 8.13 Data from three

distinct samples

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Figure 8.14 Data that easily could

have come from the same population

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Section 8.8

Quantile and

Probability Plots

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Definition 8.6

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Figure 8.15 Quantile plot for paint

data

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Definition 8.7

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Figure 8.16 Normal

quantile-quantile plot for paint data

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Table 8.1 Data for Example 8.12

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Figure 8.17 Normal quantile-quantile

plot for density data of Example 8.12

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Section 8.9

Potential

Misconceptions and Hazards;

Relationship to

Material in Other Chapters

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