Probability statistics for engineers and scientists 9th by walpole myers chapter 12
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Chapter 12
Multiple Linear
Regression and
Certain
Nonlinear
Regression
Models
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Section 12.1
Introduction
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Section 12.2
Estimating the
Coefficients
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Table 12.1 Data for Example 12.1
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Table 12.2 Data for Example 12.3
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Section 12.3
Linear
Regression Model
Using Matrices
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Table 12.3 Data for Example 12.4
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Section 12.4
Properties of the
Least Squares
Estimators
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Theorem 12.1
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Section 12.5
Inferences in
Multiple Linear
Regression
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Figure 12.1 SAS printout for data
in Example 12.4
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Section 12.6
Choice of a Fitted
Model through
Hypothesis
Testing
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Section 12.7
Special Cases of
Orthogonality
(Optional)
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Table 12.4 Analysis of Variances
for Orthogonal Variables
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Table 12.5 Data for Example 12.8
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Table 12.6 Analysis of Variance
for Grain Radius Data
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Section 12.8
Categorical or
Indicator
Variables
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Figure 12.2 Case of three
categories
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Table 12.7 Data for Example 12.9
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Figure 12.3 SAS printout for
Example 12.9
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Figure 12.4 Nonparallelism on
categorical variables
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Section 12.9
Sequential
Methods for
Model Selection
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Table 12.8 Data Relating to Infant
Length
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Table 12.9 t-Values for the
Regression Data of Table 12.8
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Section 12.10
Study of
Residuals and
Violation of
Assumptions
(Model Checking)
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