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| Basic Concepts for Experimental Design and Introductory Regression Analysis | |
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| Introduction and Historical Perspective | |
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| A Systematic Approach to the Planning and Implementation of Experiments | |
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| Fundamental Principles: Replication, Randomization, and Blocking | |
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| Simple Linear Regression | |
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| Testing of Hypothesis and Interval Estimation | |
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| Multiple Linear Regression | |
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| Variable Selection in Regression Analysis | |
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| Analysis of Air Pollution Data | |
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| Practical Summary | |
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| Experiments with a Single Factor | |
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| One-Way Layout | |
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| Multiple Comparisons | |
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| Quantitative Factors and Orthogonal Polynomials | |
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| Expected Mean Squares and Sample Size Determination | |
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| One-Way Random Effects Model | |
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| Residual Analysis: Assessment of Model Assumptions | |
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| Practical Summary | |
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| Experiments with More Than One Factor | |
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| Paired Comparison Designs | |
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| Randomized Block Designs | |
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| Two-Way Layout: Factors With Fixed Levels | |
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| Two-Way Layout: Factors With Random Levels | |
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| Multi-Way Layout | |
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| Latin Square Designs: Two Blocking Variables | |
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| Graeco-Latin Square Designs | |
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| Balanced Incomplete Block Designs | |
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| Split-Plot Designs | |
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| Analysis of Covariance: Incorporating Auxiliary Information | |
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| Transformation of the Response | |
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| Practical Summary | |
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| Full Factorial Experiments at Two Levels | |
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| An Epitaxial Layer Growth Experiment | |
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| Full Factorial Designs at Two Levels: A General Discussion | |
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| Factorial Effects and Plots | |
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| Using Regression to Compute Factorial Effects | |
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| ANOVA Treatment of Factorial Effects | |
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| Fundamental Principles for Factorial Effects: Effect Hierarchy, Effect Sparsity, and Effect Heredity | |
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| Comparisons with the One-Factor-At-A-Time" Approach | |
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| Normal and Half-Normal Plots for Judging Effect Significance | |
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| Lenth's Method: Testing Effect Significance for Experiments Without Variance Estimates | |
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| Nominal-the-Best Problem and Quadratic Loss Function | |
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| Use of Log Sample Variance for Dispersion Analysis | |
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| Analysis of Location and Dispersion: Revisiting the Epitaxial Layer Growth Experiment | |
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| Test of Variance Homogeneity and Pooled Estimate of Variance | |
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| Studentized Maximum Modulus Test: Testing Effect Significance for Experiments With Variance Estimates | |
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| Blocking and Optimal Arrangement of 2k Factorial Designs in 2q Blocks | |
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| Practical Summary | |
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| Fractional Factorial Experiments at Two Levels | |
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| A Leaf Spring Experiment | |
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| Fractional Factorial Designs: Effect Aliasing and the Criteria Of Resolution and Minimum Aberration | |
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| Analysis of Fractional Factorial Experiments | |
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| Techniques for Resolving the Ambiguities in Aliased Effects | |
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| Selection of 2kp Designs Using Minimum Aberration and Related Criteria | |
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| Blocking in Fractional Factorial Designs | |
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| Practical Summary | |
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| Full Factorial and Fractional Factorial Experiments at Three.Levels | |
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| A Seat-Belt Experiment | |
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| Larger-the-Better and Smaller-the-Better Problems | |
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| 3k Full Factorial Designs | |
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| 3kp Fractional Factorial Designs | |
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| Simple Analysis Methods: Plots and Analysis of Variance | |
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| An Alternative Analysis Method | |
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| Analysis Strategies for Multiple Responses I: Out-Of-Spec Probabilities | |
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| Blocking in 3k and 3kp Designs | |
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| Practical Summary | |
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| Other Design and Analysis Techniques for Experiments at More Than Two Levels | |
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| A Router Bit Experiment Based on a Mixed Two-Level and Four-Level Design | |
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| Method of Replacement and Construction of 2m4n Designs | |
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| Minimum Aberration 2m4n Designs | |