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| Introduction | |
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| Engineering Statistics: What and Why | |
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| Basic Terminology | |
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| Types of Statistical Studies | |
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| Types of Data | |
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| Types of Data Structures | |
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| Measurement: Its Importance and Difficulty | |
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| Mathematical Models, Reality, and Data Analysis | |
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| Data Collection | |
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| General Principles in the Collection of Engineering Data | |
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| Measurement | |
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| Sampling | |
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| Recording | |
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| Sampling in Enumerative Studies | |
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| Principles for Effective Experimentation | |
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| Taxonomy of Variables | |
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| Handling Extraneous Variables | |
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| Comparative Study | |
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| Replication | |
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| Allocation of Resources | |
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| Some Common Experimental Plans | |
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| Completely Randomized Experiments | |
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| Randomized Complete Block Experiments | |
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| Incomplete Block Experiments (Optional) | |
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| Preparing to Collect Engineering Data | |
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| A Series of Steps to Follow | |
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| Problem Definition | |
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| Study Definition | |
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| Physical Preparation | |
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| Elementary Descriptive Statistics | |
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| Elementary Graphical and Tabular Treatment of Quantitative Data | |
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| Dot Diagrams and Stem-and-Leaf Plots | |
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| Frequency Tables and Histograms | |
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| Scatterplots and Run Charts | |
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| Quantiles and Related Graphical Tools | |
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| Quantiles and Quantile Plots | |
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| Boxplots | |
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| Q-Q Plots and Comparing Distributional Shapes | |
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| Standard Numerical Summary Measures | |
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| Measures of Location | |
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| Measures of Spread | |
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| Statistics and Parameters | |
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| Plots of Summary Statistics | |
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| Summary Statistics and Personal Computer Software | |
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| Descriptive Statistics for Qualitative and Count Data (Optional) | |
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| Numerical Summarization of Qualitative and Count Data | |
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| Bar Charts and Plots for Qualitative and Count Data | |
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| Describing Relationships Between Variables | |
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| Fitting a Line by Least Squares | |
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| Applying the Least Squares Principle | |
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| The Sample Correlation and Coefficient of Determination | |
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| Computing and Using Residuals | |
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| Some Cautions | |
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| Computing | |
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| Fitting Curves and Surfaces by Least Squares | |
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| Curve Fitting by Least Squares | |
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| Surface Fitting by Least Squares | |
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| Some Additional Cautions | |
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| Fitted Effects for Factorial Data | |
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| Fitted Effects for 2-Factor Studies | |
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| Simpler Descriptions for Some Two-Way Data Sets | |
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| Fitted Effects for Three-Way (and Higher) Factorials | |
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| Simpler Descriptions of Some Three-Way Data Sets | |
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| Special Devices for 2[superscript p] Studies | |
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| Transformations and Choice of Measurement Scale (Optional) | |
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| Transformations and Single Samples | |
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| Transformations and Multiple Samples | |
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| Transformations and Simple Structure in Multifactor Studies | |
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| Beyond Descriptive Statistics | |
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| Probability: The Mathematics of Randomness | |
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| (Discrete) Random Variables | |
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| Random Variables and Their Distributions | |
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| Discrete Probability Functions and Cumulative Probability Functions | |
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| Summarization of Discrete Probability Distributions | |
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| The Binomial and Geometric Distributions | |
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| The Poisson Distributions | |
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| Continuous Random Variables | |
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| Probability Density Functions and Cumulative Probability Functions | |
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| Means and Variances for Continuous Distributions | |
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| The Normal Probability Distributions | |
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| The Exponential Distributions (Optional) | |
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| The Weibull Distributions (Optional) | |
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| Probability Plotting (Optional) | |
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| More on Normal Probability Plots | |
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| Probability Plots for Exponential and Weibull Distributions | |
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| Joint Distributions and Independence | |
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| Describing Jointly Discrete Random Variables | |
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| Conditional Distributions and Independence for Discrete Random Variables | |
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| Describing Jointly Continuous Random Variables (Optional) | |
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| Conditional Distributions and Independence for Continuous Random Variables (Optional) | |
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| Functions of Several Random Variables | |
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| The Distribution of a Function of Random Variables | |
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| Simulations to Approximate the Distribution of U = g(X, Y,..., Z) | |
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| Means and Variances for Linear Combinations of Random Variables | |
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| The Propagation of Error Formulas | |
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| The Central Limit Effect | |
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| Introduction to Formal Statistical Inference | |
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| Large-Sample Confidence Intervals for a Mean | |
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| A Large-n Confidence Interval for [mu] Involving [sigma] | |
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| A Generally Applicable Large-n Confidence Interval for [mu] | |
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| Some Additional Comments Concerning Confidence Intervals | |
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| Large-Sample Significance Tests for a Mean | |
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| Large-n Significance Tests for [mu] Involving [sigma] | |
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| A Five-Step Format for Summarizing Significance Tests | |
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| Generally Applicable Large-n Significance Tests for [mu] | |
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| Significance Testing and Formal Statistical Decision Making (Optional) | |
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| Some Comments Concerning Significance Testing and Estimation | |
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| One- and Two-Sample Inference for Means | |
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| Small-Sample Inference for a Single Mean | |
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| Inference for a Mean of Paired Differences | |
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| Large-Sample Comparisons of Two Means (Based on Independent Samples) | |
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| Small-Sample Comparisons of Two Means (Based on Independent Samples from Normal Distributions) | |
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| One- and Two-Sample Inference for Variances | |
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| Inference for the Variance of a Normal Distribution | |
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| Inference for the Ratio of Two Variances (Based on Independent Samples from Normal Distributions) | |
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| One- and Two-Sample Inference for Proportions | |
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| Inference for a Single Proportion | |
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| Inference for the Difference Between Two Proportions (Based on Independent Samples) | |
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| Prediction and Tolerance Intervals | |
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| Prediction Intervals for a Normal Distribution | |
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| Tolerance Intervals for a Normal Distribution | |
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| Prediction and Tolerance Intervals Based on Minimum and/or Maximum Values in a Sample | |
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| Inference for Unstructured Multisample Studies | |
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| The One-Way Normal Model | |
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| Graphical Comparison of Several Samples of Measurement Data | |
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| The One-Way (Normal) Multisample Model, Fitted Values, and Residuals | |
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| A Pooled Estimate of Variance for Multisample Studies | |
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| Standardized Residuals | |
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| Simple Confidence Intervals in Multisample Studies | |
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| Intervals for Means and for Comparing Means | |
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| Intervals for General Linear Combinations of Means | |
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| Individual and Simultaneous Confidence Levels | |
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| Two Simultaneous Confidence Interval Methods | |
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| The Pillai-Ramachandran Method | |
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| Tukey's Method | |
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| One-Way Analysis of Variance (ANOVA) | |
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| Significance Testing and Multisample Studies | |
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| The One-Way ANOVA F Test | |
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| The One-Way ANOVA Identity and Table | |
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| Random Effects Models and Analyses (Optional) | |
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| ANOVA-Based Inference for Variance Components (Optional) | |
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| Shewhart Control Charts for Measurement Data | |
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| Generalities about Shewhart Control Charts | |
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| "Standards Given" x Control Charts | |
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| Retrospective x Control Charts | |
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| Control Charts for Ranges | |
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| Control Charts for Standard Deviations | |
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| Control Charts for Measurements and Industrial Process Improvement | |
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| Shewhart Control Charts for Qualitative and Count Data | |
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| p Charts | |
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| u Charts | |
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| Common Control Chart Patterns and Special Checks | |
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| Inference for Full and Fractional Factorial Studies | |
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| Basic Inference in Two-Way Factorials with Some Replication | |
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| One-Way Methods in Two-Way Factorials | |
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| Two-Way Factorial Notation and Definitions of Effects | |
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| Individual Confidence Intervals for Factorial Effects | |
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| Tukey's Method for Comparing Main Effects (Optional) | |
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| p-Factor Studies with Two Levels for Each Factor | |
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| One-Way Methods in p-Way Factorials | |
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| p-Way Factorial Notation, Definitions of Effects, and Related Confidence Interval Methods | |
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| 2[superscript p] Studies Without Replication and the Normal-Plotting of Fitted Effects | |
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| Fitting and Checking Simplified Models in Balanced 2[superscript p] Factorial Studies and a Corresponding Variance Estimate (Optional) | |
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| Confidence Intervals for Balanced 2[superscript p] Studies under Few-Effects Models (Optional) | |
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| Standard Fractions of Two-Level Factorials, Part I: 1/2 Fractions | |
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| General Observations about Fractional Factorial Studies | |
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| Choice of Standard 1/2 Fractions of 2[superscript p] Studies | |
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| Aliasing in the Standard 1/2 Fractions | |
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| Data Analysis for 2[superscript p-1] Fractional Factorials | |
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| Some Additional Comments | |
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| Standard Fractions of Two-Level Factorials Part II: General 2[superscript p-q] Studies | |
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| Using 2[superscript p-q] Fractional Factorials | |
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| Design Resolution | |
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| Two-Level Factorials and Fractional Factorials in Blocks (Optional) | |
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| Some Additional Comments | |
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| Regression Analysis--Inference for Curve- and Surface-Fitting | |
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| Inference Methods Related to the Least Squares Fitting of a Line (Simple Linear Regression) | |
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| The Simple Linear Regression Model, Corresponding Variance Estimate, and Standardized Residuals | |
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| Inference for the Slope Parameter | |
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| Inference for the Mean System Response for a Particular Value of x | |
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| Prediction and Tolerance Intervals (Optional) | |
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| Simple Linear Regression and ANOVA | |
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| Simple Linear Regression and Statistical Software | |
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| Inference Methods for General Least Squares Curve- and Surface-Fitting (Multiple Linear Regression) | |
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| The Multiple Linear Regression Model, Corresponding Variance Estimate, and Standardized Residuals | |
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| Inference for the Parameters [beta subscript 0], [beta subscript 1], [beta subscript 2],..., [beta subscript k] | |
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| Inference for the Mean System Response for a Particular Set of Values for x[subscript 1], x[subscript 2],..., x[subscript k] | |
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| Prediction and Tolerance Intervals (Optional) | |
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| Multiple Regression and ANOVA | |
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| Application of Multiple Regression in Response Surface Problems and Factorial Analyses | |
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| Surface-Fitting and Response Surface Studies | |
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| Regression and Factorial Analyses | |
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| More on Probability and Model Fitting | |
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| More Elementary Probability | |
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| Basic Definitions and Axioms | |
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| Simple Theorems of Probability Theory | |
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| Conditional Probability and the Independence of Events | |
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| Applications of Simple Probability to System Reliability Prediction | |
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| Series Systems | |
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| Parallel Systems | |
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| Combination Series-Parallel Systems | |
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| Counting | |
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| A Multiplication Principle, Permutations, and Combinations | |
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| Probabilistic Concepts Useful in Survival Analysis | |
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| Survivorship and Force-of-Mortality Functions | |
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| Maximum Likelihood Fitting of Probability Models and Related Inference Methods | |
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| Likelihood Functions for Discrete Data and Maximum Likelihood Model Fitting | |
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| Likelihood Functions for Continuous and Mixed Data and Maximum Likelihood Model Fitting | |
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| Likelihood-Based Large-Sample Inference Methods | |
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| Tables | |
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| Answers to Section Exercises | |
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| Index | |