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Introduction | |
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Quality Improvement in the Modern Business Environment | |
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Chapter Overview and Learning Objectives | |
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The Meaning of Quality and Quality Improvement | |
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Dimensions of Quality | |
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Quality Engineering Terminology | |
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A Brief History of Quality Control and Improvement | |
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Statistical Methods for Quality Control and Improvement | |
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Management Aspects of Quality Improvement | |
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Quality Philosophy and Management Strategies | |
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The Link Between Quality and Productivity | |
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Supply Chain Quality Management | |
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Quality Costs | |
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Legal Aspects of Quality | |
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Implementing Quality Improvement | |
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The Dmaic Process | |
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Chapter Overview and Learning Objectives | |
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Overview of DMAIC | |
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The Define Step | |
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The Measure Step | |
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The Analyze Step | |
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The Improve Step | |
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The Control Step | |
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Examples of DMAIC | |
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Litigation Documents | |
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Improving On-Time Delivery | |
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Improving Service Quality in a Bank | |
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Statistical Methods Useful in Quality Control and Improvement | |
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Modeling Process Quality | |
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Chapter Overview and Learning Objectives | |
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Describing Variation | |
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The Stem-and-Leaf Plot | |
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The Histogram | |
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Numerical Summary of Data | |
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The Box Plot | |
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Probability Distributions | |
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Important Discrete Distributions | |
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The Hypergeometric Distribution | |
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The Binomial Distribution | |
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The Poisson Distribution | |
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The Negative Binomial and Geometric Distributions | |
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Important Continuous Distributions | |
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The Normal Distribution | |
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The Lognormal Distribution | |
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The Exponential Distribution | |
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The Gamma Distribution | |
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The Weibull Distribution | |
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Probability Plots | |
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Normal Probability Plots | |
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Other Probability Plots | |
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Some Useful Approximations | |
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The Binomial Approximation to the Hypergeometric | |
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The Poisson Approximation to the Binomial | |
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The Normal Approximation to the Binomial | |
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Comments on Approximations | |
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Inferences About Process Quality | |
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Chapter Overview and Learning Objectives | |
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Statistics and Sampling Distributions | |
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Sampling from a Normal Distribution | |
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Sampling from a Bernoulli Distribution | |
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Sampling from a Poisson Distribution | |
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Point Estimation of Process Parameters | |
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Statistical Inference for a Single Sample | |
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Inference on the Mean of a Population, Variance Known | |
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The Use of P-Values for Hypothesis Testing | |
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Inference on the Mean of a Normal Distribution, Variance Unknown | |
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Inference on the Variance of a Normal Distribution | |
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Inference on a Population Proportion | |
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The Probability of Type II Error and Sample Size Decisions | |
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Statistical Inference for Two Samples | |
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Inference for a Difference in Means, Variances Known | |
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Inference for a Difference in Means of Two Normal Distributions, Variances Unknown | |
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Inference on the Variances of Two Normal Distributions | |
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Inference on Two Population Proportions | |
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What If There Are More Than Two Populations? The Analysis of Variance | |
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An Example | |
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The Analysis of Variance | |
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Checking Assumptions: Residual Analysis | |
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Linear Regression Models | |
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Estimation of the Parameters in Linear Regression Models | |
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Hypothesis Testing in Multiple Regression | |
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Confidance Intervals in Multiple Regression | |
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Prediction of New Observations | |
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Regression Model Diagnostics | |
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Basic Methods of Statistical Process Control and Capability Analysis | |
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Methods and Philosophy of Statistical Process Control | |
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Chapter Overview and Learning Objectives | |
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Introduction | |
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Chance and Assignable Causes of Quality Variation | |
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Statistical Basis of the Control Chart | |
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Basic Principles | |
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Choice of Control Limits | |
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Sample Size and Sampling Frequency | |
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Rational Subgroups | |
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Analysis of Patterns on Control Charts | |
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Discussion of Sensitizing Rules for Control Charts | |
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Phase I and Phase II of Control Chart Application | |
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The Rest of the Magnificent Seven | |
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Implementing SPC in a Quality Improvement Program | |
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An Application of SPC | |
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Applications of Statistical Process Control and Quality Improvement Tools in Transactional and Service Businesses | |
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Control Charts for Variables | |
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Chapter Overview and Learning Objectives | |
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Introduction | |
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Control Charts for �x and R | |
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Statistical Basis of the Charts | |
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Development and Use of �x and R Charts | |
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Charts Based on Standard Values | |
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Interpretation of �x and R Charts | |
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The Effect of Nonnormality on �x and R Charts | |
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The Operating-Characteristic Function | |
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The Average Run Length for the �x Chart | |