Efnisyfirlit

• Cover
• Title Page
• Preface
• CHAPTER 1: The Role of Statistics in Engineering
  • Important Terms and Concepts
  • Study Resources
    • Additional Study Resources
  • Readings Content
    • 1.1 The Engineering Method and Statistical Thinking
    • 1.2 Collecting Engineering Data
    • 1.3 Mechanistic and Empirical Models
    • 1.4 Probability and Probability Models
• CHAPTER 2: Probability
  • Exercises
    • Exercises for Section 2.1
    • Exercises for Section 2.2
    • Exercises for Section 2.3
    • Exercises for Section 2.4
    • Exercises for Section 2.5
    • Exercises for Section 2.6
    • Exercises for Section 2.7
    • Exercises for Section 2.8
    • Exercises for Section 2.9
    • Supplemental Exercises for Chapter 2
  • Important Terms and Concepts
  • Study Resources
    • Section 2.1: Sample Spaces and Events
    • Section 2.2: Counting Techniques
    • Section 2.3: Interpretations and Axioms of Probability
    • Section 2.5: Conditional Probability
    • Section 2.6: Intersections of Events and Multiplication and Total Probability Rules
    • Section 2.7: Independence
    • Section 2.8: Bayes’ Theorem
    • Additional Study Resources
  • Readings Content
    • 2.1 Sample Spaces and Events
    • 2.2 Counting Techniques
    • 2.3 Interpretations and Axioms of Probability
    • 2.4 Unions of Events and Addition Rules
    • 2.5 Conditional Probability
    • 2.6 Intersections of Events and Multiplication and Total Probability Rules
    • 2.7 Independence
    • 2.8 Bayes’ Theorem
    • 2.9 Random Variables
• Chapter 3: Discrete Random Variables and Probability Distributions
  • Exercises
    • Exercises for Section 3.1
    • Exercises for Section 3.2
    • Exercises for Section 3.3
    • Exercises for Section 3.4
    • Exercises for Section 3.5
    • Exercises for Section 3.6
    • Exercises for Section 3.7
    • Exercises for Section 3.8
    • Supplemental Exercises for Chapter 3
  • Important Terms and Concepts
  • Study Resources
    • Section 3.1 Probability Distributions and Probability Mass Functions
    • Section 3.2 Cumulative Distribution Functions
    • Section 3.3 Mean and Variance of a Discrete Random Variable
    • Section 3.5 Binomial Distribution
    • Section 3.6 Geometric and Negative Binomial Distributions
    • Section 3.7 Hypergeometric Distribution
    • Section 3.8 Poisson Distribution
    • Additional Study Resources
  • Reading Content
    • 3.1 Probability Distributions and Probability Mass Functions
    • 3.2 Cumulative Distribution Functions
    • 3.3 Mean and Variance of a Discrete Random Variable
    • 3.4 Discrete Uniform Distribution
    • 3.5 Binomial Distribution
    • 3.6 Geometric and Negative Binomial Distributions
    • 3.7 Hypergeometric Distribution
    • 3.8 Poisson Distribution
• CHAPTER 4: Continuous Random Variables and Probability Distributions
  • Exercises
    • Exercises for Section 4.1
    • Exercises for Section 4.2
    • Exercises for Section 4.3
    • Exercises for Section 4.4
    • Exercises for Section 4.5
    • Exercises for Section 4.6
    • Exercises for Section 4.7
    • Exercises for Section 4.8
    • Exercises for Section 4.9
    • Exercises for Section 4.10
    • Exercises for Section 4.11
    • Supplemental Exercises for Chapter 4
  • Important Terms and Concepts
  • Study Resources
    • Section 4.1 Probability Distributions and Probability Density Functions
    • Section 4.2 Cumulative Distribution Functions
    • Section 4.3 Mean and Variance of a Continuous Random Variable
    • Section 4.4 Continuous Uniform Distribution
    • Section 4.5 Normal Distribution
    • Section 4.6 Normal Approximation to the Binomial and Poisson Distributions
    • Section 4.7 Exponential Distribution
    • Section 4.9 Weibull Distribution
    • Section 4.10 Lognormal Distribution
    • Additional Study Resources
  • Readings Content
    • 4.1 Probability Distributions and Probability Density Functions
    • 4.2 Cumulative Distribution Functions
    • 4.3 Mean and Variance of a Continuous Random Variable
    • 4.4 Continuous Uniform Distribution
    • 4.5 Normal Distribution
    • 4.6 Normal Approximation to the Binomial and Poisson Distributions
    • 4.7 Exponential Distribution
    • 4.8 Erlang and Gamma Distributions
    • 4.9 Weibull Distribution
    • 4.10 Lognormal Distribution
    • 4.11 Beta Distribution
• CHAPTER 5: Joint Probability Distributions
  • Exercises
    • Exercises for Section 5.1
    • Exercises for Section 5.2
    • Exercises for Section 5.3
    • Exercises for Section 5.4
    • Exercises for Section 5.5
    • Exercises for Section 5.6
    • Exercises for Section 5.7
    • Exercises for Section 5.8
    • Supplemental Exercises for Chapter 5
  • Important Terms and Concepts
  • Study Resources
    • Section 5.1 Joint Probability Distributions for Two Random Variables
    • Section 5.2 Conditional Probability Distributions and Independence
    • Section 5.4 Covariance and Correlation
    • Section 5.5 Common Joint Distributions
    • Section 5.6 Linear Functions of Random Variables
    • Section 5.8 Moment-Generating Functions
    • Additional Study Resources
  • Readings Content
    • 5.1 Joint Probability Distributions for Two Random Variables
    • 5.2 Conditional Probability Distributions and Independence
    • 5.3 Joint Probability Distributions for More Than Two Random Variables
    • 5.4 Covariance and Correlation
    • 5.5 Common Joint Distributions
    • 5.6 Linear Functions of Random Variables
    • 5.7 General Functions of Random Variables
    • 5.8 Moment-Generating Functions
• CHAPTER 6: Descriptive Statistics
  • Exercises
    • Exercises for Section 6.1
    • Exercises for Section 6.2
    • Exercises for Section 6.3
    • Exercises for Section 6.4
    • Exercises for Section 6.5
    • Exercises for Section 6.6
    • Exercises for Section 6.7
    • Supplemental Exercises for Chapter 6
  • Important Terms and Concepts
  • Study Resources
    • Section 6.1 Numerical Summaries of Data
    • Section 6.2 Stem-and-Leaf Diagrams
    • Section 6.3 Frequency Distributions and Histograms
    • Section 6.4 Box Plots
    • Section 6.6 Scatter Diagrams
    • Section 6.7 Probability Plots
    • Additional Study Resources
  • Readings Content
    • 6.1 Numerical Summaries of Data
    • 6.2 Stem-and-Leaf Diagrams
    • 6.3 Frequency Distributions and Histograms
    • 6.4 Box Plots
    • 6.5 Time Sequence Plots
    • 6.6 Scatter Diagrams
    • 6.7 Probability Plots
• CHAPTER 7: Point Estimation of Parameters and Sampling Distributions
  • Exercises
    • Exercises for Section 7.2
    • Exercises for Section 7.3
    • Exercises for Section 7.4
    • Supplemental Exercises for Chapter 7
  • Important Terms and Concepts
  • Study Resources
    • Section 7.2 Sampling Distributions and the Central Limit Theorem
    • Section 7.3 General Concepts of Point Estimation
    • Section 7.4 Methods of Point Estimation
    • Additional Study Resources
  • Readings Content
    • Introduction
    • 7.1 Point Estimation
    • 7.2 Sampling Distributions and the Central Limit Theorem
    • 7.3 General Concepts of Point Estimation
    • 7.4 Methods of Point Estimation
• CHAPTER 8: Statistical Intervals for a Single Sample
  • Exercises
    • Exercises for Section 8.1
    • Exercises for Section 8.2
    • Exercises for Section 8.3
    • Exercises for Section 8.4
    • Exercises for Section 8.6
    • Supplemental Exercises for Chapter 8
  • Important Terms and Concepts
  • Study Resources
    • Section 8.1 Confidence Interval on the Mean of a Normal Distribution, Variance Known
    • Section 8.2 Confidence Interval on the Mean of a Normal Distribution, Variance Unknown
    • Section 8.3 Confidence Interval on the Variance and Standard Deviation of a Normal Distribution
    • Section 8.4 Large-Sample Confidence Interval for a Population Proportion
    • Additional Study Resources
  • Readings Content
    • Introduction
    • 8.1 Confidence Interval on the Mean of a Normal Distribution, Variance Known
    • 8.2 Confidence Interval on the Mean of a Normal Distribution, Variance Unknown
    • 8.3 Confidence Interval on the Variance and Standard Deviation of a Normal Distribution
    • 8.4 Large-Sample Confidence Interval for a Population Proportion
    • 8.5 Guidelines for Constructing Confidence Intervals
    • 8.6 Bootstrap Confidence Interval
    • 8.7 Tolerance and Prediction Intervals
• CHAPTER 9: Tests of Hypotheses for a Single Sample
  • Exercises
    • Exercises for Section 9.1
    • Exercises for Section 9.2
    • Exercises for Section 9.3
    • Exercises for Section 9.4
    • Exercises for Section 9.5
    • Exercises for Section 9.7
    • Exercises for Section 9.8
    • Exercises for Section 9.9
    • Exercises for Section 9.10
    • Exercises for Section 9.11
    • Supplemental Exercises for Chapter 9
  • Important Terms and Concepts
  • Study Resources
    • Section 9.1 Hypothesis Testing
    • Section 9.2 Tests on the Mean of a Normal Distribution, Variance Known
    • Section 9.3 Tests on the Mean of a Normal Distribution, Variance Unknown
    • Section 9.5 Tests on a Population Proportion
    • Additional Study Resources
  • Readings Content
    • Introduction
    • 9.1 Hypothesis Testing
    • 9.2 Tests on the Mean of a Normal Distribution, Variance Known
    • 9.3 Tests on the Mean of a Normal Distribution, Variance Unknown
    • 9.4 Tests on the Variance and Standard Deviation of a Normal Distribution
    • 9.5 Tests on a Population Proportion
    • 9.6 Summary Table of Inference Procedures for a Single Sample
    • 9.7 Testing for Goodness of Fit
    • 9.8 Contingency Table Tests
    • 9.9 Nonparametric Procedures
    • 9.10 Equivalence Testing
    • 9.11 Combining P-Values
• CHAPTER 10: Statistical Inference for Two Samples
  • Exercises
    • Exercises for Section 10.1
    • Exercises for Section 10.2
    • Exercises for Section 10.3
    • Exercises for Section 10.4
    • Exercises for Section 10.5
    • Exercises for Section 10.6
    • Supplemental Exercises for Chapter 10
  • Important Terms and Concepts
  • Study Resources
    • Section 10.2 Inference on the Difference in Means of Two Normal Distributions, Variances Unknown
    • Section 10.3 A Nonparametric Test for the Difference in Two Means
    • Section 10.4 Paired t-Test
    • Section 10.6 Inference on Two Population Proportions
    • Additional Study Resources
  • Readings Content
    • 10.1 Inference on the Difference in Means of Two Normal Distributions, Variances Known
    • 10.2 Inference on the Difference in Means of Two Normal Distributions, Variances Unknown
    • 10.3 A Nonparametric Test for the Difference in Two Means
    • 10.4 Paired t-Test
    • 10.5 Inference on the Variances of Two Normal Distributions
    • 10.6 Inference on Two Population Proportions
    • 10.7 Summary Table and Road Map for Inference Procedures for Two Samples
• CHAPTER 11: Simple Linear Regression and Correlation
  • Exercises
    • Exercises for Section 11.2
    • Exercises for Section 11.4
    • Exercises for Sections 11.5 and 11.6
    • Exercises for Section 11.7
    • Exercises for Section 11.8
    • Exercises for Section 11.9
    • Exercises for Section 11.10
    • Supplemental Exercises for Chapter 11
  • Important Terms and Concepts
  • Study Resources
    • Section 11.2 Simple Linear Regression
    • Section 11.4 Hypothesis Tests in Simple Linear Regression
    • Section 11.7 Adequacy of the Regression Model
    • Section 11.8 Correlation
    • Section 11.9: Regression on Transformed Variables
    • Additional Study Resources
  • Readings Content
    • 11.1 Empirical Models
    • 11.2 Simple Linear Regression
    • 11.3 Properties of the Least Squares Estimators
    • 11.4 Hypothesis Tests in Simple Linear Regression
    • 11.5 Confidence Intervals
    • 11.6 Prediction of New Observations
    • 11.7 Adequacy of the Regression Model
    • 11.8 Correlation
    • 11.9 Regression on Transformed Variables
    • 11.10 Logistic Regression
• CHAPTER 12: Multiple Linear Regression
  • Exercises
    • Exercises for Section 12.1
    • Exercises for Section 12.2
    • Exercises for Sections 12.3 and 12.4
    • Exercises for Section 12.5
    • Exercises for Section 12.6
    • Supplemental Exercises for Chapter 12
  • Important Terms and Concepts
  • Study Resources
    • Section 12.1 Multiple Linear Regression Model
    • Section 12.2 Hypothesis Tests in Multiple Linear Regression
    • Section 12.5 Model Adequacy Checking
    • Section 12.6 Aspects of Multiple Regression Modeling
    • Additional Study Resources
  • Readings Content
    • 12.1 Multiple Linear Regression Model
    • 12.2 Hypothesis Tests in Multiple Linear Regression
    • 12.3 Confidence Intervals in Multiple Linear Regression
    • 12.4 Prediction of New Observations
    • 12.5 Model Adequacy Checking
    • 12.6 Aspects of Multiple Regression Modeling
• CHAPTER 13: Design and Analysis of Single-Factor Experiments: The Analysis of Variance
  • Exercises
    • Exercises for Section 13.2
    • Exercises for Section 13.3
    • Exercises for Section 13.4
    • Supplemental Exercises for Chapter 13
  • Important Terms and Concepts
  • Study Resources
    • Section 13.2 Completely Randomized Single-Factor Experiment
    • Section 13.3 The Random-Effects Model
    • Section 13.4 Randomized Complete Block Design
    • Additional Study Resources
  • Readings Content
    • 13.1 Designing Engineering Experiments
    • 13.2 Completely Randomized Single-Factor Experiment
    • 13.3 The Random-Effects Model
    • 13.4 Randomized Complete Block Design
• CHAPTER 14: Design of Experiments with Several Factors
  • Exercises
    • Exercises for Section 14.3
    • Exercises for Section 14.4
    • Exercises for Section 14.5
    • Exercises for Section 14.6
    • Exercises for Section 14.7
    • Exercises for Section 14.8
    • Exercises for Section 14.9
    • Exercises for Section 14.10
    • Exercises for Section 14.11
    • Supplemental Exercises for Chapter 14
  • Important Terms and Concepts
  • Study Resources
    • Section 14.3 Two-Factor Factorial Experiments
    • Section 14.4 General Factorial Experiments
    • Section 14.5 2k Factorial Designs
    • Section 14.6 Single Replicate of the 2k Design
    • Additional Study Resources
  • Readings Content
    • 14.1 Introduction
    • 14.2 Factorial Experiments
    • 14.3 Two-Factor Factorial Experiments
    • 14.4 General Factorial Experiments
    • 14.5 2 Factorial Designs
    • 14.6 Single Replicate of the 2 Design
    • 14.7 Addition of Center Points to a 2 Design
    • 14.8 Blocking and Confounding in the 2 Design
    • 14.9 One-Half Fraction of the 2 Design
    • 14.10 Smaller Fractions: The 2 Fractional Factorial
    • 14.11 Response Surface Methods and Designs
• CHAPTER 15: Statistical Quality Control
  • Exercises
    • Exercises for Section 15.3
    • Exercises for Section 15.4
    • Exercises for Section 15.5
    • Exercises for Section 15.6
    • Exercises for Section 15.7
    • Exercises for Section 15.8
    • Exercises for Section 15.10
    • Supplemental Exercises for Chapter 15
  • Important Terms and Concepts
  • Study Resources
    • Section 15.3 X and R or S Control Charts
    • Section 15.4 Control Charts for Individual Measurements
    • Section 15.5 Process Capability
    • Section 15.6 Attribute Control Charts
    • Section 15.7 Control Chart Performance
    • Additional Study Resources
  • Readings Content
    • Bowl of Beads
    • 15.1 Quality Improvement and Statistics
    • 15.2 Introduction to Control Charts
    • 15.3 X¯ and R or S Control Charts
    • 15.4 Control Charts for Individual Measurements
    • 15.5 Process Capability
    • 15.6 Attribute Control Charts
    • 15.7 Control Chart Performance
    • 15.8 Time-Weighted Charts
    • 15.9 Other SPC Problem-Solving Tools
    • 15.10 Decision Theory
    • 15.11 Implementing SPC
• Appendices
  • Appendix A: Statistical Tables and Charts
  • Appendix B: Bibliography
  • Appendix C: Summary of Confidence Intervals and Hypothesis Testing Equations for One‐ and Two Sample Applications
• Glossary
• Index
• End User License Agreement

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