Description

Book Synopsis


Table of Contents
CHAPTER 1 The Role of Statistics in Engineering.

1-1 The Engineering Method and Statistical Thinking.

1-2 Collecting Engineering Data.

1-3 Mechanistic and Empirical Models.

1-4 Observing Processes Over Time.

CHAPTER 2 Data Summary and Presentation.

2-1 Data Summary and Display.

2-2 Stem-and-Leaf Diagram.

2-3 Histograms.

2-4 Box Plot.

2-5 Time Series Plots.

2-6 Multivariate Data.

CHAPTER 3 Random Variables and Probability Distributions.

3-1 Introduction.

3-2 Random Variables.

3-3 Probability.

3-4 Continuous Random Variables.

3-5 Important Continuous Distributions.

3-6 Probability Plots.

3-7 Discrete Random Variables.

3-8 Binomial Distribution.

3-9 Poisson Process.

3-10 Normal Approximation to the Binomial and Poisson Distributions.

3-11 More than One Random Variable and Independence.

3-12 Functions of Random Variables.

3-13 Random Samples, Statistics, and the Central Limit Theorem.

CHAPTER 4 Decision Making for a Single Sample.

4-1 Statistical Inference.

4-2 Point Estimation.

4-3 Hypothesis Testing.

4-4 Inference on the Mean of a Population, Variance Known.

4-5 Inference on the Mean of a Population, Variance Unknown.

4-6 Inference on the Variance of a Normal Population.

4-7 Inference on a Population Proportion.

4-8 Other Interval Estimates for a Single Sample.

4-9 Summary Tables of Inference Procedures for a Single Sample.

4-10 Testing for Goodness of Fit.

CHAPTER 5 Decision Making for Two Samples.

5-1 Introduction.

5-2 Inference on the Means of Two Populations, Variances Known.

5-3 Inference on the Means of Two Populations, Variances Unknown.

5-4 The Paired t-Test.

5-5 Inference on the Ratio of Variances of Two Normal Populations.

5-6 Inference on Two Population Proportions.

5-7 Summary Tables for Inference Procedures for Two Samples.

5-8 What if We Have More than Two Samples?

CHAPTER 6 Building Empirical Models.

6-1 Introduction to Empirical Models.

6-2 Simple Linear Regression.

6-3 Multiple Regression.

6-4 Other Aspects of Regression.

CHAPTER 7 Design of Engineering Experiments.

7-1 The Strategy of Experimentation.

7-2 Factorial Experiments.

7-3 2k Factorial Design.

7-4 Center Points and Blocking in 2k Designs.

7-5 Fractional Replication of a 2k Design.

7-6 Response Surface Methods and Designs.

7-7 Factorial Experiments With More Than Two Levels.

CHAPTER 8 Statistical Process Control.

8-1 Quality Improvement and Statistical Process Control.

8-2 Introduction to Control Charts.

8-3 X and R Control Charts.

8-4 Control Charts For Individual Measurements.

8-5 Process Capability.

8-6 Attribute Control Charts.

8-7 Control Chart Performance.

8-8 Measurement Systems Capability.

APPENDICES.

APPENDIX A Statistical Tables and Charts.

APPENDIX B Bibliography.

APPENDIX C Answers to Selected Exercises.

INDEX.

Engineering Statistics

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    Order before 4pm today for delivery by Mon 29 Jun 2026.

    A Hardback by Douglas C. Montgomery, George C. Runger, Norma F. Hubele

    7 in stock


      View other formats and editions of Engineering Statistics by Douglas C. Montgomery

      Publisher: John Wiley and Sons Ltd
      Publication Date: 20/12/2010
      ISBN13: 9780470631478, 978-0470631478
      ISBN10: 0470631473

      Description

      Book Synopsis


      Table of Contents
      CHAPTER 1 The Role of Statistics in Engineering.

      1-1 The Engineering Method and Statistical Thinking.

      1-2 Collecting Engineering Data.

      1-3 Mechanistic and Empirical Models.

      1-4 Observing Processes Over Time.

      CHAPTER 2 Data Summary and Presentation.

      2-1 Data Summary and Display.

      2-2 Stem-and-Leaf Diagram.

      2-3 Histograms.

      2-4 Box Plot.

      2-5 Time Series Plots.

      2-6 Multivariate Data.

      CHAPTER 3 Random Variables and Probability Distributions.

      3-1 Introduction.

      3-2 Random Variables.

      3-3 Probability.

      3-4 Continuous Random Variables.

      3-5 Important Continuous Distributions.

      3-6 Probability Plots.

      3-7 Discrete Random Variables.

      3-8 Binomial Distribution.

      3-9 Poisson Process.

      3-10 Normal Approximation to the Binomial and Poisson Distributions.

      3-11 More than One Random Variable and Independence.

      3-12 Functions of Random Variables.

      3-13 Random Samples, Statistics, and the Central Limit Theorem.

      CHAPTER 4 Decision Making for a Single Sample.

      4-1 Statistical Inference.

      4-2 Point Estimation.

      4-3 Hypothesis Testing.

      4-4 Inference on the Mean of a Population, Variance Known.

      4-5 Inference on the Mean of a Population, Variance Unknown.

      4-6 Inference on the Variance of a Normal Population.

      4-7 Inference on a Population Proportion.

      4-8 Other Interval Estimates for a Single Sample.

      4-9 Summary Tables of Inference Procedures for a Single Sample.

      4-10 Testing for Goodness of Fit.

      CHAPTER 5 Decision Making for Two Samples.

      5-1 Introduction.

      5-2 Inference on the Means of Two Populations, Variances Known.

      5-3 Inference on the Means of Two Populations, Variances Unknown.

      5-4 The Paired t-Test.

      5-5 Inference on the Ratio of Variances of Two Normal Populations.

      5-6 Inference on Two Population Proportions.

      5-7 Summary Tables for Inference Procedures for Two Samples.

      5-8 What if We Have More than Two Samples?

      CHAPTER 6 Building Empirical Models.

      6-1 Introduction to Empirical Models.

      6-2 Simple Linear Regression.

      6-3 Multiple Regression.

      6-4 Other Aspects of Regression.

      CHAPTER 7 Design of Engineering Experiments.

      7-1 The Strategy of Experimentation.

      7-2 Factorial Experiments.

      7-3 2k Factorial Design.

      7-4 Center Points and Blocking in 2k Designs.

      7-5 Fractional Replication of a 2k Design.

      7-6 Response Surface Methods and Designs.

      7-7 Factorial Experiments With More Than Two Levels.

      CHAPTER 8 Statistical Process Control.

      8-1 Quality Improvement and Statistical Process Control.

      8-2 Introduction to Control Charts.

      8-3 X and R Control Charts.

      8-4 Control Charts For Individual Measurements.

      8-5 Process Capability.

      8-6 Attribute Control Charts.

      8-7 Control Chart Performance.

      8-8 Measurement Systems Capability.

      APPENDICES.

      APPENDIX A Statistical Tables and Charts.

      APPENDIX B Bibliography.

      APPENDIX C Answers to Selected Exercises.

      INDEX.

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