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Statistical Methods for Engineers 3rd Edition by G Geoffrey Vining, Scott Kowalski ISBN 053873518X 978-0538735186

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Statistical Methods for Engineers 3rd edition G. Geoffrey Vining Digital Instant Download

Author(s): G. Geoffrey Vining, Scott Kowalski
ISBN(s): 9780538735186, 053873518X
Edition: 3
File Details: PDF, 87.99 MB
Year: 2010
Language: english
SKU: EB-1677604 Category: Tags: ,

Statistical Methods for Engineers 3rd Edition by G. Geoffrey Vining, Scott Kowalski – Ebook PDF Instant Download/Delivery: 053873518X, 978-0538735186

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Product details:

ISBN 10: 053873518X

ISBN 13: 978-0538735186 

Author: G. Geoffrey Vining, Scott Kowalski

STATISTICAL METHODS FOR ENGINEERS offers a balanced, streamlined one-semester introduction to Engineering Statistics that emphasizes the statistical tools most needed by practicing engineers. Using real engineering problems with real data based on actual journals and consulting experience in the field, users see how statistics fits within the methods of engineering problem solving. The book teaches users how to think like an engineer at analyzing real data and planning a project the same way they will in their careers.

Table of contents:

  1. Engineering method and data collection

  2. Need for statistical methods in engineering

  3. Engineering method and statistical thinking

  4. Statistical thinking and structured problem solving

  5. Models

  6. Obtaining data

  7. Sampling

  8. Basic principles of experimental design

  9. Examples of engineering experiments

  10. Purpose of engineering statistics

  11. Case study: manufacture of writing instruments

  12. Ideas for projects

  13. References

  14. Data displays

  15. Importance of data displays

  16. Stem-and-leaf displays

  17. Boxplots

  18. Using computer software

  19. Using boxplots to analyze designed experiments

  20. Case study

  21. Need for probability and distributions

  22. Ideas for projects

  23. References

  24. Modeling random behavior

  25. Probability

  26. Random variables and distributions

  27. Discrete random variables

  28. Continuous random variables

  29. The normal distribution

  30. Random behavior of means

  31. Random behavior of means when the variance is unknown

  32. Normal approximation to the binomial

  33. The Weibull distribution for reliability applications

  34. Case study

  35. References

  36. Estimation and testing

  37. Estimation

  38. Hypothesis testing

  39. Inference for a single mean

  40. Inference for a single proportion

  41. Inference for two independent samples

  42. The paired t-test

  43. Inference for two proportions

  44. Inference for variances

  45. Transformations and nonparametric analyses

  46. Case study

  47. Ideas for projects

  48. References

  49. Control charts and statistical process control

  50. Overview

  51. Specification limits

  52. X- and R-charts

  53. X- and s-charts

  54. X-chart, np-chart, c-chart

  55. Average run lengths

  56. Standard control charts with runs rules

  57. CUSUM and EWMA charts

  58. Basic process capability indices

  59. The SPC approach to gage R studies

  60. Case study

  61. Ideas for projects

  62. References

  63. Linear regression analysis

  64. Relationships among data

  65. Simple linear regression

  66. Multiple linear regression

  67. Residual analysis

  68. Collinearity diagnostics

  69. Case study

  70. Ideas for projects

  71. References

  72. Introduction to 2k factorial-based experiments

  73. The 2² factorial design

  74. The 2k factorial design

  75. Fractions of the 2k factorial design

  76. Case study

  77. Ideas for projects

  78. References

  79. Introduction to response surface methodology

  80. Sequential philosophy of experimentation

  81. Central composite designs

  82. Box-Behnken designs

  83. Multiple responses

  84. Experimental designs for quality improvement

  85. Case study

  86. Ideas for projects

  87. References

  88. Coda

  89. The themes of this course

  90. Integrating the themes

  91. Statistics and engineering

  92. Appendix

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Tags: G Geoffrey Vining, Scott Kowalski, Statistical, Methods, Engineers