Chemometrics in Spectroscopy
eBook - ePub

Chemometrics in Spectroscopy

  1. 558 pages
  2. English
  3. ePUB (mobile friendly)
  4. Available on iOS & Android
eBook - ePub

Chemometrics in Spectroscopy

About this book

Chemometrics in Spectroscopy builds upon the statistical information covered in other books written by these leading authors in the field by providing a broader range of mathematics and progressing into the fundamentals of multivariate and experimental data analysis. Subjects covered in this work include: matrix algebra, analytic geometry, experimental design, calibration regression, linearity, design of collaborative laboratory studies, comparing analytical methods, noise analysis, use of derivatives, analytical accuracy, analysis of variance, and much more are all part of this chemometrics compendium. Developed in the form of a tutorial offering a basic hands-on approach to chemometric and statistical analysis for analytical scientists, experimentalists, and spectroscopists. Without using complicated mathematics, Chemometrics in Spectroscopy demonstrates the basic principles underlying the use of common experimental, chemometric, and statistical tools. Emphasis has been given to problem-solving applications and the proper use and interpretation of data used for scientific research. - Offers basic hands-on approach to chemometric and statistical analysis for analytical scientists, experimentalists, and spectroscopists - Useful for analysts in their daily problem solving, as well as detailed insights into subjects often considered difficult to thoroughly grasp by non-specialists - Provides mathematical proofs and derivations for the student or rigorously-minded specialist

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Information

Publisher
Academic Press
Year
2010
eBook ISBN
9780080548388
Topic
Physical Sciences
Subtopic
Analytic Chemistry

Table of contents

  1. Cover image
  2. Title page
  3. Table of Contents
  4. Preface
  5. Note to Readers
  6. Chapter 1: A New Beginning. . .
  7. Chapter 2: Elementary Matrix Algebra: Part 1
  8. Chapter 3: Elementary Matrix Algebra: Part 2
  9. Chapter 4: Matrix Algebra and Multiple Linear Regression: Part 1
  10. Chapter 5: Matrix Algebra and Multiple Linear Regression: Part 2
  11. Chapter 6: Matrix Algebra and Multiple Linear Regression: Part 3 – The Concept of Determinants
  12. Chapter 7: Matrix Algebra and Multiple Linear Regression: Part 4 – Concluding Remarks
  13. Chapter 8: Experimental Designs: Part 1
  14. Chapter 9: Experimental Designs: Part 2
  15. Chapter 10: Experimental Designs: Part 3
  16. Chapter 11: Analytic Geometry: Part 1 – The Basics in Two and Three Dimensions
  17. Chapter 12: Analytic Geometry: Part 2 – Geometric Representation of Vectors and Algebraic Operations
  18. Chapter 13: Analytic Geometry: Part 3 – Reducing Dimensionality
  19. Chapter 14: Analytic Geometry: Part 4 – The Geometry of Vectors and Matrices
  20. Chapter 15: Experimental Designs: Part 4 – Varying Parameters to Expand the Design
  21. Chapter 16: Experimental Designs: Part 5 – One-at-a-time Designs
  22. Chapter 17: Experimental Designs: Part 6 – Sequential Designs
  23. Chapter 18: Experimental Designs: Part 7 – Ξ², the Power of a Test
  24. Chapter 19: Experimental Designs: Part 8 – Ξ², the Power of a Test (Continued)
  25. Chapter 20: Experimental Designs: Part 9 – Sequential Designs Concluded
  26. Chapter 21: Calculating the Solution for Regression Techniques: Part 1 – Multivariate Regression Made Simple
  27. Chapter 22: Calculating the Solution for Regression Techniques: Part 2 – Principal Component(s) Regression Made Simple
  28. Chapter 23: Calculating the Solution for Regression Techniques: Part 3 – Partial Least Squares Regression Made Simple
  29. Chapter 24: Looking Behind and Ahead: Interlude
  30. Chapter 25: A Simple Question: The Meaning of Chemometrics Pondered
  31. Chapter 26: Calculating the Solution for Regression Techniques: Part 4 – Singular Value Decomposition
  32. Chapter 27: Linearity in Calibration
  33. Chapter 28: Challenges: Unsolved Problems in Chemometrics
  34. Chapter 29: Linearity in Calibration: Act II Scene I
  35. Chapter 30: Linearity in Calibration: Act II Scene II – Reader’s Comments …
  36. Chapter 31: Linearity in Calibration: Act II Scene III
  37. Chapter 32: Linearity in Calibration: Act II Scene IV
  38. Chapter 33: Linearity in Calibration: Act II Scene V
  39. Chapter 34: Collaborative Laboratory Studies: Part 1 – A Blueprint
  40. Chapter 35: Collaborative Laboratory Studies: Part 2 – using ANOVA
  41. Chapter 36: Collaborative Laboratory Studies: Part 3 – Testing for Systematic Error
  42. Chapter 37: Collaborative Laboratory Studies: Part 4 – Ranking Test
  43. Chapter 38: Collaborative Laboratory Studies: Part 5 – Efficient Comparison of Two Methods
  44. Chapter 39: Collaborative Laboratory Studies: Part 6 – MathCad Worksheet Text
  45. Chapter 40: Is Noise Brought by the Stork? Analysis of Noise: Part 1
  46. Chapter 41: Analysis of Noise: Part 2
  47. Chapter 42: Analysis of Noise: Part 3
  48. Chapter 43: Analysis of Noise: Part 4
  49. Chapter 44: Analysis of Noise: Part 5
  50. Chapter 45: Analysis of Noise: Part 6
  51. Chapter 46: Analysis of Noise: Part 7
  52. Chapter 47: Analysis of Noise: Part 8
  53. Chapter 48: Analysis of Noise: Part 9
  54. Chapter 49: Analysis of Noise: Part 10
  55. Chapter 50: Analysis of Noise: Part 11
  56. Chapter 51: Analysis of Noise: Part 12
  57. Chapter 52: Analysis of Noise: Part 13
  58. Chapter 53: Analysis of Noise: Part 14
  59. Chapter 54: Derivatives in Spectroscopy: Part 1 – The Behavior of the Derivative
  60. Chapter 55: Derivatives in Spectroscopy: Part 2 – The β€œTrue” Derivative
  61. Chapter 56: Derivatives in Spectroscopy: Part 3 – Computing the Derivative
  62. Chapter 57: Derivatives in Spectroscopy: Part 4 – Calibrating with Derivatives
  63. Chapter 58: Comparison of Goodness of Fit Statistics for Linear Regression: Part 1 – Introduction
  64. Chapter 59: Comparison of Goodness of Fit Statistics for Linear Regression: Part 2 – The Correlation Coefficient
  65. Chapter 60: Comparison of Goodness of Fit Statistics for Linear Regression: Part 3 – Computing Confidence Limits for the Correlation Coefficient
  66. Chapter 61: Comparison of Goodness of Fit Statistics for Linear Regression: Part 4 – Confidence Limits for Slope and Intercept
  67. Chapter 62: Correction and Discussion Regarding Derivatives
  68. Chapter 63: Linearity in Calibration: Act III Scene I – Importance of Nonlinearity
  69. Chapter 64: Linearity in Calibration: Act III Scene II – A Discussion of the Durbin-Watson Statistic, a Step in the Right Direction
  70. Chapter 65: Linearity in Calibration: Act III Scene III – Other Tests for Nonlinearity
  71. Chapter 66: Linearity in Calibration: Act III Scene IV – How to Test for Nonlinearity
  72. Chapter 67: Linearity in Calibration: Act III Scene V – Quantifying Nonlinearity
  73. Chapter 68: Linearity in Calibration: Act III Scene VI – Quantifying Nonlinearity, Part II, and a News Flash
  74. Chapter 69: Connecting Chemometrics to Statistics: Part 1 – The Chemometrics Side
  75. Chapter 70: Connecting Chemometrics to Statistics: Part 2 – The Statistics Side
  76. Chapter 71: Limitations in Analytical Accuracy: Part 1 – Horwitz’s Trumpet
  77. Chapter 72: Limitations in Analytical Accuracy: Part 2 – Theories to Describe the Limits in Analytical Accuracy
  78. Chapter 73: Limitations in Analytical Accuracy: Part 3 – Comparing Test Results for Analytical Uncertainty
  79. Chapter 74: The Statistics of Spectral Searches
  80. Chapter 75: The Chemometrics of Imaging Spectroscopy
  81. Glossary of Terms
  82. Index

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Yes, you can access Chemometrics in Spectroscopy by Howard Mark,Jerry Workman Jr.,Jerry Workman, Jr. in PDF and/or ePUB format, as well as other popular books in Physical Sciences & Analytic Chemistry. We have over one million books available in our catalogue for you to explore.