Chemometrics in Spectroscopy, Revised Second Edition provides the reader with the methodology crucial to apply chemometrics to real world data. The book allows scientists using spectroscopic instruments to find explanations and solutions to their problems when they are confronted with unexpected and unexplained results. Unlike other books on these topics, it explains the root causes of the phenomena that lead to these results. While books on NIR spectroscopy sometimes cover basic chemometrics, they do not mention many of the advanced topics this book discusses.
This revised second edition has been expanded with 50% more content on advances in the field that have occurred in the last 10 years, including calibration transfer, units of measure in spectroscopy, principal components, clinical data reporting, classical least squares, regression models, spectral transfer, and more.
1. Chapter 8 Experimental Designs, Part 1: Introduction - p. 57 2. Chapter 9 Experimental Designs, Part 2: One-Way ANOVA☆ - p. 63 3. Chapter 10 Experimental Designs, Part 3: Two-Factor Designs☆ - p. 69 4. Chapter 11 Experimental Designs, Part 4: Varying Parameters to Expand the Design☆ - p. 77 5. Chapter 12 Experimental Designs, Part 5: One-at-a-Time Designs☆ - p. 81 6. Chapter 13 Experimental Designs, Part 6: Sequential Designs☆ - p. 83 7. Chapter 14 Experimental Designs, Part 7: β, the Power of a Test☆ - p. 87 8. Chapter 15 Experimental Designs, Part 8: β, the Power of a Test (Continued)☆ - p. 91 9. Chapter 16 Experimental Designs, Part 9: Sequential Designs (Concluded)☆ - p. 93 10. Chapter 17 Analytic Geometry: Part 1—The Basics in Two and Three Dimensions - p. 99 11. Chapter 18 Analytic Geometry: Part 2—Geometric Representation of Vectors and Algebraic Operations - p. 105 12. Chapter 19 Analytic Geometry: Part 3—Reducing Dimensionality - p. 109 13. Chapter 20 Analytic Geometry: Part 4—The Geometry of Vectors and Matrices - p. 113 14. Chapter 21 Calculating the Solution for Regression Techniques: Part 1—Multivariate Regression Made Simple - p. 119 15. Chapter 22 Calculating the Solution for Regression Techniques: Part 2—Principal Component(s) Regression Made Simple - p. 121 16. Chapter 23 Calculating the Solution for Regression Techniques: Part 3—Partial Least Squares Regression Made Simple - p. 125 17. Chapter 24 Calculating the Solution for Regression Techniques: Part 4—Singular Value Decomposition - p. 129 18. Chapter 25 Interlude: Looking Behind and Ahead☆ - p. 133 19. Chapter 26 A Simple Question☆ - p. 135 20. Chapter 27 Challenges: Unsolved Problems in Chemometrics☆ - p. 143 21. Chapter 28 Linearity in Calibration— Act I—A Thought Experiment Carried Out by Computer Simulation☆ - p. 151 22. Chapter 29 Linearity in Calibration—Act II Scene I—A Firestorm Erupts and A Theoretical Explanation of Linearity - p. 157 23. Chapter 30 Linearity in Calibration—Act II Scene II—Details of Reader Responses☆ - p. 161 24. Chapter 31 Linearity in Calibration—Act II Scene III—Summary of Reader Responses, and Our Commentary on Those Responses☆ - p. 165 25. Chapter 32 Linearity in Calibration—Act II Scene IV—A Summary of Findings and Recommendations for Future Explorations☆ - p. 175 26. Chapter 33 Linearity in Calibration—Act II Scene V—Effect of (Non) Linearity on PLS Algorithm☆ - p. 179 27. Chapter 34 Collaborative Laboratory Studies: Part 1—A Blueprint - p. 185 28. Chapter 35 Collaborative Laboratory Studies: Part 2—Using ANOVA - p. 197 29. Chapter 36 Collaborative Laboratory Studies: Part 3—Testing for Systematic Error - p. 201 30. Chapter 37 Collaborative Laboratory Studies: Part 4—Ranking Test - p. 203 31. Chapter 38 Collaborative Laboratory Studies: Part 5—Efficient Comparison of Two Methods - p. 205 32. Chapter 39 Collaborative Laboratory Studies: Part 6—MathCad Worksheet Text - p. 211 33. Chapter 40 Is Noise Brought by the Stork? Analysis of Noise—Part 1—A Listing of the Sources of Spectroscopic Noise and Their Characteristics☆ - p. 233 34. Chapter 41 Analysis of Noise—Part 2—The analysis of the effect of ‘constant’ detector noise on a transmission measurement☆ - p. 237 35. Chapter 42 Analysis of Noise—Part 3—The Analysis of the Effect of ‘constant’ Detector Noise on the Absorbance, the Relative Absorbance (ΔA/A) and the Optimum Absorbance Value☆ - p. 245 36. Chapter 43 Analysis of Noise—Part 4—The Analysis of the Effect of ‘constant’ Gaussian Detector Noise When the Noise Is Not Negligible Compared to the Signal☆ - p. 253 37. Chapter 44 Analysis of Noise—Part 5—The Analysis of the Effect of ‘constant’ Gaussian Detector Noise When the Reference Energy Approaches Zero☆ - p. 263 38. Chapter 45 Analysis of Noise—Part 6—The Analysis of the Effect of ‘constant’ Gaussian Detector Noise: Comparing the Effect of Noise in the Sample Channel Versus Noise in the Reference Channel☆ - p. 271 39. Chapter 46 Analysis of Noise—Part 7—The Analysis of ‘constant’ Detector Noise on the Kubelka-Munk Function - p. 277 40. Chapter 47 Analysis of Noise—Part 8—Effect of Noise on the Computed Transmittance, Analysis of Uniformly Distributed Noise for Transmittance and Absorbance Values☆ - p. 289 41. Chapter 48 Analysis of Noise—Part 9—Analysis of Poisson-Distributed Noise, Effects on Transmittance and Absorbance Values☆ - p. 297 42. Chapter 49 Analysis of Noise—Part 10—Analysis of Poisson-Distributed Noise, Effects on Relative Absorbance☆ - p. 305 43. Chapter 50 Analysis of Noise—Part 11—Analysis of Poisson-Distributed Noise, When the Noise Is Not Small Compared to the Reference Signal☆ - p. 311 44. Chapter 51 Analysis of Noise—Part 12—Analysis of Poisson-Distributed Noise: Computation of the Transmittance Noise☆ - p. 323 45. Chapter 52 Analysis of Noise—Part 13—Analysis of Poisson-Distributed Noise: Computation of the Absorbance Noise☆ - p. 327 46. Chapter 53 Analysis of Noise—Part 14—Analysis of Noise Proportional to the Signal, Small-Noise Case☆ - p. 333 47. Chapter 54 Analysis of Noise—Part 15—Analysis of Noise Proportional to the Signal, Large-Noise Case☆ - p. 339 48. Chapter 55 Derivatives in Spectroscopy: Part 1—The Behavior of the Theoretical Derivative☆ - p. 351 49. Chapter 56 Derivatives in Spectroscopy: Part 2—The “True” Derivative☆ - p. 363 50. Chapter 57 Derivatives in Spectroscopy: Part 3—Computing the Derivative (the Savitzky-Golay Method)☆ - p. 371 51. Chapter 58 Derivatives in Spectroscopy: Part 4—Calibrating With Derivatives☆ - p. 383 52. Chapter 59 Corrections and Discussion Regarding Derivatives☆ - p. 391 53. Chapter 60 Comparison of Goodness of Fit Statistics for Linear Regression: Part 1—Introduction - p. 401 54. Chapter 61 Comparison of Goodness of Fit Statistics for Linear Regression: Part 2—The Correlation Coefficient - p. 407 55. Chapter 62 Comparison of Goodness of Fit Statistics for Linear Regression: Part 3—Computing Confidence Limits for the Correlation Coefficient - p. 415 56. Chapter 63 Comparison of Goodness of Fit Statistics for Linear Regression: Part 4—Confidence Limits for Slope and Intercept - p. 421 57. Chapter 64 Linearity in Calibration, Act III Scene I: Importance of (Non)linearity☆ - p. 427 58. Chapter 65 Linearity in Calibration, Act III Scene II: A Discussion of the Durbin-Watson Statistic, a Step in the Right Direction☆ - p. 433 59. Chapter 66 Linearity in Calibration, Act III Scene III: Other Tests for Nonlinearity☆ - p. 441 60. Chapter 67 Linearity in Calibration, Act III Scene IV: How Test for Nonlinearity☆ - p. 445 61. Chapter 68 Linearity in Calibration, Act III Scene V: Quantifying Nonlinearity☆ - p. 457 62. Chapter 69 Linearity in Calibration, Act III, Scene VI: Quantifying Nonlinearity, Part II: A Calculus-Based Approach, and A News Flash☆ - p. 465 63. Chapter 70 Connecting Chemometrics to Statistics: Part 1—The Chemometrics Side☆ - p. 479 64. Chapter 71 Connecting Chemometrics to Statistics: Part 2—The Statistics Side☆ - p. 485 65. Chapter 72 Limitations in Analytical Accuracy: Part 1—Horwitz’s Trumpet - p. 491 66. Chapter 73 Limitations in Analytical Accuracy: Part 2—Theories to Describe the Limits in Analytical Accuracy - p. 497 67. Chapter 74 Limitations in Analytical Accuracy: Part 3—Comparing Test Results for Analytical Uncertainty - p. 501 68. Chapter 75 The Statistics of Spectral Searches - p. 507 69. Chapter 76 The Chemometrics of Imaging Spectroscopy - p. 513 70. Chapter 77 Corrections to Analysis of Noise—Part 1: Alternate Analysis of Transmittance Noise in the ‘large noise’ Regime☆ - p. 521 71. Chapter 78 Corrections to Analysis of Noise—Part 2: Alternate Analysis of Absorbance noise in the ‘large noise’ Regime☆ - p. 529 72. Chapter 79 What Can NIR Predict?☆ - p. 535 73. Chapter 80 The Long, Complicated, Tedious, and Difficult Route to Principal Components (or, When You’re Through Reading This Set You’ll Know Why It's Always Done With Matrices)—Part 1: Introduction and Review - p. 547 74. Chapter 81 The Long, Complicated, Tedious, and Difficult Route to Principal Components (or, When You’re Through Reading This Set You’ll Know Why It's Always Done With Matrices)—Part 2: Our First Attempt☆ - p. 561 75. Chapter 82 The Long, Complicated, Tedious, and Difficult Route to Principal Components (or, When You’re Through Reading This Set You’ll Know Why It's Always Done With Matrices)—Part 3: Multivariate Curve Fitting☆ - p. 569 76. Chapter 83 The Long, Complicated, Tedious, and Difficult Route to Principal Components (or, When you’re Through Reading This Set You’ll Know Why It's Always Done With Matrices)—Part 4: The Lagrange Multiplier☆ - p. 575 77. Chapter 84 The Long, Complicated, Tedious, and Difficult Route to Principal Components (or, When you’re Through Reading This Set You’ll Know Why It's Always Done With Matrices)—Part 5: Solving the Equations With Determinants☆ - p. 581 78. Chapter 85 The Long, Complicated, Tedious, and Difficult Route to Principal Components (or, When You’re Through Reading This Set You’ll Know Why It's Always Done With Matrices)—Part 6: Solving the Equations Without Determinants☆ - p. 587 79. Chapter 86 The Long, Complicated, Tedious, and Difficult Route to Principal Components (or, When You’re Through Reading This Set You’ll Know Why It's Always Done With Matrices)—Coda: Applying Constrained Univariate Calculations☆ - p. 595 80. Chapter 87 Statistics and Chemometrics for Clinical Data Reporting, Part 1—Fundamentals - p. 601 81. Chapter 88 Statistics and Chemometrics for Clinical Data Reporting, Part 2 (Using Excel for Computations) - p. 607 82. Chapter 89 Statistics and Chemometrics for Clinical Data Reporting, Part 3 (Using Excel for Data Plotting) - p. 615 83. Chapter 90 Classical Least Squares, Part 1: MathematicalTheory☆ - p. 629 84. Chapter 91 Classical Least Squares, Part 2: Mathematical Theory Continued☆ - p. 637 85. Chapter 92 Classical Least Squares, Part 3: Spectroscopic Theory☆ - p. 645 86. Chapter 93 Classical Least Squares, Part 4: Spectroscopic Theory Continued☆ - p. 655 87. Chapter 94 Classical Least Squares, Part 5: ExperimentalResults☆ - p. 661 88. Chapter 95 Classical Least Squares, Part 6: Spectral Results☆ - p. 669 89. Chapter 96 Classical Least Squares, Part 7: Spectral Reconstruction of Mixtures☆ - p. 689 90. Chapter 97 Classical Least Squares, Part 8: Comparison of CLS Values With Known Values☆ - p. 697 91. Chapter 98 Classical Least Squares, Part 9: Spectral Results from a Second Laboratory☆ - p. 707 92. Chapter 99 Classical Least Squares, Part 10: Numerical Results From the Second Laboratory☆ - p. 715 93. Chapter 100 Classical Least Squares, Part 11: Comparison of Results From the Two Laboratories (Continued) - p. 725 94. Chapter 101 Transfer of Calibrations, Part 1: An Overview - p. 735 95. Chapter 102 Calibration Transfer, Part 2: The Instrumentation Aspects - p. 751 96. Chapter 103 Calibration Transfer, Part 3: The Mathematical Aspects - p. 765 97. Chapter 104 Calibration Transfer, Part 4: Measuring the Agreement Between Instruments Following Calibration Transfer - p. 777 98. Chapter 105 Calibration Transfer, Part 5: The Mathematics of Wavelength Standards Used for Spectroscopy - p. 787 99. Chapter 106 Calibration Transfer, Part 6: The Mathematics of Photometric Standards Used for Spectroscopy - p. 799 100. Chapter 107 Units of Measure in Spectroscopy, Part 1: … and Then the Light Dawned☆ - p. 811 101. Chapter 108 Units of Measure in Spectroscopy, Part 2:It's the VOLUME, Folks!☆ - p. 815 102. Chapter 109 Units of Measure in Spectroscopy, Part 3: What Does It All Mean☆ - p. 823 103. Chapter 110 Units of Measure in Spectroscopy, Part 4: Summary of Our Findings - p. 829 104. Chapter 111 Units of Measure in Spectroscopy, Part 5: The “Mythbusters” and Spectral Reconstruction - p. 839 105. Chapter 112 Choosing the Best Regression Model - p. 851 106. Chapter 113 Optimizing the Regression Model: The Challenge of Intercept/Bias and Slope “Correction” - p. 863 107. Chapter 114 Statistics, Part 1: First FoundatioN: Probability Theory☆ - p. 877 108. Chapter 115 Statistics, Part 2:Second FoundatioN: Analysis of Variance☆ - p. 883 109. Chapter 116 Statistics, Part 3: Third FoundatioN: Least Squares☆ - p. 891 110. Chapter 117 How to Select the Appropriate Degrees of Freedom for Multivariate Calibration☆ - p. 897 111. Chapter 118 Bias and Slope Correction☆ - p. 903 112. Chapter 119 Outliers—Part 1: What Are Outliers? - p. 913 113. Chapter 120 Outliers—Part 2:Pitfalls in Detecting Outliers☆ - p. 919 114. Chapter 121 Outliers—Part 3: Dealing With Outliers☆ - p. 931 115. Chapter 122 Calibration Transfer Chemometrics, Part 1: Review of the Subject - p. 939 116. Chapter 123 Calibration Transfer Chemometrics, Part 2: Review of the Subject☆ - p. 949 117. Chapter 124 Using Reference Materials, Part 1: Standards for Aligning the x-Axis - p. 959 118. Chapter 125 Using ReferenceMaterials, Part 2:Aligning the y-Axis☆ - p. 981 119. Chapter 126 More about cls, part 1: expanding the concept - p. 1003 120. Chapter 127 More About CLS, Part 2: Spectral Results and CLS (Not Requiring Constituent Values)☆ - p. 1019 121. Chapter 128 More About CLS, Part 3: Expanding the Analysis to Include Concentration Information (PCR and PLS)☆ - p. 1029 122. Index - p. 1041
Chemometrics in Spectroscopy, Revised Second Edition provides the reader with the methodology crucial to apply chemometrics to real world data. The book allows scientists using spectroscopic instruments to find explanations and solutions to their problems when they are confronted with unexpected and unexplained results. Unlike other books on these topics, it explains the root causes of the phenomena that lead to these results. While books on NIR spectroscopy sometimes cover basic chemometrics, they do not mention many of the advanced topics this book discusses.
This revised second edition has been expanded with 50% more content on advances in the field that have occurred in the last 10 years, including calibration transfer, units of measure in spectroscopy, principal components, clinical data reporting, classical least squares, regression models, spectral transfer, and more.
1. Chapter 8 Experimental Designs, Part 1: Introduction - p. 57 2. Chapter 9 Experimental Designs, Part 2: One-Way ANOVA☆ - p. 63 3. Chapter 10 Experimental Designs, Part 3: Two-Factor Designs☆ - p. 69 4. Chapter 11 Experimental Designs, Part 4: Varying Parameters to Expand the Design☆ - p. 77 5. Chapter 12 Experimental Designs, Part 5: One-at-a-Time Designs☆ - p. 81 6. Chapter 13 Experimental Designs, Part 6: Sequential Designs☆ - p. 83 7. Chapter 14 Experimental Designs, Part 7: β, the Power of a Test☆ - p. 87 8. Chapter 15 Experimental Designs, Part 8: β, the Power of a Test (Continued)☆ - p. 91 9. Chapter 16 Experimental Designs, Part 9: Sequential Designs (Concluded)☆ - p. 93 10. Chapter 17 Analytic Geometry: Part 1—The Basics in Two and Three Dimensions - p. 99 11. Chapter 18 Analytic Geometry: Part 2—Geometric Representation of Vectors and Algebraic Operations - p. 105 12. Chapter 19 Analytic Geometry: Part 3—Reducing Dimensionality - p. 109 13. Chapter 20 Analytic Geometry: Part 4—The Geometry of Vectors and Matrices - p. 113 14. Chapter 21 Calculating the Solution for Regression Techniques: Part 1—Multivariate Regression Made Simple - p. 119 15. Chapter 22 Calculating the Solution for Regression Techniques: Part 2—Principal Component(s) Regression Made Simple - p. 121 16. Chapter 23 Calculating the Solution for Regression Techniques: Part 3—Partial Least Squares Regression Made Simple - p. 125 17. Chapter 24 Calculating the Solution for Regression Techniques: Part 4—Singular Value Decomposition - p. 129 18. Chapter 25 Interlude: Looking Behind and Ahead☆ - p. 133 19. Chapter 26 A Simple Question☆ - p. 135 20. Chapter 27 Challenges: Unsolved Problems in Chemometrics☆ - p. 143 21. Chapter 28 Linearity in Calibration— Act I—A Thought Experiment Carried Out by Computer Simulation☆ - p. 151 22. Chapter 29 Linearity in Calibration—Act II Scene I—A Firestorm Erupts and A Theoretical Explanation of Linearity - p. 157 23. Chapter 30 Linearity in Calibration—Act II Scene II—Details of Reader Responses☆ - p. 161 24. Chapter 31 Linearity in Calibration—Act II Scene III—Summary of Reader Responses, and Our Commentary on Those Responses☆ - p. 165 25. Chapter 32 Linearity in Calibration—Act II Scene IV—A Summary of Findings and Recommendations for Future Explorations☆ - p. 175 26. Chapter 33 Linearity in Calibration—Act II Scene V—Effect of (Non) Linearity on PLS Algorithm☆ - p. 179 27. Chapter 34 Collaborative Laboratory Studies: Part 1—A Blueprint - p. 185 28. Chapter 35 Collaborative Laboratory Studies: Part 2—Using ANOVA - p. 197 29. Chapter 36 Collaborative Laboratory Studies: Part 3—Testing for Systematic Error - p. 201 30. Chapter 37 Collaborative Laboratory Studies: Part 4—Ranking Test - p. 203 31. Chapter 38 Collaborative Laboratory Studies: Part 5—Efficient Comparison of Two Methods - p. 205 32. Chapter 39 Collaborative Laboratory Studies: Part 6—MathCad Worksheet Text - p. 211 33. Chapter 40 Is Noise Brought by the Stork? Analysis of Noise—Part 1—A Listing of the Sources of Spectroscopic Noise and Their Characteristics☆ - p. 233 34. Chapter 41 Analysis of Noise—Part 2—The analysis of the effect of ‘constant’ detector noise on a transmission measurement☆ - p. 237 35. Chapter 42 Analysis of Noise—Part 3—The Analysis of the Effect of ‘constant’ Detector Noise on the Absorbance, the Relative Absorbance (ΔA/A) and the Optimum Absorbance Value☆ - p. 245 36. Chapter 43 Analysis of Noise—Part 4—The Analysis of the Effect of ‘constant’ Gaussian Detector Noise When the Noise Is Not Negligible Compared to the Signal☆ - p. 253 37. Chapter 44 Analysis of Noise—Part 5—The Analysis of the Effect of ‘constant’ Gaussian Detector Noise When the Reference Energy Approaches Zero☆ - p. 263 38. Chapter 45 Analysis of Noise—Part 6—The Analysis of the Effect of ‘constant’ Gaussian Detector Noise: Comparing the Effect of Noise in the Sample Channel Versus Noise in the Reference Channel☆ - p. 271 39. Chapter 46 Analysis of Noise—Part 7—The Analysis of ‘constant’ Detector Noise on the Kubelka-Munk Function - p. 277 40. Chapter 47 Analysis of Noise—Part 8—Effect of Noise on the Computed Transmittance, Analysis of Uniformly Distributed Noise for Transmittance and Absorbance Values☆ - p. 289 41. Chapter 48 Analysis of Noise—Part 9—Analysis of Poisson-Distributed Noise, Effects on Transmittance and Absorbance Values☆ - p. 297 42. Chapter 49 Analysis of Noise—Part 10—Analysis of Poisson-Distributed Noise, Effects on Relative Absorbance☆ - p. 305 43. Chapter 50 Analysis of Noise—Part 11—Analysis of Poisson-Distributed Noise, When the Noise Is Not Small Compared to the Reference Signal☆ - p. 311 44. Chapter 51 Analysis of Noise—Part 12—Analysis of Poisson-Distributed Noise: Computation of the Transmittance Noise☆ - p. 323 45. Chapter 52 Analysis of Noise—Part 13—Analysis of Poisson-Distributed Noise: Computation of the Absorbance Noise☆ - p. 327 46. Chapter 53 Analysis of Noise—Part 14—Analysis of Noise Proportional to the Signal, Small-Noise Case☆ - p. 333 47. Chapter 54 Analysis of Noise—Part 15—Analysis of Noise Proportional to the Signal, Large-Noise Case☆ - p. 339 48. Chapter 55 Derivatives in Spectroscopy: Part 1—The Behavior of the Theoretical Derivative☆ - p. 351 49. Chapter 56 Derivatives in Spectroscopy: Part 2—The “True” Derivative☆ - p. 363 50. Chapter 57 Derivatives in Spectroscopy: Part 3—Computing the Derivative (the Savitzky-Golay Method)☆ - p. 371 51. Chapter 58 Derivatives in Spectroscopy: Part 4—Calibrating With Derivatives☆ - p. 383 52. Chapter 59 Corrections and Discussion Regarding Derivatives☆ - p. 391 53. Chapter 60 Comparison of Goodness of Fit Statistics for Linear Regression: Part 1—Introduction - p. 401 54. Chapter 61 Comparison of Goodness of Fit Statistics for Linear Regression: Part 2—The Correlation Coefficient - p. 407 55. Chapter 62 Comparison of Goodness of Fit Statistics for Linear Regression: Part 3—Computing Confidence Limits for the Correlation Coefficient - p. 415 56. Chapter 63 Comparison of Goodness of Fit Statistics for Linear Regression: Part 4—Confidence Limits for Slope and Intercept - p. 421 57. Chapter 64 Linearity in Calibration, Act III Scene I: Importance of (Non)linearity☆ - p. 427 58. Chapter 65 Linearity in Calibration, Act III Scene II: A Discussion of the Durbin-Watson Statistic, a Step in the Right Direction☆ - p. 433 59. Chapter 66 Linearity in Calibration, Act III Scene III: Other Tests for Nonlinearity☆ - p. 441 60. Chapter 67 Linearity in Calibration, Act III Scene IV: How Test for Nonlinearity☆ - p. 445 61. Chapter 68 Linearity in Calibration, Act III Scene V: Quantifying Nonlinearity☆ - p. 457 62. Chapter 69 Linearity in Calibration, Act III, Scene VI: Quantifying Nonlinearity, Part II: A Calculus-Based Approach, and A News Flash☆ - p. 465 63. Chapter 70 Connecting Chemometrics to Statistics: Part 1—The Chemometrics Side☆ - p. 479 64. Chapter 71 Connecting Chemometrics to Statistics: Part 2—The Statistics Side☆ - p. 485 65. Chapter 72 Limitations in Analytical Accuracy: Part 1—Horwitz’s Trumpet - p. 491 66. Chapter 73 Limitations in Analytical Accuracy: Part 2—Theories to Describe the Limits in Analytical Accuracy - p. 497 67. Chapter 74 Limitations in Analytical Accuracy: Part 3—Comparing Test Results for Analytical Uncertainty - p. 501 68. Chapter 75 The Statistics of Spectral Searches - p. 507 69. Chapter 76 The Chemometrics of Imaging Spectroscopy - p. 513 70. Chapter 77 Corrections to Analysis of Noise—Part 1: Alternate Analysis of Transmittance Noise in the ‘large noise’ Regime☆ - p. 521 71. Chapter 78 Corrections to Analysis of Noise—Part 2: Alternate Analysis of Absorbance noise in the ‘large noise’ Regime☆ - p. 529 72. Chapter 79 What Can NIR Predict?☆ - p. 535 73. Chapter 80 The Long, Complicated, Tedious, and Difficult Route to Principal Components (or, When You’re Through Reading This Set You’ll Know Why It's Always Done With Matrices)—Part 1: Introduction and Review - p. 547 74. Chapter 81 The Long, Complicated, Tedious, and Difficult Route to Principal Components (or, When You’re Through Reading This Set You’ll Know Why It's Always Done With Matrices)—Part 2: Our First Attempt☆ - p. 561 75. Chapter 82 The Long, Complicated, Tedious, and Difficult Route to Principal Components (or, When You’re Through Reading This Set You’ll Know Why It's Always Done With Matrices)—Part 3: Multivariate Curve Fitting☆ - p. 569 76. Chapter 83 The Long, Complicated, Tedious, and Difficult Route to Principal Components (or, When you’re Through Reading This Set You’ll Know Why It's Always Done With Matrices)—Part 4: The Lagrange Multiplier☆ - p. 575 77. Chapter 84 The Long, Complicated, Tedious, and Difficult Route to Principal Components (or, When you’re Through Reading This Set You’ll Know Why It's Always Done With Matrices)—Part 5: Solving the Equations With Determinants☆ - p. 581 78. Chapter 85 The Long, Complicated, Tedious, and Difficult Route to Principal Components (or, When You’re Through Reading This Set You’ll Know Why It's Always Done With Matrices)—Part 6: Solving the Equations Without Determinants☆ - p. 587 79. Chapter 86 The Long, Complicated, Tedious, and Difficult Route to Principal Components (or, When You’re Through Reading This Set You’ll Know Why It's Always Done With Matrices)—Coda: Applying Constrained Univariate Calculations☆ - p. 595 80. Chapter 87 Statistics and Chemometrics for Clinical Data Reporting, Part 1—Fundamentals - p. 601 81. Chapter 88 Statistics and Chemometrics for Clinical Data Reporting, Part 2 (Using Excel for Computations) - p. 607 82. Chapter 89 Statistics and Chemometrics for Clinical Data Reporting, Part 3 (Using Excel for Data Plotting) - p. 615 83. Chapter 90 Classical Least Squares, Part 1: MathematicalTheory☆ - p. 629 84. Chapter 91 Classical Least Squares, Part 2: Mathematical Theory Continued☆ - p. 637 85. Chapter 92 Classical Least Squares, Part 3: Spectroscopic Theory☆ - p. 645 86. Chapter 93 Classical Least Squares, Part 4: Spectroscopic Theory Continued☆ - p. 655 87. Chapter 94 Classical Least Squares, Part 5: ExperimentalResults☆ - p. 661 88. Chapter 95 Classical Least Squares, Part 6: Spectral Results☆ - p. 669 89. Chapter 96 Classical Least Squares, Part 7: Spectral Reconstruction of Mixtures☆ - p. 689 90. Chapter 97 Classical Least Squares, Part 8: Comparison of CLS Values With Known Values☆ - p. 697 91. Chapter 98 Classical Least Squares, Part 9: Spectral Results from a Second Laboratory☆ - p. 707 92. Chapter 99 Classical Least Squares, Part 10: Numerical Results From the Second Laboratory☆ - p. 715 93. Chapter 100 Classical Least Squares, Part 11: Comparison of Results From the Two Laboratories (Continued) - p. 725 94. Chapter 101 Transfer of Calibrations, Part 1: An Overview - p. 735 95. Chapter 102 Calibration Transfer, Part 2: The Instrumentation Aspects - p. 751 96. Chapter 103 Calibration Transfer, Part 3: The Mathematical Aspects - p. 765 97. Chapter 104 Calibration Transfer, Part 4: Measuring the Agreement Between Instruments Following Calibration Transfer - p. 777 98. Chapter 105 Calibration Transfer, Part 5: The Mathematics of Wavelength Standards Used for Spectroscopy - p. 787 99. Chapter 106 Calibration Transfer, Part 6: The Mathematics of Photometric Standards Used for Spectroscopy - p. 799 100. Chapter 107 Units of Measure in Spectroscopy, Part 1: … and Then the Light Dawned☆ - p. 811 101. Chapter 108 Units of Measure in Spectroscopy, Part 2:It's the VOLUME, Folks!☆ - p. 815 102. Chapter 109 Units of Measure in Spectroscopy, Part 3: What Does It All Mean☆ - p. 823 103. Chapter 110 Units of Measure in Spectroscopy, Part 4: Summary of Our Findings - p. 829 104. Chapter 111 Units of Measure in Spectroscopy, Part 5: The “Mythbusters” and Spectral Reconstruction - p. 839 105. Chapter 112 Choosing the Best Regression Model - p. 851 106. Chapter 113 Optimizing the Regression Model: The Challenge of Intercept/Bias and Slope “Correction” - p. 863 107. Chapter 114 Statistics, Part 1: First FoundatioN: Probability Theory☆ - p. 877 108. Chapter 115 Statistics, Part 2:Second FoundatioN: Analysis of Variance☆ - p. 883 109. Chapter 116 Statistics, Part 3: Third FoundatioN: Least Squares☆ - p. 891 110. Chapter 117 How to Select the Appropriate Degrees of Freedom for Multivariate Calibration☆ - p. 897 111. Chapter 118 Bias and Slope Correction☆ - p. 903 112. Chapter 119 Outliers—Part 1: What Are Outliers? - p. 913 113. Chapter 120 Outliers—Part 2:Pitfalls in Detecting Outliers☆ - p. 919 114. Chapter 121 Outliers—Part 3: Dealing With Outliers☆ - p. 931 115. Chapter 122 Calibration Transfer Chemometrics, Part 1: Review of the Subject - p. 939 116. Chapter 123 Calibration Transfer Chemometrics, Part 2: Review of the Subject☆ - p. 949 117. Chapter 124 Using Reference Materials, Part 1: Standards for Aligning the x-Axis - p. 959 118. Chapter 125 Using ReferenceMaterials, Part 2:Aligning the y-Axis☆ - p. 981 119. Chapter 126 More about cls, part 1: expanding the concept - p. 1003 120. Chapter 127 More About CLS, Part 2: Spectral Results and CLS (Not Requiring Constituent Values)☆ - p. 1019 121. Chapter 128 More About CLS, Part 3: Expanding the Analysis to Include Concentration Information (PCR and PLS)☆ - p. 1029 122. Index - p. 1041
