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Record Nr. |
UNINA9910146074303321 |
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Autore |
Meier Peter C. <1945-> |
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Titolo |
Statistical methods in analytical chemistry [[electronic resource] /] / Peter C. Meier, Richard E. Zünd |
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Pubbl/distr/stampa |
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ISBN |
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1-280-25331-2 |
9786610253319 |
0-470-24805-X |
0-471-72611-7 |
0-471-72841-1 |
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Edizione |
[2nd ed.] |
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Descrizione fisica |
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1 online resource (452 p.) |
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Collana |
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Chemical analysis ; ; v. 153 |
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Altri autori (Persone) |
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Disciplina |
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Soggetti |
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Chemometrics |
Chemistry |
Electronic books. |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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"A Wiley-Interscience publication." |
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Nota di bibliografia |
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Includes bibliographical references (p. 404-415) and index. |
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Nota di contenuto |
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Statistical Methods in Analytical Chemistry; CHEMICAL ANALYSIS; CONTENTS; PREFACE; CHEMICAL ANALYSIS SERIES; INTRODUCTION; CHAPTER 1: UNIVARIATE DATA; 1.1 Mean and Standard Deviation; 1.1.1 The Most Probable Value; 1.1.2 The Dispersion; 1.1.3 Independency of Measurements; 1.1.4 Reproducibility and Repeatibility; 1.1.5 Reporting the Results; 1.1.6 Interpreting the Results; 1.2 Distributions and the Problem of Small Numbers; 1.2.1 The Normal Distribution; 1.2.2 Student's t Distribution; 1.3 Confidence Limits; 1.3.1 Confidence Limits of the Distribution; 1.3.2 Confidence Limits of the Mean |
1.4 The Simulation of a Series of Measurements1.5 Testing for Deviations; 1.5.1 Examining Two Series of Measurements; 1.5.2 The t-Test; 1.5.3 Extension of the t-Test to More Than Two Series of Measurements; 1.5.4 Multiple-Range Test; 1.5.5 Outlier Tests; 1.5.6 Analysis of Variance (ANOVA); 1.6 Number of Determinations; 1.7 Width of a Distribution; 1.7.1 The F-Test; 1.7.2 Confidence Limits for a Standard Deviation; 1.7.3 Bartlett Test; 1.8 Charting a Distribution; |
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1.8.1 Histograms; 1.8.2 X2-Test; 1.8.3 Probability Charts; 1.8.4 Conventional Control Charts (Shewhart Charts); 1.8.5 Cumsum Charts |
1.9 Errors of the First and Second KindCHAPTER 2: BI- AND MULTIVARIATE DATA; 2.1 Correlation; 2.2 Linear Regression; 2.2.1 The Standard Approach; 2.2.2 Slope and Intercept; 2.2.3 Residual Variance; 2.2.4 Testing Linearity and Slope; 2.2.5 Interpolating Y(x); 2.2.6 Interpolating X(y); 2.2.7 Limit of Detection; 2.2.8 Minimizing the Costs of a Calibration; 2.2.9 Standard Addition; 2.2.10 Weighted Regression; 2.2.11 The Intersection of Two Linear Regression Lines; 2.3 Nonlinear Regression; 2.3.1 Linearization; 2.3.2 Nonlinear Regression and Modeling; 2.4 Multidimensional Data/Visualizing Data |
CHAPTER 3: RELATED TOPICS3.1 GMP Background: Selectivity and Interference/Linearity/Accuracy/Precision/Reliability/Economic Considerations; 3.2 Development, Qualification, and Validation; Installation Qualification, Operations Qualification, Performance Qualification/Method Development/Method Validation; 3.3 Data Treatment Scheme: Data Acquisition/Acceptance Criteria/Data Assembly and Clean-up/Data Evaluation/ Presentation of R; 3.4 Exploratory Data Analysis (EDA); 3.5 Optimization Techniques; 3.5.1 Full Factorial vs. Classical Experiments; 3.5.2 Simplex-Guided Experiments |
3.5.3 Optimization of the Model: Curve Fitting3.5.4 Computer Simulation; 3.5.5 Monte Carlo Technique (MCT); 3.6 Smoothing and Filtering Data/Box-Car Averaging/Moving Average/Savitzky-Golay Filtering/CUSUM; 3.7 Error Propagation and Numerical Artifacts; 3.8 Programs; CHAPTER 4: COMPLEX EXAMPLES; 4.1 To Weigh or Not to Weigh; 4.2 Nonlinear Fitting; 4.3 UV-Assay Cost Structure; 4.4 Process Validation; 4.5 Regulations and Realities; 4.6 Diffusing Vapors; 4.7 Stability a la Carte; 4.8 Secret Shampoo Switch; 4.9 Tablet Press Woes; 4.10 Sounding Out Solubility; 4.11 Exploring a Data Jungle |
4.12 Sifting Through Sieved Samples |
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Sommario/riassunto |
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This new edition of a successful, bestselling book continues to provide you with practical information on the use of statistical methods for solving real-world problems in complex industrial environments. Complete with examples from the chemical and pharmaceutical laboratory and manufacturing areas, this thoroughly updated book clearly demonstrates how to obtain reliable results by choosing the most appropriate experimental design and data evaluation methods.Unlike other books on the subject, Statistical Methods in Analytical Chemistry, Second Edition presents and solves problems in the co |
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