A Statistical Manual for Chemists
- 2nd Edition - November 14, 2012
- Latest edition
- Author: Edward Bauer
- Language: English
- Paperback ISBN:9 7 8 - 0 - 1 2 - 3 9 4 2 0 3 - 6
- eBook ISBN:9 7 8 - 0 - 3 2 3 - 1 6 1 9 7 - 8
A Statistical Manual for Chemists, Second Edition presents simple and fast statistical tools for data analysis of working chemists. This edition is organized into nine chapters… Read more
A Statistical Manual for Chemists, Second Edition presents simple and fast statistical tools for data analysis of working chemists. This edition is organized into nine chapters and begins with an overview of the fundamental principles of the statistical techniques used in experimental data analysis. The subsequent chapters deal with the concept of statistical average, experimental design, and analysis of variance. The discussion then shifts to control charts, with particular emphasis on variable charts that are more useful to chemists and chemical engineers. A chapter focuses on the effect of correlated variables and their analysis using various tools. The concluding chapters deal with the theory and aspects of sampling and control of routine analysis. This edition is of great benefit to working chemists and chemical engineers.
Preface to the Second Edition
Preface to the First Edition
List of Symbols
1 Fundamentals
1.1 Introduction
1.2 Experimental Error
1.3 The Average
1.4 The Normal Distribution
1.5 The t Distribution
1.6 Accuracy and Precision
1.7 The Average Deviation
1.8 The Variance and Standard Deviation
1.9 The Range
References
2 The Average
2.1 Replication
2.2 Confidence Limits
2.3 Degree of Confidence
2.4 Illustration of Confidence Limits
2.5 Calculation of Confidence Limits
2.6 Confidence Limits of Large Groups of Data by Range
2.7 Tolerance Limits
2.8 Invalid Measurements
2.9 Derivations and Proofs
References
3 Experimental Design and the Analysis of Variance
3.1 Experimental Design
3.2 Nomenclature of Statistically Designed Experiments
3.3 Tests of Significance
3.4 The Analysis of Variance
3.5 Block Design: One-Way Classification
3.6 Block Design: Two-Way Classification
3.7 Models of ANOVA
3.8 Components of Variance
3.9 Expected Mean Square (EMS) Components
3.10 Latin Square
3.11 Factorial Experiments
3.12 Nested Factorial Experiment
4 The Comparison of Two Averages
4.1 The t Test
4.2 Uses of a t Test
4.3 Substitute t Tests
4.4 Uses of Substitute t Tests
5 Analysis of Variance by Range
5.1 Introduction
5.2 Block Design: One-Way Classification
5.3 Block Design: Two-Way Classification
5.4 Interaction
5.5 The Latin Square Design
5.6 Factorial Experiments
References
6 Control Charts
6.1 Introduction
6.2 Nomenclature
6.3 Theory of Control Charts
6.4 Control Limits
6.5 The Chart for Averages
6.6 The Chart for Ranges (or Standard Deviations)
6.7 Subgroups
6.8 Calculation of Control Limits
6.9 Significance of Control Limits
6.10 Runs
6.11 Making a Control Chart
6.12 Lack of Control
References
7 Correlated Variables
7.1 Linear Regression
7.2 A Laboratory Use of Regression
7.3 Shortcut Methods
7.4 Shortcut Method When Xn Does Not Equal nX1
7.5 Colorimetric Analysis
7.6 Confidence Limits for X
7.7 Nonlinear Functions
Reference
8 Sampling
8.1 The Sample and the Population
8.2 The Theory of Sampling
8.3 Sample Size
8.4 Attribute Sampling
8.5 Sampling by Variables
8.6 Use of Components of Variance
8.7 Variables Plan Based upon Normal Distribution
References
9 Control of Routine Analysis
9.1 Problems of the Routine Analyst
9.2 Test for Outliers
9.3 Precision of the Analyses
9.4 Difference between Analysts
9.5 Accuracy
9.6 Precision of Optical Rotation Measurements
9.7 Precision of Colorimetric Analysis
9.8 Reduced Sample Size
9.9 Compliance with Specifications
9.10 Control Charts in the Analytical Laboratory
9.11 Interlaboratory Studies
Reference
Appendix
Subject Index
- Edition: 2
- Latest edition
- Published: November 14, 2012
- Language: English
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