The Application of Mathematical Statistics to Chemical Analysis
- 1st Edition - September 12, 2014
- Author: V. V. Nalimov
- Editor: M. Williams
- Language: English
- Paperback ISBN:9 7 8 - 1 - 4 8 3 1 - 6 8 9 8 - 2
- eBook ISBN:9 7 8 - 1 - 4 8 3 1 - 8 4 7 9 - 1
The Application of Mathematical Statistics to Chemical Analysis presents the methods of mathematical statistics as applied to problems connected with chemical analysis. This book… Read more
Purchase options
The Application of Mathematical Statistics to Chemical Analysis presents the methods of mathematical statistics as applied to problems connected with chemical analysis. This book is divided into nine chapters that particularly consider the principal theorems of mathematical statistics that are explained with examples taken from researchers associated with chemical analysis in laboratory work. This text deals first with the problems of mathematical statistics as a means to summarize information in chemical analysis. The next chapters examine the classification of errors, random variables and their characteristics, and the normal distribution in mathematical statistics. These topics are followed by surveys of the application of Poisson's and binomial distribution in radiochemical analysis; the estimation of chemical analytic results; and the principles and application of determination of experimental variance. The last chapters explore the determination of statistical parameters of linear relations and some working methods associated with the statistical design of an experiment. This book will be of great value to analytical chemists and mathematical statisticians.
Publisher's Note
Preface
I. Problems of Mathematical Statistics
II. Classifications of Errors in Chemical Analysis
III. Random Variables and their Characteristics
1. Distribution of a Random Variable.
2. Mean Value of a Random Variable and Variance.
Mean Value of a Random Variable
Variance and Root Mean Square Deviation
3. Calculation of Variances from Current Measurements.
4. Law of Addition of Errors.
5. Errors of Indirect Measurements.
Absorption Spectrophotometric Analysis
Emission Spectrographic Analysis
IV. Normal Distribution
1. Normal Distribution Function.
2. Some Special Distributions Connected with Normal Distribution.
t-distribution
X2-distribution
F-distribution
r-distribution
3. Criteria for Estimating the Degree- of Proximity of the Observed Distribution to the Normal Distribution.
Estimation with the Help of the X2-criterion
Estimation with the Help of the λ-criterion
Verification of the Hypothesis of Normality from a Large Number of Small Samples
Method of Rectified Diagrams
4. Deviations from Normal Distribution in Chemical Analysis.
V. Poisson's Distribution and Binomial Distribution
1. Poisson's Distribution.
2. Evaluation of the Results of Semi-Quantitative Determinations with the Help of Poisson's Distribution.
3. Binomial Distribution.
VI. Estimation of the Results of Chemical Analysis
1. Comparison of two Means with the Help of the t-criterion.
2. Comparison of Several Variances.
3. Verification of the Hypothesis of Homogeneity of Results of Measurements. Estimation of Sharply Separated Determinations.
4. Sequential (Successive) Analysis.
5. Non-Parametric Statistics.
Verification of the Hypothesis of the Existence of a Constant Divergence in the Results of Observations
Verification of the Hypothesis Regarding the Random Nature of Fluctuations
Metrological Estimations on the Basis of Tschebyscheff's Inequality
VII. Analysis of Variance
1. Determination of Variance due to the Effect of One Factor.
Principle of the Method and Simple Examples
Analysis of Variance with Unequal Columns
Conditions in which Analysis of Variance can be Applied
An Example of Application of Analysis of Variance in the Study of Procedural Errors
2. Multi-Stage Classification.
Two-Stage Grouping
Three-Stage Grouping
3. Complex Experiment.
Two-Sided Classification
Three-Sided Classification
4. Design of An Experiment by the Latin-Square Method.
5. Efficiency of Analysis of Variance.
VIII. Statistics of Linear Relations
1. Method of Least Squares.
Determination of the Parameters of a Graduated Graph
Weighted mean of Unequally Accurate Measurements
2. Regression Analysis.
Verification of the Hypothesis of Linearity
Comparison of Parameters of Graduated Graphs with the Theoretically Expected Values
Comparison of Two Graduated Graphs
Verification of the Hypothesis of Parallel Displacement of Graduated Graphs
Estimation of the Results of Analysis Obtained with the Help of a Graduated Graph
3. Correlational Analysis.
4. Application of Complex Design of An Experiment using Different Statistical Methods of Analysis.
IX. Some Working Methods Connected with the Statistical Design of An Experiment
1. Sampling and Randomization of Experimental Conditions. Application of the Table of Random Numbers.
2. Choice of the Number of Parallel Determinations.
3. Documentation of the Material.
4. Control Diagrams.
Bibliography
1. Principal Manuals and Monographs on Mathematical Statistics and the Theory of Probability.
2. Reviews and Bibliographical Sources of Problems Relating to the Application of Mathematical Statistics to Analysis.
3. Articles on Questions Relating to the Application of Mathematical Statistics to Analysis Published in Periodicals and Symposia.
4. Miscellaneous
Appendix
Index
- Edition: 1
- Published: September 12, 2014
- Language: English
MW
M. Williams
Affiliations and expertise
Department of Urology, Addenbrooke’s Hospital, Cambridge, UKRead The Application of Mathematical Statistics to Chemical Analysis on ScienceDirect