Statistics and Chemometrics for Analytical Chemistry (häftad)
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Häftad (Paperback)
Antal sidor
Pearson Education
Miller, Jane C
245 x 190 x 15 mm
610 g
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Statistics and Chemometrics for Analytical Chemistry (häftad)

Statistics and Chemometrics for Analytical Chemistry

Häftad Engelska, 2018-04-16
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This popular textbook provides a clear accessible introduction to main statistical methods used in modern analytical laboratories.
It is the ideal companion for students in Chemistry and related fields keen to build their understanding of how to conduct high quality analyses in areas such as the safety of food, water and medicines, environmental monitoring, and chemical manufacturing. With a focus on the underlying statistical ideas, this book incorporates useful real world examples, step by step explanation and helpful exercises throughout.


Features of the new edition:

 Significant revision of the Quality of analytical measurements chapter to incorporate more detailed coverage of the estimation of measurement uncertainty and the validation of analytical methods.

 Updated coverage of a range of topics including robust statistics, Bayesian methods, and testing for normality of distribution, plus expanded material on regression and calibration methods.

 Additional experimental design methods, including the increasingly popular optimal designs.

 Worked examples have been updated throughout to ensure compatibility with the latest versions of Excel and Minitab.

 Exercises are available at the end of each chapter to allow student to check understanding and prepare for exams.  Answers are provided at the back of the book for handy reference. 

This book is aimed at undergraduate and graduate courses in Analytical Chemistry and related topics.  It will also be a valuable resource for researchers and chemists working in analytical chemistry.


Professor James Miller is Emeritus Professor of Analytical Chemistry at Loughborough University. 


Dr Jane Miller is an experienced author and teacher of mathematics and physics at higher education and 6th form levels. 


Robert Miller has over 20 years experience as an analytical chemist in the water and pharmaceutical industries.
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Professor James Miller is Emeritus Professor of Analytical Chemistry at Loughborough University. He has published numerous reviews and papers on analytical techniques and been awarded the SAC Silver Medal, the Theophilus Redwood Lectureship and the SAC Gold Medal by the Royal Society of Chemsitry. A Past President of the Analytical Division of the RSC, he is currently Chairman of the Divisions's Statistical Sub-Committee. A former member of the Society's Council, he has served on the editorial boards of many analytical and spectroscopic journals. Dr Jane Miller completed a PhD at Cambridge University's Cavendish Laboratory and is an experienced teacher of mathematics and physics at higher education and 6th form levels. She holds an MSc in Applied Statistics from Sheffield Hallam University and is the author of several specialist A-level statistics texts. Robert Miller has an honours degree in chemistry from Southampton University and completed an MSc in Environmental Monitoring at Bradford University. He has over 20 years experience as an analytical chemist in the water and pharmaceutical industries, specialising in the areas of method development and validation.


Preface to the seventh edition

Preface to the first edition


Glossary of symbols

1 Introduction

1.1 Analytical problems

1.2 Errors in quantitative analysis

1.3 Types of error

1.4 Random and systematic errors in titrimetric analysis

1.5 Handling systematic errors

1.6 Planning and design of experiments

1.7 Statistical calculations

Bibliography and resources


2 Statistics of repeated measurements

2.1 Mean and standard deviation

2.2 The distribution of repeated measurements

2.3 Log-normal distribution

2.4 Definition of a sample

2.5 The sampling distribution of the mean

2.6 Confidence limits of the mean for large samples

2.7 Confidence limits of the mean for small samples

2.8 Presentation of results

2.9 Other uses of confidence limits

2.10 Confidence limits of the geometric mean for a log-normal distribution

2.11 Propagation of random errors

2.12 Propagation of systematic errors



3 Significance tests

3.1 Introduction

3.2 Comparison of an experimental mean with a known value

3.3 Comparison of two experimental means

3.4 Paired t-test

3.5 One-sided and two-sided tests

3.6 F-test for the comparison of standard deviations

3.7 Outliers

3.8 Analysis of variance

3.9 Comparison of several means

3.10 The arithmetic of ANOVA calculations

3.11 The chi-squared test

3.12 Testing for normality of distribution

3.13 Conclusions from significance tests

3.14 Bayesian statistics



4 The quality of analytical measurements

4.1 Introduction

4.2 Sampling

4.3 Separation and estimation of variances using ANOVA

4.4 Sampling strategy

4.5 Introduction to quality control methods

4.6 Shewhart charts for mean values

4.7 Shewhart charts for ranges

4.8 Establishing the process capability

4.9 Average run length: CUSUM charts

4.10 Zone control charts (J-charts)

4.11 Proficiency testing schemes

4.12 Method performance studies (collaborative trials)

4.13 Uncertainty

4.14 Acceptance sampling

4.15 Method validation



5 Calibration methods in instrumental analysis: Regression and correlation

5.1 Introduction: instrumental analysis

5.2 Calibration graphs in instrumental analysis

5.3 The productmoment correlation coefficient

5.4 The line of regression of y on x

5.5 Errors in the slope and intercept of the regression line

5.6 Calculation of a concentration and its random error

5.7 Limits of detection

5.8 The method of standard additions

5.9 Use of regression lines for comparing analytical methods