Statistics and Chemometrics for Analytical Chemistry

This popular textbook gives a clear account of the principles of the main statistical methods used in modern analytical laboratories. Such methods underpin high quality analyses in areas such as the safety of food, water and medicines, environmental monitoring, and chemical manufacturing. The treatment throughout emphasises the underlying statistical ideas, and no detailed knowledge of mathematics is required. There are numerous worked examples, including the use of Microsoft Excel and Minitab, and a large number of student exercises, many of them based on examples from the analytical literature.

Features of the new edition

• introduction to Bayesian methods
• additions to cover method validation and sampling uncertainty
• extended treatment of robust statistics
• new material on experimental design
• additions to sections on regression and calibration methods
• updated Instructors manual
• improved website including further exercises for lecturers and students

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.  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 a former member of the Societys Council and has served on the editorial boards of many analytical and spectroscopic journals.

Dr Jane Miller completed a PhD at Cambridge Universitys 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 and is the author of several specialist A-level statistics texts.

 

 

(Pearson)

Bli först med att recensera och betygsätt boken Statistics and Chemometrics for Analytical Chemistry - du kan vinna 200 kr varje månad i tävlingen "Månadens recension".

"I have found much of interest and use in this book and will no doubt be referring back to it both for teaching (UG and PG) and research purposes." - Frank J M Rutten, School of Pharmacy and EPSAM, Keele University, reviewed in 'Reviews'

(Pearson)

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 Chemistry. A Past President of the Analytical Division of the RSC, he is a former member of the Society's Council and 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 and is the author of several specialist A-level statistics texts.

(Pearson)

1. Introduction
1.1  Analytical problems
1.2  Errors in qunatitative 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  Calculators and computers in statistical calculations
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  Quality control methods - Introduction
4.6  Stewhart charts for mean values
4.7  Stewhart 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  Acceptable sampling

4.15 Method validation
5. Calibration Methods in Instumental Analysis
5.1  Introduction: instrumentational analysis
5.2  Calibration graphs in instrumental analysis
5.3  The product-moment 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
5.10  Weighted regression lines
5.11  Intersection of two straight lines
5.12  ANOVA and regression calculations
5.13&n...

(Pearson)