The Eurachem reading list

4. Statistics

Web resources

Standards

  • ISO 3534-1:2006. Statistics -- Vocabulary and symbols -- Part 1: General statistical terms and terms used in probability. (www.iso.org)
  • ISO 3534-2:2006. Statistics -- Vocabulary and symbols -- Part 2: Applied statistics. (www.iso.org)
  • ISO 3534-3:2013. Statistics -- Vocabulary and symbols -- Part 3: Design of experiments. (www.iso.org)

Books

  • J. V. Stone, Bayes' Rule: A Tutorial Introduction to Bayesian Analysis, Sebtel Press, 2013, ISBN 0956372848
  • D. C. Montgomery, E. A. Peck, G. G. Vining, Introduction to linear regression analysis, 5th edition, Wiley, 2012, ISBN 978-0-470-54281-1
  • P. Kroese, T. Taimre, Z. I. Botev, Handbook of Monte Carlo methods, Wiley, 2011, ISBN 978-0-470-17793-8
  • M. Thompson and P. J. Lowthian, Notes on statistics and data quality for analytical chemists, Imperial College Press, 2011, ISBN 978-1848166172
  • J. N. Miller, J. C. Miller, Statistics and chemometrics for analytical chemistry, 6th Edition, Prentice Hall, 2010, ISBN 0273730428
  • S. L. R. Ellison, V. J. Barwick, T. J. Duguid Farrant, Practical statistics for the analytical scientist: A bench guide, 2nd Edition, RSC, 2009, ISBN 978 0 85404 131 2
  • D. B. Hibbert, J. J. Gooding, Data Analysis for Chemistry: An Introductory Guide for Students and Laboratory Scientists, Oxford University Press, 2005, ISBN, 978-0195162110
  • E. Mullins, Statistics for the quality control chemistry laboratory, RSC, 2003, ISBN 978 0 85404 671 3
  • I.T. Jolliffe, Principal Component Analysis, 2nd edition, Springer, 2002, ISBN: 0387954422
  • J. D. Jobson, Applied multivariate data analysis - Volume I: Regression and experimental design (Springer Text in Statistics), Springer, corrected edition 1999, ISBN 9780387976600
  • W. P. Gardiner, Statistical analysis methods for chemists: A software based approach, RSC, 1997, ISBN 978 0 85404 549 5
  • J. D. Jobson, Applied multivariate data analysis: Volume II: Categorical and multivariate methods (Springer Texts in Statistics), Springer, 1992, ISBN 9780387978048

Articles and reports

  • J. Kragten, Calculating standard deviations and confidence intervals with a universally applicable spreadsheet technique, Analyst, 1994, 119, 2161-2165 (www.rsc.org)
  • Series “Statistics in Context”, VAM Bulletin (www.lgcgroup.com/nmi):
    • Issue 18, pp18-21: Regression and calibration
    • Issue 19, pp 22-27: Missing values, outliers, robust statistics and non-parametric methods
    • Issue 20, pp 28-31: Analysis of Variance (ANOVA)
    • Issue 21, pp 28-32: Measurement uncertainty and cause and effect analysis
  • AMC Technical Briefs, RSC, (www.rsc.org/Membership/Networking/InterestGroups/Analytical/AMC/TechnicalBriefs.asp):
    • AMC TB 72-2016, AMC Datasets – a resource for analytical scientists
    • AMC TB 69-2015, Using the Grubbs and Cochran tests to identify outliers
    • AMC TB 57-2013, An introduction to non-parametric statistics
    • AMC TB 55-2013, Experimental design and optimisation (4): Plackett-Burman designs
    • AMC TB 52-2013, Bayesian statistics in action
    • AMC TB 50-2012, Robust regression: An introduction
    • AMC TB 39-2009, Rogues and suspects: How to tackle outliers
    • AMC TB 38-2009, Significance, importance and power
    • AMC TB 37-2009, Standard additions: myth and reality
    • AMC TB 36-2009, Experimental design and optimisation (3): some fractional factorial designs
    • AMC TB 30-2008, The standard deviation of the sum of several variables
    • AMC TB 27-2007, Why are we weighting?
    • AMC TB 26-2006, Experimental design and optimisation (2): Handling uncontrolled factors
    • AMC TB 24-2006, Experimental design and optimisation (1): An introduction to some basic concepts
    • AMC TB 23-2006, Mixture models for describing multimodal data
    • AMC TB 14-2003, A glimpse into Bayesian statistics
    • AMC TB 10-2002, Fitting a linear functional relationship to data with error on both variables
    • AMC TB 08-2001, The Bootstrap: A Simple Approach to Estimating Standard Errors and Confidence – Intervals when Theory Fails
    • AMC TB 06-2001, Robust statistics: a method of coping with outliers
    • AMC TB 04-2001 (revised March 2016), Representing data distributions with kernel density estimates

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