Statistical Methods in Research

  • Domenico SpinaEmail author
Part of the Methods in Molecular Biology book series (MIMB, volume 746)


Statistical methods appropriate in research are described with examples. Topics covered include the choice of appropriate averages and measures of dispersion to summarize data sets, and the choice of tests of significance, including t-tests and a one- and a two-way ANOVA plus post-tests for normally distributed (Gaussian) data and their non-parametric equivalents. Techniques for transforming non-normally distributed data to more Gaussian distributions are discussed. Concepts of statistical power, errors and the use of these in determining the optimal size of experiments are considered. Statistical aspects of linear and non-linear regression are discussed, including tests for goodness-of-fit to the chosen model and methods for comparing fitted lines and curves.

Key words

Statistical analysis Descriptive and comparative statistics Parametric Non-parametric Normal distribution Statistical power 


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Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  1. 1.The Sackler Institute of Pulmonary Pharmacology, School of Biomedical ScienceKing’s College LondonLondonUK

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