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Editorial
. 2012 Mar;165(5):1217-22.
doi: 10.1111/j.1476-5381.2011.01809.x.

Different tests for a difference: how do we do research?

Gordon B Drummond, Sarah L Vowler
Editorial

Different tests for a difference: how do we do research?

Gordon B Drummond et al. Br J Pharmacol. 2012 Mar.
No abstract available

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Figures

Figure 1
Figure 1
The frequentist approach considers the result of taking multiple samples from a known population. The P value is the probability of obtaining such samples, if it were the same population that had been sampled, each time. The samples provide estimates of the original population.
Figure 2
Figure 2
The Bayesian approach is to take a sample that is used to allow further information about the original, not so well-characterized population: the test results give a more firm measure of the original.
Figure 3
Figure 3
The permutation test assembles the observed experimental data in all possible arrangements. Each arrangement would be equally possible if the allocation of data were random. We can then assess the likelihood of the data being distributed the way they have been found to occur.
See this image and copyright information in PMC

References

    1. Abelson RP. Statistics As Principled Argument. Erlbaum: Mahwah, N.J; 1995.
    1. Cohen J. The earth is round (p < .05) Am Psychol. 1994;49:997–1003.
    1. Lew MJ. On contemporaneous controls, unlikely outcomes, boxes and replacing the ‘Student’: good statistical practice in pharmacology, problem 3. Br J Pharmacol. 2008;155:797–803. - PMC - PubMed
    1. Ludbrook J, Dudley H. Why permutation tests are superior to t- and F-tests in biomedical research. Am Stat. 1998;52:127–132.

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