help:wilcoxon

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+ | [[http://www.sofastatistics.com/userguide.php | Contents]] | ||

+ | [[:help:stats_tests | Statistical Tests Available]] | ||

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+ | ====== Wilcoxon Signed Ranks ====== | ||

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+ | The Wilcoxon Signed Ranks Test (see [[http://en.wikipedia.org/wiki/Wilcoxon_signed-rank_test | Wilcoxon signed-rank test]]) is useful for looking at differences in two variables. The data must be paired e.g. looking at pre and post-diet weight. The variables being averaged must also be measured at an interval level of measurement. | ||

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+ | If your data is numerical and is adequately normally distributed, you may be better using the [[:help:paired_ttest | paired t-test]]. | ||

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+ | If you are looking at independent/unpaired data e.g. height between two countries, the non-parametric equivalent is the [[:help:mann_whitney | Mann-Whitney U Test]]. | ||

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+ | The p value tells you how likely the difference observed would occur if sampling from a population in which there is no actual difference. A small p value tells you that it would be rare to observe such a difference if there is no actual difference between the variables. From this we might reject the null hypothesis in favour of the alternative hypothesis - namely, that there is a difference. | ||

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+ | Be aware that there is a certain sensitivity about terminology around this area. According to a widespread convention, we shouldn't conclude that there is a relationship, only that we reject the null hypothesis (see [[http://www.stats.gla.ac.uk/steps/glossary/hypothesis_testing.html#h0 | Hypothesis testing]]). We might go so far as to reject the null hypothesis in favour of the alternative hypothesis. See [[http://en.wikipedia.org/wiki/Statistical_hypothesis_testing | Statistical hypothesis testing]]. | ||

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+ | [[http://www.sofastatistics.com/userguide.php | Contents]] | ||

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+ | [[:help:stats_tests | Statistical Tests Available]] | ||

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+ | [[:home | Wiki]] |

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