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Please sign and share the petition 'Tighten regulation on taking, making and faking explicit images' at Change.org initiated by Helen Mort to the w:Law Commission (England and Wales) to properly update UK laws against synthetic filth. Only name and email required to support, no nationality requirement. See Current and possible laws and their application @ #SSF! wiki for more info on the struggle for laws to protect humans.

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Toolkit for Quantitative Surveys: Difference between revisions

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* '''[[w:Spearman's rank correlation coefficient|Spearman's rank correlation coefficient]]''' or '''Spearman's rho''', named after [[w:Charles Spearman|Charles Spearman]] and often denoted by the Greek letter rho is a [[w:non-parametric statistics|nonparametric]] measure of [[w:correlation and dependence|statistical dependence]] between two [[w:Variable (mathematics)#Applied statistics|variables]].  It assesses how well the relationship between two variables can be described using a [[w:monotonic|monotonic]] function.  If there are no repeated data values, a perfect Spearman correlation of +1 or −1 occurs when each of the variables is a perfect monotone function of the other. ( Wikipedia )
* '''[[w:Spearman's rank correlation coefficient|Spearman's rank correlation coefficient]]''' or '''Spearman's rho''', named after [[w:Charles Spearman|Charles Spearman]] and often denoted by the Greek letter rho is a [[w:non-parametric statistics|nonparametric]] measure of [[w:correlation and dependence|statistical dependence]] between two [[w:Variable (mathematics)#Applied statistics|variables]].  It assesses how well the relationship between two variables can be described using a [[w:monotonic|monotonic]] function.  If there are no repeated data values, a perfect Spearman correlation of +1 or −1 occurs when each of the variables is a perfect monotone function of the other. ( Wikipedia )
* The '''[[w:Pearson product-moment correlation coefficient|Pearson product-moment correlation coefficient]]'''  (sometimes referred to as the '''PPMCC''' or '''PCC''', or '''Pearson's ''r''''') is a measure of the linear [[w:correlation|correlation]] (dependence) between two variables ''X'' and ''Y'', giving a value between +1 and −1 inclusive, where 1 is total positive correlation, 0 is no correlation, and −1 is total negative correlation. It is widely used in the sciences as a measure of the degree of linear dependence between two variables. It was developed by [[w:Karl Pearson|Karl Pearson]] from a related idea introduced by [[w:Francis Galton|Francis Galton]] in the 1880s.
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