In X and Y the coefficient correlation is 'r' find out coefficient correlation in 4x&4y
(r): (795 Park 22nd/edition)Correlation coefficient may refer to:* Pearson product-moment correlation coefficient, also known as r, R, or Pearson's r, a measure of the strength and direction of the linear relationship between two variables that is defined as the (sample) covariance of the variables divided by the product of their (sample) standard deviations.* Intraclass correlation, a descriptive statistic that can be used when quantitative measurements are made on units that are organized into groups; describes how strongly units in the same group resemble each other.* Rank correlation, the study of relationships between rankings of different variables or different rankings of the same variable* Spearman's rank correlation coefficient, a measure of how well the relationship between two variables can be described by a monotonic function* Kendall tau rank correlation coefficient, a measure of the portion of ranks that match between two data sets.* Goodman and Kruskal's gamma, a measure of the strength of association of the cross tabulated data when both variables are measured at the ordinal level.In statistics, the Pearson product-moment correlation coefficient (sometimes referred to as the PPMCC or PCC, or Pearson's r) is a measure of the linear 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 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 Karl Pearson from a related idea introduced by FrancisGalton in the 1880s The correlation coefficient ranges from -1 to 1. A value of 1 implies that a linear equation describes the relationship between X and Y perfectly, with all data points lying on a line for which Tincreases as X increases. A value of-1 implies that all data points lie on a line for which Y decreases as X increases. A value of 0 implies that there is no linear correlation between the variables. More generally, note that (Xi - X)(Yi - Y) is positive if and only if Xi and Yi lie on the same side of their respective means. Thus the correlation coefficient is positive if Xi and Yi tend to be simultaneously greater than, or simultaneously less than, their respective means. The correlation coefficient is negative if Xi and Ti tend to lie on opposite sides of their respective means.Correlation Coefficient is given by the formulaTends to lie between - 1 and + 1.0* 'r' value near + 1 - Signals a strong positive association * 'r' value near - 1 - Signals a strong negative association * 'r' = 0 - signals no association between x and y
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Biostatistics