correlation coefficient

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correlation coefficient

[‚kär·ə′lā·shən ‚kō·i′fish·ənt]
(statistics)
A measurement, which is unchanged by both addition and multiplication of the random variable by positive constants, of the tendency of two random variables X and Y to vary together; it is given by the ratio of the covariance of X and Y to the square root of the product of the variance of X and the variance of Y.

correlation coefficient

a measure of the association between two variables. See CORRELATION, PEARSON PRODUCT MOMENT CORRELATION COEFFICIENT, SPEARMAN RANK CORRELATION COEFFICIENT.
References in periodicals archive ?
Therefore all the alternatives can be ranked according to the value of the weighted correlation coefficients so that the best alternative can be selected.
The trends shown in Figures 5 and 11 do not differ as much as in Figure 23, but the correlation coefficients lie under 0.
ix and iy for selection intensity of trait x and y, rg for genetic correlation coefficient of trait x and y; Hx and Hy for evolution of heritability of trait x and y.
So path coefficient analysis technique is a statistical approach which is based on multiple regression and is useful for revealing the direct and indirect effects of the variables in a network of factors like agro/morpho/physio/biochemical traits which is able to separate correlation coefficients into their components of direct and indirect effects (Dewey and Lu, 1959; Wright, 1960).
The correlation coefficients obtained between (a *) and the other parameters are shown in Table 4.
In that table there are five negative correlation coefficients and one positive correlation coefficient, but none of them is statistically significant at a 5% probability level.
Correlation coefficients are useful tools to determine first if a correlation exists and second to determine whether the correlation is a positive or negative relationship.
TABLE 2: CORRELATION COEFFICIENTS DETERMINED BETWEEN THE OBSERVED VALUES AND THOSE PREDICTED ACCORDING TO PONT'S INDEX
The main purpose of this paper is to develop fuzzy correlation coefficients for fuzzy interval data.
The closer the value of the correlation coefficients to the outer values of the interval <-1; 1> is, the stronger the relationship between the two variables .
For analyzing data, in this research the descriptive statistics (average and standard deviation) and inferential methods like Pearson correlation coefficient (in order to investigate the relation between attachment styles and intimacy with marital satisfaction) were used.

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