Examples of using Correlation coefficient in English and their translations into Greek
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Colloquial
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Computer
A correlation coefficient with a value of 0 reflects the absence of any relationship between the two variables.
with impressive reliability and highest correlation coefficient of 0.974 compared with DEXA& Thermal Printer!
These examples indicate that the correlation coefficient, as a summary statistic,
The PEARSON() function calculates the correlation coefficient of two cell ranges.
The correlation coefficient, like the covariance, is a measure of the extent to which two measurement variables"vary together.".
The information given by a correlation coefficient is not enough to define the dependence structure between random variables.
points, with the correlation coefficient of x and y for each set.
Great accuracy with high correlation coefficient of 0.984 with DEXA,
with the Pearson correlation coefficient of x and y for each set.
The coefficient of determination generalizes the correlation coefficient for relationships beyond simple linear regression.
Details on fitted regression line(log k versus log Pow) and the correlation coefficient of the line including confidence intervals;
Another approach parallels the use of the Fisher transformation in the case of the Pearson product-moment correlation coefficient.
The PEARSON(array1, array2) function returns the Pearson product-moment correlation coefficient between two arrays of data.
that shows the correlation coefficient or covariance, respectively,
that shows the correlation coefficient or covariance, respectively,
corr is a widely used alternative notation for the correlation coefficient.
A negative Spearman correlation coefficient corresponds to a decreasing monotonic trend between X and Y.
A positive Spearman correlation coefficient corresponds to an increasing monotonic trend between X and Y.
The correlation coefficient r between X
The CORREL and PEARSON worksheet functions both calculate the correlation coefficient between two measurement variables when measurements on each variable are observed for each of N subjects.