What we need to know when calculating the coefficient of correlation
By Martina Udovičić, K. Baždarić, L. Bilić-Zulle, M. Petrovecki. 2007
110 citations recorded by the source corpus.
Abstract: Correlation is a statistical procedure applied to calculate association between two variables. The value of correlation is numerically shown by a coefficient of correlation, most often by Pearson's or Spearman's coefficient, while the significance of the coefficient is expressed by P value. The coefficient of correlation shows the extent to which changes in the value of one variable are correlated to changes in the value of the other. A sign preceding the coefficient of correlation (+ or -) indicates the direction of correlation. The most frequent errors in calculating correlation are related to conditions for calculation, interpretation of the coefficient and correlation significance, high correlation coefficients, assumption of causal relationship, the strength of correlation (coefficient of determination), and comparison of two correlation coefficients.
Subfields: Computer Networks and Communications, Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/7b87867bff40dcfa9ddfa411f96856d9002d91a8
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Statistics and Probability
Citations in the corpus
- Understanding Bland Altman analysis (2015, background): “Correlation describes linear relationship between two sets of data but not their agreement (3).”