The p-values that are computed for each coefficient allow testing the null hypothesis that the coefficients are not significantly different from 0. Note: the squared Pearson correlation coefficient gives an idea of how much of the variability of a variable is explained by the other variable. Its value ranges from -1 to 1, and it measures the degree of linear correlation between two variables. This coefficient is well suited for continuous data. The Pearson coefficient corresponds to the classical linear correlation coefficient. XLSTAT proposes three correlation coefficients to compute the correlation between a set of quantitative variables, whether continuous, discrete or ordinal: Pearson correlation coefficient This tool to compute different kinds of correlation coefficients, between two or more variables, and to determine if the correlations are significant or not.
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