Rank Correlation

Options

Correlation type

Choose the type of correlation. The coefficient must be in the range from −1 (100% negative association, or perfect inversion) to +1 (100% positive association, or perfect agreement). A value of zero indicates the absence of association.

• Spearman's Rho: Spearman's rank correlation coefficient is a statistical measure of the strength of a monotonic relationship between paired data. Where the monotonic relationship is characterised by a relationship between ordered sets that preserves the given order, i.e., either never increases or never decreases as its independent variable increases. The value of this measure ranges from -1 (strong negative correlation) to 1 (strong positive correlation). A perfect Spearman correlation of +1 or −1 occurs when each of the variables is a perfect monotone function of the other. For Spearman's rank correlation coefficient the p-value and degrees of freedom are computed. The p-value indicates the probability of an uncorrelated system producing a correlation at least as extreme, if the mean of the correlation is zero and it follows a t-distribution with df degrees of freedom.
• Kendall's Tau A: Kendall's tau rank correlation coefficient is used to measure the strength of association between two measured quantities which is based on the number of concordant and discordant pairs and can be considered as standardized form of Gamma. The Tau A statistic does not consider tied values (two or more observations having the same value) and is mostly suitable for square tables.
• Kendall's Tau B: Kendall's tau rank correlation coefficient is used to measure the strength of association between two measured quantities which is based on the number of concordant and discordant pairs and can be considered as standardized form of Gamma. The Tau B statistic makes adjustments for tied values (two or more observations having the same value) and is most appropriately used for rectangular tables.
• Goodman and Kruskal's Gamma: Goodman and Kruskal's gamma is used to measure the strength of association between two measured quantities. It's based on the number of concordant and discordant pairs.

Correlation columns

Select the columns for which correlation values should be computed.

Include only column pairs with a valid correlation

Check this option if only the column pairs where the correlation could be computed should be included in the output table. Column pairs where the correlation could not be computed are then omitted from the output table.

p-value

Select which p-value should be computed for Spearman's rank correlation coefficient.

• two-sided: Corresponds to the probability of obtaining a correlation value that is at least as extreme as the observed correlation.
• one-sided (right): Corresponds to the probability of obtaining a correlation value that shows even greater positive association.
• one-sided (left): Corresponds to the probability of obtaining a correlation value that shows even greater negative association.

Views

Correlation Matrix

Squared table view showing the pair-wise correlation values of all columns. The color range varies from dark red (strong negative correlation), over white (no correlation) to dark blue (strong positive correlation). If a correlation value for a pair of column is not available, the corresponding cell contains a missing value (shown as cross in the color view).

Workflows

• 01_Data_SummarizationKNIME Hub
• 01. Descriptive StatisticsKNIME Hub
• 01. Descriptive StatisticsKNIME Hub
• 05-k-means-wine-solutionKNIME Hub
• 05-k-means-wine-templateKNIME Hub
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