Linear regression is a data relationship algorithm that compares two numerical values by fitting a linear equation to the observed data. It measures the strength and direction of the relationship between the dependent variable (Y) and the independent variable (X) by calculating the slope and the intercept of the line. It also provides a p-value that indicates the significance of the relationship1. The other options are not data relationship algorithms that compare two numerical values. Chi-square is used to compare categorical columns by testing the independence of the frequencies in a contingency table2. Anova is used to compare the mean values of a numerical column across different groups defined by a categorical column3. Kruskal-Wallis is used to compare the ranks of a sortable column across different groups defined by a categorical column. References: 1: Linear Regression - TIBCO Software1, 2: Chi-square - TIBCOSoftware2, 3: Data Relationships Anova Algorithm - TIBCO Software3, : Kruskal-Wallis - TIBCO Software