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Purpose. Coefficient of determination (R-squared) indicates the proportionate amount of variation in the response variable y explained by the independent variables X in the linear regression model. The larger the R-squared is, the more variability is explained by the linear regression model.
ârÂ²â is the coefficient of determination. This is the most important measure, Wudyka says. It measures the strength of the relationship between two variables (how they âcovaryâ or how much one âexplainsâ the other). What do lines look like at various values of r? In the left top and bottom lines, r is -1 or 1. Very strong, says Wudyka.