In a simple linear regression problem, the least squares line is $\tilde { y } = - 3.75 + 1.25 x$ , and the coefficient of determination is 0.81. The coefficient of correlation must be -0.90.

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The coefficient of determination (R²) is 0.81, which means the absolute value of the correlation coefficient (r) is the square root of 0.81, i.e., 0.90. However, the sign of r is determined by the slope of the regression line, which is positive (1.25), so r should be +0.90, not -0.90.

In a Simple Linear Regression Problem, the Least Squares Line y~=−3.75+1.25x\tilde { y } = - 3.75 + 1.25 xy~​=−3.75+1.25x

In a Simple Linear Regression Problem, the Least Squares Line $\tilde { y } = - 3.75 + 1.25 x$