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An R-squared value closer to one indicates a strong relationship between the two variables, though the relationship may be either positive or negative. Another measure of noise in a regression is the standard error, which measures the "spread' around each of the two parameters estimated- the intercept and the slope. Each parameter has an associated standard error, which is calculated from the data -
Standard Error of Intercept = SEa =
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