Unformatted text preview: o It tells us change in y that corresponds to x increasing by 1 o B = (Σ ( x  ) ( y  )) / (Σ (x  ) 2 ) The yintercept o This is α, or a (for a sample) o It is the value of y when the line crosses the yintercept (when x=0) o After we find b, then we know that a = Y – b X o If X = 14.4, Y = 4.6, and b =1.4 a = 4.6 – (1.4)14.4 = 15.6 Using the regression line for predictions o Since y = a + b(x), we can predict y if we know b and a If a =10, and b = 2, what is the predicted value of y when X=15? Y = 10 +2(15) = 40 o In the example of age and delinquency: a = 15.6; b = 1.4; r = .87; r 2 = .75 If X = 15, what is the predicted value of Y? Y = 15.6 + (1.4)15 = 15.6 + 21 = 5.4 Does this fit the scatter plot value? About right How much of the variance is explained?...
View
Full Document
 Spring '09
 Kupchick
 Regression Analysis, regression line, perfect negative relationship, perfect positive relationship

Click to edit the document details