AMS 5 Lecture 10: Class 10 - Regression: Additional Comments

• School: UCSC
• Department: Applied Math and Statistics
• Course: AMS 5
• Professor: Yonatan Katznelson

Document Summary

Interpreting the coefficients: example, x(j) = mathsat score of jth student, y(j) = freshman gpa. : x = 550, sd(x) = 80. : y = 2. 6, sd(y) = 0. 6, r = 0. 4, regression equation, slope coefficient: b1 = r*sd(y)/sd(x) = 0. 003. Intercept coefficient: b0 = y b1*x: equation: ^y(j) = . 95 + . 003x(j) predicted average statistics of all students who scored x(j) on math sat. 95 and . 003 = sample statistics: b1 = . 003 the average increase in gpa for every 1pt percentage in math sat score, remember: correlation does not mean causation, b(0) = . 95 avg. Gpa of all students who scored 0 on math sat. _ : u(0) = x r, y ~ 411. 33, ^x(j) = 411. 33 + 53. 66*y(j, note: putting the ^ over the j (ex: x^(j)) would require you to compute different things. : x = 70 (on scale 0-100)