The sample correlation coefficients for Y and X_1, Y and X_2, and X_1 and X_2 ar

Question

The sample correlation coefficients for Y and X_1, Y and X_2, and X_1 and X_2 are r_yx1 = 0.7558, r_yx2 = -0.0548, and r_x1x2 = 0.1354, respectively. And the regression equation for predicting Y given X_1 and X_2 is Y^1 = 3.60X_1 + -0.10X_2 + 2908.31. What proportion of the variability in babies' birth weights is explained by the multiple regression equation? Suppose that instead you compute a regression equation to predict the baby's birth weight that uses only mother's age (X_1). The difference in the proportion of the variance in babies' birth weights explained by the multiple regression equation and that explained by a regression equation using only X_1 is 0.44.

Explanation / Answer

Proportion of variablity in babies weight is explaned by multiple regression is 0.60.

proportion of variablity of the babies birth weight explained by the multiple regression equation is 0.571

Related Questions

Navigate

• Browse (All)
• Browse T
• Subjects

---

---

Integrity-first tutoring: explanations and feedback only — we do not complete graded work. Learn more.