Pre-study scores versus post-study scores for a class of 120 college freshman English students were considered. The residual plot for the least squares regression line showed no pattern. The least squares regression line was \hat{y} = 0.2 + 0.9xy^=0.2+0.9x with a correlation coefficient r = 0.76. What percent of the variation of post-study scores can be explained by the variation in pre-study scores? 57.8% 87.2% 52.0% 76.0% We cannot determine the answer using the information given.

Pre-study scores versus post-study scores for a class of 120 college freshman English students were considered. The residual plot for the least squares regression line showed no pattern. The least squares regression line was \hat{y} = 0.2 + 0.9xy^=0.2+0.9x with a correlation coefficient r = 0.76. What percent of the variation of post-study scores can be explained by the variation in pre-study scores? 57.8% 87.2% 52.0% 76.0% We cannot determine the answer using the information given.

Algebra & Trigonometry with Analytic Geometry

13th Edition

ISBN:9781133382119

Author:Swokowski

Publisher:Swokowski

Chapter3: Functions And Graphs

Section3.3: Lines

Problem 76E

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