MoreFinalPracticeSolution - Example: For a certain...

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- 1 - Example: For a certain statistics course, data for student’s scores on Exam 1 are used to try to predict student’s scores on Exam 2. 1. What is the estimated least squares regression line? y_hat = -4.85586 + 0.96325x 2. Is there a linear relationship between Exam 1 and Exam 2? State your hypotheses, test statistic, p-value, and conclusion in terms of the problem. Yes. H 0 : β = 0 H a : β ≠ 0. t = 6.39, P-value < 0.0001. Reject the null, we have a significant linear relationship between Exam 1 and Exam 2 scores. 3. What is the percent of variation in Exam 2 explained by Exam 1. R-square = 0.2943, so 29.43%. 4. What is the estimate for the standard deviation of the error, s e ? Root MSE = 14.05383 5. Give the 95% confidence interval for the regression coefficient for Exam 1. df = n – 2 = 98, use 60 from the table b ± (t crit) s b = 0.96325 ± 2.000(0.15068) = (0.66189, 1.26461) 6. A student received an 82% on Exam 1. What is this student’s predicted score on Exam 2? y_hat = -4.85586 + 0.96325(82) = 74.13064
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This note was uploaded on 02/26/2012 for the course STAT 350 taught by Professor Staff during the Fall '08 term at Purdue University-West Lafayette.

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MoreFinalPracticeSolution - Example: For a certain...

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