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As part of a class project at a large university, Amber selected a random sample of 12 students in her major field of study. All students in the sample were asked to report their number of hours spent studying for the final exam and their score on the final exam. A regression analysis on the data produced the following partial computer output. Assume that the conditions for performing inference about the slope of the true regression line are met. Predictor Coef SE CoefConstant 63.328 4.570Study Hours 1.806 0.745 Do these provide evidence at the a=0.05 level of a positive linear association between number of hours of studying and score on final exam?
As part of a class project at a large university, Amber selected a random sample of 12 students in her major field of study. All students in the sample were asked to report their number of hours spent studying for the final exam and their score on the final exam. A regression analysis on the data produced the following partial computer output. Assume that the conditions for performing inference about the slope of the true regression line are met. Predictor Coef SE CoefConstant 63.328 4.570Study Hours 1.806 0.745 Do these provide evidence at the a=0.05 level of a positive linear association between number of hours of studying and score on final exam?
Yes, there is evidence at the a=0.05 level of a positivelinear associationbetween number of hours of studying and score on the final exam based on the regression analysis output.To determine whether there isevidenceof a positive linear association between the number of hours of studying and the score on the final exam, we need to conduct a hypothesis test.The null hypothesis for this test is that there is no relationship between the number of hours of studying and the score on the final exam.The alternativehypothesisis that there is a positive relationship between the two variables.Let's set alpha at 0.05.The computer output provides us with the estimated slope of the true regression line (1.806) and its standard error (0.745).We can use this information to calculate the t-statistic for testing the null hypothesis.t-statistic = (estimated slope - hypothesized slope) / standard errorwhere the hypothesized slope under the null hypothesis is zero.So, the t-statistic is:t = (1.806 - 0) / 0.745 = 2.426Using a t-distribution table with 10 degrees of freedom (n - 2), we find that the critical value of t for a two-tailed test with alpha = 0.05 is approximately 2.306.Since our calculated t-statistic (2.426) is greater than the critical value of t (2.306), we reject the null hypothesis and conclude that there is evidence at the 0.05 level of a positive linear association between the number of hours of studying and the score on the final exam.We can say that as the number of hours of studying increases, thescoreon the final exam tends to increase as well.For similar question onlinear association.brainly.com/question/30318449#SPJ11...