Two measures of a baseball players effectiveness as a hitter are the number of hits he...

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Two measures of a baseball players effectiveness as a hitter are the number of hits he makes in a season and the number of times he "bats in" a run (known as "runs batted in" or RBIS). Can we predict a batter's RBIs from his hits? Below is a numerical and graphical output from a computer regression of RBIS on Hits for 12 randomly selected Major League Baseball batters in 2017. Predictor Constant Hits S = 14.359 R-Sq = T Coef SE Coef 14.98 29.35 0.51 0.3664 0.1915 1.91 P 0.621 0.085 26.8% R-Sq (adj) = 19.5% Assume the conditions for inference have been met. a) Does these data provide convincing evidence that there is a linear relationship between RBIs and Hits for Major League Baseball batters in 2017? b) Construct a 95% confidence interval for the slope of the population regression line for predicting RBIs from hits. Two measures of a baseball players effectiveness as a hitter are the number of hits he makes in a season and the number of times he "bats in" a run (known as "runs batted in" or RBIS). Can we predict a batter's RBIs from his hits? Below is a numerical and graphical output from a computer regression of RBIS on Hits for 12 randomly selected Major League Baseball batters in 2017. Predictor Constant Hits S = 14.359 R-Sq = T Coef SE Coef 14.98 29.35 0.51 0.3664 0.1915 1.91 P 0.621 0.085 26.8% R-Sq (adj) = 19.5% Assume the conditions for inference have been met. a) Does these data provide convincing evidence that there is a linear relationship between RBIs and Hits for Major League Baseball batters in 2017? b) Construct a 95% confidence interval for the slope of the population regression line for predicting RBIs from hits.

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SOLUTION a Hypothesis testing The null hypothesis is that there is no linear relationship between RBIs and Hits for Major League Baseball batters in 2017 The alternative hypothesis is that there is a ... View the full answer