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Regressionn output for predicting the time (in minutes) for baseball games on the number of hits is given below. Interpret the value of R2.

Regressionn output for predicting the time (in minutes) for baseball games on the number of hits is given below. Interpret the value of R2.

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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Regressionn output for predicting the time (in minutes) for baseball games on the number of hits is given below. Interpret the value of R2. The regression equation is Time = 156 + 1.36 Hits Predictor Coef SE Coef T Constant 155.68 12.78 12.18 0.000 Hits 1.3648 0.6932 1.97 0.059 s = 19.5861 R-sq = 12.2% %3D O 12.2% of the variability in hits is explained by by game times. O 12.2% is greater than 0, so the correlation is positive. O 12.2% of game times are accurately predicted by hits. O 12.2% is the correlation between game times and hits. 12.2% of the variability in game times is explained by hits.
Transcribed Image Text:Regressionn output for predicting the time (in minutes) for baseball games on the number of hits is given below. Interpret the value of R2. The regression equation is Time = 156 + 1.36 Hits Predictor Coef SE Coef T Constant 155.68 12.78 12.18 0.000 Hits 1.3648 0.6932 1.97 0.059 s = 19.5861 R-sq = 12.2% %3D O 12.2% of the variability in hits is explained by by game times. O 12.2% is greater than 0, so the correlation is positive. O 12.2% of game times are accurately predicted by hits. O 12.2% is the correlation between game times and hits. 12.2% of the variability in game times is explained by hits.
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