Identifying Total Variation What percentage of the total variation in height can be explained by the linear correlation between foot length and height?

Interpreting a Computer Display. In Exercises 9–12, refer to the display obtained by using the paired data consisting of foot lengths (cm) and heights (cm) of 40 people .
(Unlike the examples in this section, these exercises use foot lengths instead of shoe print lengths.) Along with the paired sample data, a foot length of 29.0 cm is used for predicting height.

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The regression equation is Height 64.1 +4.29 Foot Length Predictor Constant Coef SE Coef 64.13 11.49 5.58 0.4460 T P 0.000 9.62 0.000 Foot Length 4.2913 5-5.50571 R-Sq - 70.9 R-Sq (adj) 70.14 Predicted Values for New Observations New Obs Fit SE Fit 1 188.572 1.718 95% CI (185.095, 192.049) 95% PI (176.896, 200.247) Values of Predictors for New Observations Foot New Obs Length 1 29.0