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The accompanying technology output was obtained by using the paired data consisting of foot lengths (cm) and heights (cm) of a sample of 40 people. Along with the paired sample data, the technology was also given a foot length of 27.5 cm to be used for predicting height. The technology found that there is a linear correlation between height and foot length. If someone has a foot length of 27.5 cm, what is the single value that is the best predicted height for that person? E Click the icon to view the technology output. Technology Output The single value that is the best predicted height is cm. The regression equation is Height = 57.1 + 5.89 Foot Length (Round to the nearest whole number as needed.) Predictor Coef SE Coef P Constant 57.12 11.23 5.09 0.000 Foot Length 5.8888 0.4006 14.70 0.000 S-5.50296 R-Sq - 72.98 R-Sq (adj) - 72.28 Predicted Values for New Observations New Obs Fit SE Fit 95 CI 95 PI 219.062 1.727 (214.309, 223.815) (207.819, 230.305) Values of Predictors for New Observations Foot New Obs Length 1 27.5

The accompanying technology output was obtained by using the paired data consisting of foot lengths (cm) and heights (cm) of a sample of 40 people. Along with the paired sample data, the technology was also given a foot length of 27.5 cm to be used for predicting height. The technology found that there is a linear correlation between height and foot length. If someone has a foot length of 27.5 cm, what is the single value that is the best predicted height for that person? E Click the icon to view the technology output. Technology Output The single value that is the best predicted height is cm. The regression equation is Height = 57.1 + 5.89 Foot Length (Round to the nearest whole number as needed.) Predictor Coef SE Coef P Constant 57.12 11.23 5.09 0.000 Foot Length 5.8888 0.4006 14.70 0.000 S-5.50296 R-Sq - 72.98 R-Sq (adj) - 72.28 Predicted Values for New Observations New Obs Fit SE Fit 95 CI 95 PI 219.062 1.727 (214.309, 223.815) (207.819, 230.305) Values of Predictors for New Observations Foot New Obs Length 1 27.5

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
18th Edition
ISBN:9780079039897
Author:Carter
Publisher:Carter
Chapter10: Statistics
Section10.6: Summarizing Categorical Data
Problem 23PPS
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The accompanying technology output was obtained by using the paired data consisting of foot lengths (cm) and heights (cm) of a sample of 40 people. Along with the paired sample data, the technology was also given a foot length of 27.5 cm to be used for predicting height. The technology found that there is a linear correlation between height and foot length. If someone has a foot length of 27.5 cm, what is the single value that is the best predicted height for that person? Click the icon to view the technology output. Technology Output The regression equation is Height = 57.1+5.89 Foot Length The single value that is the best predicted height is cm. (Round to the nearest whole number as needed.) Predictor Coef SE Coef T P Constant 57.12 11.23 5.09 0.000 Foot Length 5.8888 0.4006 14.70 0.000 S = 5.50296 R-Sq=72.9% R-Sq(adj) = 72.2% Predicted Values for New Observations New Obs Fit SE Fit 95% CI 95% PI 1 219.062 1.727 (214.309, 223.815) (207.819, 230.305) Values of Predictors for New Observations Foot New Obs Length 1 27.5
Transcribed Image Text:The accompanying technology output was obtained by using the paired data consisting of foot lengths (cm) and heights (cm) of a sample of 40 people. Along with the paired sample data, the technology was also given a foot length of 27.5 cm to be used for predicting height. The technology found that there is a linear correlation between height and foot length. If someone has a foot length of 27.5 cm, what is the single value that is the best predicted height for that person? Click the icon to view the technology output. Technology Output The regression equation is Height = 57.1+5.89 Foot Length The single value that is the best predicted height is cm. (Round to the nearest whole number as needed.) Predictor Coef SE Coef T P Constant 57.12 11.23 5.09 0.000 Foot Length 5.8888 0.4006 14.70 0.000 S = 5.50296 R-Sq=72.9% R-Sq(adj) = 72.2% Predicted Values for New Observations New Obs Fit SE Fit 95% CI 95% PI 1 219.062 1.727 (214.309, 223.815) (207.819, 230.305) Values of Predictors for New Observations Foot New Obs Length 1 27.5
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