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 24.1 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 24.1 cm, what is the single value that is the best predicted height for that person? Technology Output The regression equation is Height = 58.8+3.42 Foot Length Coef SE Coef 58.76 11.46 Foot Length 3.4244 0.4189 Predictor Constant S=5.50622 R-Sq=73.3% R-Sq (adj) = 72.6% New Obs T P 5.13 8.17 Predicted Values for New Observations Fit SE Fit 1 141.288 1.765 (136.699, 145.877) 95% CI Foot New Obs Length 1 24.1 0.000 0.000 Values of Predictors for New Observations 95% PI (130.192, 152.384) - X
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 24.1 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 24.1 cm, what is the single value that is the best predicted height for that person? Technology Output The regression equation is Height = 58.8+3.42 Foot Length Coef SE Coef 58.76 11.46 Foot Length 3.4244 0.4189 Predictor Constant S=5.50622 R-Sq=73.3% R-Sq (adj) = 72.6% New Obs T P 5.13 8.17 Predicted Values for New Observations Fit SE Fit 1 141.288 1.765 (136.699, 145.877) 95% CI Foot New Obs Length 1 24.1 0.000 0.000 Values of Predictors for New Observations 95% PI (130.192, 152.384) - X
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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
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 24.1 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 24.1 cm, what is the single
value that is the best predicted height for that person?
Technology Output
The regression equation is
Height = 58.8+3.42 Foot Length
Coef SE Coef
58.76
11.46
Foot Length 3.4244 0.4189
Predictor
Constant
S=5.50622 R-Sq=73.3% R-Sq (adj) = 72.6%
New Obs
T P
5.13
8.17
Predicted Values for New Observations
Fit SE Fit
1 141.288 1.765 (136.699, 145.877)
95% CI
Foot
New Obs Length
1
24.1
0.000
0.000
Values of Predictors for New Observations
95% PI
(130.192, 152.384)
- X
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