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we used a least-squares regression line to model the relationship between p 3. and miles driven for 41 used Dodge Chargers. The Coefficient of Determination, r', was calculated to be 67%. Interpret the value r=0.67 for this model. %3D

we used a least-squares regression line to model the relationship between p 3. and miles driven for 41 used Dodge Chargers. The Coefficient of Determination, r', was calculated to be 67%. Interpret the value r=0.67 for this model. %3D

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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1. Is it possible to predict the mass of an Atlantic Ocean rockfish from its length? A sample of rockfish was obtained and a linear regression equation for predicting the mass of a fish (in grams) from its length was calculated. The residual plot for that model is shown below. 200 150 100 50 -50 -100 10 15 20 25 30 35 40 Length_cm Use the residual plot to determine if the linear regression model is appropriate. 2. we used a least-squares regression line to model the relationship between the height of a student (inches) and their vertical jump (inches). The standard deviation of the residuals for this model is s = 4.45 inches. Interpret this value. we used a least-squares regression line to model the relationship between pr and miles driven for 41 used Dodge Chargers. The Coefficient of Determination, r, was calculated to be 67%. Interpret the value r=0.67 for this model. Residual 3.
Transcribed Image Text:1. Is it possible to predict the mass of an Atlantic Ocean rockfish from its length? A sample of rockfish was obtained and a linear regression equation for predicting the mass of a fish (in grams) from its length was calculated. The residual plot for that model is shown below. 200 150 100 50 -50 -100 10 15 20 25 30 35 40 Length_cm Use the residual plot to determine if the linear regression model is appropriate. 2. we used a least-squares regression line to model the relationship between the height of a student (inches) and their vertical jump (inches). The standard deviation of the residuals for this model is s = 4.45 inches. Interpret this value. we used a least-squares regression line to model the relationship between pr and miles driven for 41 used Dodge Chargers. The Coefficient of Determination, r, was calculated to be 67%. Interpret the value r=0.67 for this model. Residual 3.
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