Q8/Linearized the model below and use the data to find(a4, B4):0.1 0.20406 0.9 1.3 15 1.7 1.80.751.25 145 1.25 0.85 0.55 0.35 0.28 0.18

In the case where the independent variables and dependent variables are not linearly related to each…

Answered: Linearized the model below and use the…

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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A regression was run to determine if there is a relationship between hours of TV watched per day (x) and number of situps a person can do (y). The results of the regression were: y-a+bx a=37,525 b=-1.215 =0,790321 T==0,889 Use this to predict the number of situps a person who watches 6.5 hours of TV can do (to one decimal place) 19.7 Question Help: o Message instructor Submit Question MacBook Pro esc 288 F4 F3 F7 #3 & 2 6 7 Q T Y A S G C V B * LO
A regression was run to determine if there is a relationship between hours of TV watched per day (x) and number of situps a person can do (y). The results of the regression were: y=ax+b a=-1.307 b=32.392 r²=0.675684 r=-0.822 Use this to predict the number of situps a person who watches 12.5 hours of TV can do (to one decimal place)
Find the multiple regression model of the given data: y A B с D E F 8.0 19.6 94.9 5.2 2.3 2.1 29.6 8.3 19.8 89.7 5.2 1.8 2.1 32.4 8.5 19.6 96.2 5.5 2.0 2.1 31.0 8.8 18.6 95.6 5.8 1.9 2.0 32.4 9.0 18.8 86.5 6.4 1.8 2.2 32.6 9.3 20.4 84.5 5.8 2.1 2.1 32.2 9.5 20.8 88.9 5.5 1.9 2.2 31.8 Suppose that the regressors are grouped by Group 1: A, C, and F; and Group 2: B, D, and E. Find the multiple regression model.
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Which of the following is the most appropriate equation to model the data? ŷ = –10.89x + 0.85 ŷ = –0.85x + 10.89 ŷ = 10.89(0.85)x ŷ = 0.85(10.89)x
A regression was run to determine if there is a relationship between hours of TV watched per day (x) and number of situps a person can do (y). The results of the regression were: y=ax+b a=-0.971 b=21.794 r²-0.872356 r=-0.934 Use this to predict the number of situps a person who watches 5 hours of TV can do (to one decimal place)
Perform a linear regression analysis on the following data and determine the "a" coefficient (i.e., slope): Y 4.99 22.19 1.96 9.89 2.98 11 9 40.46 4.04 18.93 6.06 25 0.88 0.19 8.02 34.02 6.97 28.03
in simple linear regression, given the following table : n = 25 E(y,-7) = 1407 %3D SSR = 472 Calculate the standard error of the estimate (s): Select one: Oa. 7.82 Ob. 6.38 Oc. 58.62 d. 34.63 Next
A regression was run to determine if there is a relationship between hours of TV watched per day (x) and number of situps a person can do (y). The results of the regression were: ý=ax+b a=-0.873 b=26.236 r2=0.527076 r=-0.726 Use this to predict the number of situps a person who watches 11 hours of TV can do (to one decimal place)
:::.
A regression was run to determine if there is a relationship between hours of TV watched per day (x) and number of situps a person can do (y). The results of the regression were: y=a+bx b=-0.993 a=29.135 r2=0.463761 r=-0.681 Use this to predict the number of situps a person who watches 6 hours of TV can do. Round to one decimal place.
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Linearized the model below and use the data to find(u4, B4): 0.1 0.2 04 06 0.9 1.3 1.5 1.7 1.8 yl0.75 1.25 1.45 1.25 0.85 0.55 0.35 0.28 0.18