The estimated regression equation for a model involving two independent variables and 10 observations follows.ŷ = 30.5304 + 0.3088x₁ +0.7485*2a. Interpret b₁ and be in this estimated regression equation (to 4 decimals).b₁ = 0.3088y changes by 0.3088 when x1 increases by 1 unit and x2 stays the sameb₂ = 0.7485y changes by 0.3088 when x1 increases by 1 unit and x2 stays the sameb. Estimate y when *₁ = 180 and 2 = 310 (to 3 decimals).318.14

a.The multiple regression equation is, .

Answered: The estimated regression equation for a…

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=ax+b a=-1.309 b=28.368 r2=0.4096 r=-0.64 Use this to predict the number of situps a person who watches 3 hours of TV can do (to one decimal place)
The relationship between number of chocolate bars consumed (x) and blood sugar content (y) was studied in 16 male college students. The following regression equation was obtained from this study: y= -0.0127 + 0.0180x The above equation implies that: O On average it takes 1.8 Each chocolate bar to increase blood sugar content by 1% O Each chocolate bar consumed increases blood sugar by exactly 0.018 Each chocolate bar consumed increases blood sugar by an average of amount of 1.8% O Each chocolate bar consumed increases blood sugar by 1.27% ere to search
= In a statistics course, a linear regression equation was computed to predict the final-exam score from the score on the first test. The equation as y 10+ 0.75x where y is the final-exam score and x is the score on the first test. Parvez scored 80 on the first test. What is the predicted value of the Parvez's score on the final exam? Parvez scored 60 on the final exam. What is the value of the residual?
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A regression analysis was performed to determine if there is a relationship between hours of TV watched per day (xx) and number of sit ups a person can do (yy). The results of the regression were: y=ax+b a=-1.223 b=22.907 r2=0.600625 r=-0.775 Use this to predict the number of sit ups a person who watches 5 hours of TV can do, and please round your answer to a whole number.
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=-1.226 b=33.622 r²-0.4489 r=-0.67 Use this to predict the number of situps a person who watches 3 hours of TV can do (to one decimal place)
A regression analysis was performed to determine if there is a relationship between hours of TV watched per day (xx) and number of sit ups a person can do (yy). The results of the regression were: y=ax+b a=-1.152 b=30.418 r2=0.703921 r=-0.839 1. Use this to predict the number of sit ups a person who watches 2.5 hours of TV can do, and please round your answer to a whole number
Draw the regression line for the following equation: Y = -3 + (1) X Show your calculation for a low and high value on the predictor value.
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: ŷ=ax+b a=-1.312 b=36.478 r²-0.363609 r=-0.603 Use this to predict the number of situps a person who watches 9.5 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 (xx) and number of situps a person can do (yy).The results of the regression were:y=ax+b a=-1.364 b=32.282 r2=0.398161 r=-0.631 Use this to predict the number of situps a person who watches 4 hour(s) of TV can do, and please round your answer to a whole number.
A regression analysis was performed to determine if there is a relationship between hours of TV watched per day (xx) and number of sit ups a person can do (yy). The results of the regression were: y=ax+b a=-1.013 b=27.906 r2=0.498436 r=-0.706 Use this to predict the number of sit ups a person who watches 12 hours of TV can do, and please round your answer to a whole number.
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=-1.371 b=36.465 ²0.395641 r=-0.629 Use this to predict the number of situps a person who watches 9 hours of TV can do (to one decimal place)

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