The figure shown to the right contains a scatter plot of 10 data points for trees, where the diameter ofa tree at breast height (Dbh) is given in inches and the height is given in feet. The regression model isshown below, where x is the Dbh in inches and y is the height in feet.y = 0.91x +4.39(A) Interpret the slope of the model.O A. The rate of change of height with respect to Dbh is 4.39 in/ft.O B. The rate of change of height with respect to Dbh is 0.91 ft/in.O C. The rate of change of height with respect to Dbh is 4.39 ft/in.O D. The rate of change of height with respect to Dbh is 0.91 in/ft.Height (ft)40-016Dbh (in)25

Given, The Regression model is shown below, where x is the Dbh in inches and y is the height in…

Answered: The figure shown to the right contains…

Advanced Engineering Mathematics

10th Edition

ISBN:9780470458365

Author:Erwin Kreyszig

Publisher:Erwin Kreyszig

Chapter2: Second-order Linear Odes

Section: Chapter Questions

Problem 1RQ

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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=-1.319 b=38.85 r2=0.720801 r=-0.849 Use this to predict the number of situps a person who watches 7.5 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 (x) and number of situps a person can do (y). The results of the regression were: y=ax+b a=-1.204 b=27.142 r2=0.910116 r=-0.954 Use this to predict the number of situps a person who watches 7 hour(s) of TV can do, and please round your answer to a whole number. Question Help: Message instructor Submit Question 用 hp -> DII 23 2$ 3. 4 6. 7. 8 y k f
What is the interpretation of the intercept regression coefficient in a regression model? A. The change in X for a unit increase of Y B. The change in Y for a unit increase of X C. The estimated value of the dependent variable when X takes the value 1 D. The estimated value of the dependent variable when X takes the value 0
Fit a linear regression model for the following data.
Interpret the intercept and the coefficients of D1 and D2 in the regression above.
A set of X and Y scores has SSX = 15, SSY = 24, and SP = 60. The regression equation for these scores will have a slope constant of ______. a. 6 b. 5 c. 3 d. 4
Using the weights (lb) and highway fuel consumption amounts (mi/gal) of the 48 cars listed in the accompanying data set, one gets this regression equation: y = 58.9-0.00749x, where x represents weight. Complete parts (a) through (d). Click the icon to view the car data. The site to your captio V.UVITU. D. The slope is -0.00749 and the y-intercept is 58.9. c. What is the predictor variable? ... OA. The predictor variable is highway fuel consumption, which is represented by x. OB. The predictor variable is highway fuel consumption, which is represented by y. C. The predictor variable is weight, which is represented by x. OD. The predictor variable is weight, which is represented by y. d. Assuming that there is a significant linear correlation between weight and highway fuel consumption, what is the best predicted value for a car that weighs 2994 lb? The best predicted value of highway fuel consumption of a car that weighs 2994 lb is (Round to one decimal place as needed.) mi/gal.
Using the weights (Ib) and highway fuel consumption amounts (mi/gal) of the 48 cars listed in the accompanying data set, one gets this regression equation: y = 58 9-0.00749x, where x represents weight Complete parts (a) through (d). Click the icon to view the car data. 東 b. What are the specific values of the slope and y-intercept of the regression line? O A. The slope is 58.9 and the y-intercept is 0.007499. B. The slope is -0.00749 and the y-intercept is 58.9. O C. The slope is 58.9 and the y-intercept is -0.00749. O D. The slope is 0.00749 and the y-intercept is 58.9. c. What is the predictor variable? O A. The predictor variable is highway fuel consumption, which is represented by x. B. The predictor variable is weight, which is represented by x. O C. The predictor variable is weight, which is represented by y O D. The predictor variable is highway fuel consumption, which is represented by y. d. Assuming that there is a significant linear correlation between weight and highway fuel…
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=-1.113 b=31.204 r2=0.866761 r=-0.931 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 (x) and number of situps a person can do (y). The results of the regression were: y = a x + b a = -1.043 b = 29.088 %3D %3! r2 = 0.390625 r = -0.625 Use this to predict the number of situps a person who watches 6.5 hours of TV can do. situps : %3D [one decimal accuracy1

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