BASED ON THIS ANSWER:
PLEASE ANSWER THIS:
Here is your answer for part B) :-
b) The model for the perturbed data is obtained using R.
x <-
c(1.02,0.95,0.87,0.77,0.67,0.56,0.44,0.30,0.16,0.01)
y <- c(0.39,0.32,0.27,0.22,0.18,0.15,0.13,0.12,0.13,0.15)
px <- x + runif(10,-0.005,0.005)
py <- y + runif(10,-0.005,0.005)
fit <- nls(px^2 ~ a*py^2+b*px*py+c1*px+d*py+e)
fit
Nonlinear regression model: px^2 ~ a * py^2 + b * px *
py + c1 * px + d * py + e
data: parent.frame()
a b c1 d e
-3.3727 0.4601 0.4943 3.3192 -0.4250
residual sum-of-squares: 0.0002957
The new model is
{\color{Blue} -3.373^2+0.46xy+0.494x+3.19y-0.425=x^2}
From the two plots we see the second plot gets enlarged.
BASED ON THIS ANSWER: PLEASE ANSWER THIS: iven -that A Planet Rollout an Fi(tetfoo( orbit, wh...