lm produces different coefficients in r [duplicate]

I'm trying to using lm(poly) to get a polynomial regression for some points, but got some questions about the regression formula coefficients it returns.

sample like this:

x=seq(1,100)
y=x^2+3*x+7
fit=lm(y~poly(x,2))

Results are:

lm(formula = y ~ poly(x, 2))

Coefficients:

(Intercept)  poly(x, 2)1  poly(x, 2)2  
       3542        30021         7452  

Why are the coefficients not 7,3,2?

Thank you very much!

You need to set the raw argument to TRUE of you don't want to use orthogonal polynomial which is the default

set.seed(101)
N <- 100
x <- rnorm(N, 10, 3)
epsilon <- rnorm(N)
y <- 7 + 3 * x + x^2 + epsilon

coef(lm(y ~ poly(x, 2, raw = TRUE)))

##             (Intercept) poly(x, 2, raw = TRUE)1 
##                  7.8104                  2.7538 
## poly(x, 2, raw = TRUE)2 
##                  1.0150

From the help of the poly function you have

Description:

 Returns or evaluates orthogonal polynomials of degree 1 to
 ‘degree’ over the specified set of points ‘x’. These are all
 orthogonal to the constant polynomial of degree 0.  Alternatively,
 evaluate raw polynomials.

And

raw: if true, use raw and not orthogonal polynomials.

But you can also use what Ferdinand proposed, it works.

coef(lm(y ~ x + I(x^2)))
## (Intercept)           x      I(x^2) 
##      7.8104      2.7538      1.0150