Add fitted quadratic curve

Instead of using abline, use fitted, which gives you a vector the same length as your input of the predictions:

fitted(lm(data~factor+I(factor^2)))
#         1         2         3         4         5         6         7 
# 0.1248016 0.2395833 0.3699405 0.5158730 0.6773810 0.8544643 1.0471230 

Thus, something like:

plot(factor, fitted(lm(data~factor+I(factor^2))), type="l")

I couldn't get answers so far to work, as dataset I used has x-values which are not increasing (as stated by David Robinson above). Here's how I solved it...

require(ISLR)
plot(mpg~horsepower, data=Auto)

# fit the model
glm.fit = glm(mpg~poly(horsepower,2), data=Auto)

# create 100 x-values based on min/max of plotted values
minMax = range(Auto$horsepower)
xVals = seq(minMax[1], minMax[2], len = 100) 

# Use predict based on a dataframe containing 'horsepower'
yVals = predict(glm.fit, newdata = data.frame(horsepower = xVals))

lines(xVals, yVals)