Still quite new to R (and statistics to be honest) and I have currently only used it for simple linear regression models. But now one of my data sets clearly shows a inverted U pattern. I think I have to do a quadratic regression analysis on this data, but I'm not sure how. What I tried so far is:
independentvar2 <- independentvar^2
regression <- lm(dependentvar ~ independentvar + independentvar2)
summary (regression)
plot (independentvar, dependentvar)
abline (regression)
While this would work for a normal linear regression, it doesn't work for non-linear regressions. Can I even use the lm function since I thought that meant linear model?
Thanks Bert
This example is from this SO post by @Tom Liptrot.
plot(speed ~ dist, data = cars)
fit1 = lm(speed ~ dist, cars) #fits a linear model
plot(speed ~ dist, data = cars)
abline(fit1) #puts line on plot
fit2 = lm(speed ~ I(dist^2) + dist, cars) #fits a model with a quadratic term
fit2line = predict(fit2, data.frame(dist = -10:130))