library(ggplot2)
fit <- lm(price ~ lotsize + I(lotsize^2), data = housing)
prd <- data.frame(lotsize = seq(from = range(housing$lotsize)[1], to = range(housing$lotsize)[2], length.out = 100))
err <- predict(fit, newdata = prd, se.fit = TRUE)

prd$lci <- err$fit - 1.96 * err$se.fit
prd$fit <- err$fit
prd$uci <- err$fit + 1.96 * err$se.fit

ggplot(prd, aes(x = lotsize, y = fit)) +
  theme_bw() +
  geom_line() +
  geom_smooth(aes(ymin = lci, ymax = uci), stat = "identity") +
  geom_point(data = housing, aes(x = lotsize, y = price))