x <- rnorm(100) # 100 random numbers from a normal(0,1) distribution y <- exp(x) + rnorm(100) # an exponential function with error result <- lsfit(x,y) # regress x on y and store the results ls.print(result) # print the regression results plot(x,y) # pretty obvious what this does abline(result) # add the regression line to the plot lines(lowess(x,y), col=2) # add a nonparametric regression line (a smoother) hist(result$residuals) # histogram of the residuals from the regression

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