Simple Linear Regression: Estimating and Comparing Regression Lines using R - Prof. Alexei, Study notes of Data Analysis & Statistical Methods

Download Simple Linear Regression: Estimating and Comparing Regression Lines using R - Prof. Alexei and more Study notes Data Analysis & Statistical Methods in PDF only on Docsity! ## Simple Linear Regression STAT 420 Fall 2008 Examples for 09/23/2008 ## Data x = c(2,6,8,8,12,16,20,20,22,26) y = c(58,105,88,118,117,137,157,169,149,202) N = length(x) ## Estimate the regression line using pre-defined R functions fit = lm(y ~ x) fit summary(fit) names(fit) plot(x, y) abline(fit$coefficients) fit$fitted.values fit$residuals sum(fit$residuals^2) sum((y-fit$fitted.values)^2) s2 = sum(fit$residuals^2)/(N-2); s2 s = sqrt(s2); s ## SXX, SXY, SYY sum((x-mean(x))^2) sum((x-mean(x))*(y-mean(y))) sum((y-mean(y))^2) ## Predicting Y values predict(fit,data.frame(x=10)) predict(fit,data.frame(x=38)) ## Estimate the regression line using pre-defined R functions fit1 = glm(y ~ x) fit1 summary(fit1) names(fit1) ########## ########## ########## ## True relationship alpha = 10 beta = 5 truevar = 10