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<font size="3"><span style="font-family: times new roman,times,serif;"> ---+++!! R Notes for Classes Some of R codes for classes are listed where [EMS] refers to [[http://www.blackwellpublishing.com/essentialmedstats][Essential Medical Statistics]]. %TOC% ---++++ [EMS] Chapter 4 Means, standard deviations and standard errors <verbatim> ## population mean and s.d. set.seed(20) mu <- 80 # the mean of population dbp sigma <- 10 # the s.d. of population dbp N <- 20000 Y <- rnorm(N, mean=mu, sd=sigma) hist(Y, xlim=c(40, 120)) n <- 30 # the number of observation in each sample y.sam <- sample(Y, size=n, replace=FALSE) ## estimation of population s.d mean(Y) mean(y.sam) sd(Y) sd(y.sam) bin <- 10 par(mfrow=c(1,2)) hist(Y, xlim=c(40, 120)) hist(y.sam, bin, xlim=c(40, 120)) ## sampling variation n <- 30 n.trial <- 100 # the number of trials y.sam.mean <- rep(NA, n.trial) sampling.var <- function(n, n.trial){ for(i in 1:n.trial){ y.sam <- sample(Y, size=n, replace=FALSE) y.sam.mean[i] <- mean(y.sam) } return(y.sam.mean) } y.sam.mean <- sampling.var(n = n, n.trial=n.trial) par(mfrow=c(1,1)) plot(50.5, mean(Y), xlab="", col=2, pch=15, cex=1.3, xlim=c(1,100), ylim=c(60, 100)) abline(h=mu, col=3, lty=2) points(1:n.trial, y.sam.mean) ## standard error sd(y.sam.mean) sigma/sqrt(n) ## sampling distribution hist(y.sam.mean, bin, xlim=c(40, 120)) y.sam.mean.10 <- sampling.var(n = 10, n.trial=n.trial) # n=10 y.sam.mean.30 <- sampling.var(n = 30, n.trial=n.trial) # n=30 par(mfrow=c(1,2)) hist(y.sam.mean.10, bin, xlim=c(40, 120)) hist(y.sam.mean.30, bin, xlim=c(40, 120)) </verbatim> ---++++ [EMS] Chapter 5 The normal distribution <verbatim> </verbatim>
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Topic revision: r3 - 08 Jan 2007,
LeenaChoi
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