# STA 437/1005, Assignment #2, Question #2. # Define functions for multivariate tests and confidence intervals. source("mvn.r") # Read the data into the data frame "twins". twins.data <- read.table("twins.txt",head=T) # Create data frame with differences of first minus second born twin. twins.diff <- data.frame (IQ=twins.data$IQ1-twins.data$IQ2, head=twins.data$head1-twins.data$head2, area=twins.data$area1-twins.data$area2, volume=twins.data$volume1-twins.data$volume2, weight=twins.data$weight1-twins.data$weight2) # Put scatterplots in a PDF file. pdf("ass2-Q2-plots.pdf",pointsize=9,horizontal=F) plot(twins.diff,pch=20,col=c("blue","red")[twins.data$sex]) dev.off() # T-square test. cat("\nT-square test of null hypothesis of no diference\n\n") print(round(Tsq.test(twins.diff,rep(0,ncol(twins.diff))),5)) # 90% confidence intervals for differences. cat("\n90% T-square confidence intervals for differences\n\n") print(round(Tsq.conf.int(twins.diff,level=0.9),3)) cat("\n90% univariate t confidence intervals for differences\n\n") for (i in 1:ncol(twins.diff)) { print(round(t.test(twins.diff[,i],conf.level=0.9)$conf.int[1:2],3)) } cat("\n90% Bonferroni confidence intervals for differences\n\n") for (i in 1:ncol(twins.diff)) { print(round( t.test(twins.diff[,i],conf.level=1-0.1/ncol(twins.diff))$conf.int[1:2],3)) }