#Clear environment rm(list=ls()) #set working directory setwd("C:\\RProgs") #set plot directory #jpeg(file = "C:\\RProgs\\mycrimedataplots.jpeg") #load data uscrime=read.table("uscrime.txt",header=TRUE) uscrime1=uscrime #str(uscrime1) # all Rs on top are 1s, the data is not randomized as required #Rs random number generators for mixing up data set.seed(3) #summary(uscrime1) #head(uscrime1) #table(uscrime1$Crime) #summary(uscrime1$Crime) #install.packages("outliers") for (i in 1:3) { cat ("The minimum value and index of Crime ", min(uscrime1$Crime), which.min(uscrime1$Crime)) cat (" The maximum value and index of Crime ", max(uscrime1$Crime), which.max(uscrime1$Crime)) print (" ") library(car) Boxplot(uscrime1$Crime, main = "US Crime Data" , ylab = "US Crimes",col="grey", outcol="red",id.n = Inf) boxplot.stats(uscrime1$Crime)$out #plot without scaling plot(uscrime1$Crime,ylab="Crime data for US",main = "US crime data without scaling") #plot wit scaling plot(scale(uscrime1$Crime),ylab="Crime data for US",main = "US crime data with scaling") library(outliers) # one side outlier #largest g1 = grubbs.test(uscrime1$Crime, type = 10, opposite = FALSE, two.sided = FALSE); print(g1) #smallest g2=grubbs.test(uscrime1$Crime, type = 10, opposite = TRUE, two.sided = FALSE) print(g2) uscrime1 = uscrime1[-which.max(uscrime1$Crime),] summary(uscrime1$Crime) } #if(!is.null(dev.list())) dev.off()