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154.25 173.25 154 184.75 184.25 210.25 181 176 191 198.25 186.25 216 180.5 205.25 187.75 162.75 195.75 209.25 183.75 211.75 179 200.5 140.25 148.75 151.25 159.25 131.5 148 133.25 160.75 182 160.25 168 218.5 247.25 191.75 202.25 196.75 203 262.75 217 212 125.25 164.25 133.5 148.5 135.75 127.5 158.25 139.25 137.25 152.75 136.25 198 181.5 201.25 202.5 179.75 216 178.75 193.25 178 205.5 183.5 151.5 154.75 155.25 156.75 167.5 146.75 160.75 125 143 148.25 162.5 177.75 161.25 171.25 163.75 150.25 190.25 170.75 168 167 157.75 160 176.75 176 177 179.75 165.25 192.5 184.25 224.5 188.75 162.5 156.5 197 198.5 173.75 172.75 196.75 177 165.5 200.25 203.25 194 168.5 170.75 183.25 178.25 163 175.25 158 177.25 179 191 187.5 206.5 185.25 160.25 151.5 161 167 177.5 152.25 192.25 165.25 171.75 171.25 197 157 168.25 186 166.75 187.75 168.25 212.75 176.75 173.25 167 159.75 188.15 156 208.5 206.5 143.75 223 152.25 241.75 146 156.75 200.25 171.5 205.75 182.5 136.5 177.25 151.25 196 184.25 140 218.75 217 166.25 224.75 228.25 172.75 152.25 125.75 177.25 176.25 226.75 145.25 151 241.25 187.25 234.75 219.25 118.5 145.75 159.25 170.5 167.5 232.75 210.5 202.25 185 153 244.25 193.5 224.75 162.75 180 156.25 168 167.25 170.75 178.25 150 200.5 184 223 208.75 166 195 160.5 159.75 140.5 216.25 168.25 194.75 172.75 219 149.25 154.5 199.25 154.5 153.25 230 161.75 142.25 179.75 126.5 169.5 198.5 174.5 167.75 147.75 182.25 175.5 161.75 157.75 168.75 191.5 219.15 155.25 189.75 127.5 224.5 234.25 227.75 199.5 155.5 215.5 134.25 201 186.75 190.75 207.5
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R Code
x <-sort(x[!is.na(x)]) q1 <- function(data,n,p,i,f) { np <- n*p; i <<- floor(np) f <<- np - i qvalue <- (1-f)*data[i] + f*data[i+1] } q2 <- function(data,n,p,i,f) { np <- (n+1)*p i <<- floor(np) f <<- np - i qvalue <- (1-f)*data[i] + f*data[i+1] } q3 <- function(data,n,p,i,f) { np <- n*p i <<- floor(np) f <<- np - i if (f==0) { qvalue <- data[i] } else { qvalue <- data[i+1] } } q4 <- function(data,n,p,i,f) { np <- n*p i <<- floor(np) f <<- np - i if (f==0) { qvalue <- (data[i]+data[i+1])/2 } else { qvalue <- data[i+1] } } q5 <- function(data,n,p,i,f) { np <- (n-1)*p i <<- floor(np) f <<- np - i if (f==0) { qvalue <- data[i+1] } else { qvalue <- data[i+1] + f*(data[i+2]-data[i+1]) } } q6 <- function(data,n,p,i,f) { np <- n*p+0.5 i <<- floor(np) f <<- np - i qvalue <- data[i] } q7 <- function(data,n,p,i,f) { np <- (n+1)*p i <<- floor(np) f <<- np - i if (f==0) { qvalue <- data[i] } else { qvalue <- f*data[i] + (1-f)*data[i+1] } } q8 <- function(data,n,p,i,f) { np <- (n+1)*p i <<- floor(np) f <<- np - i if (f==0) { qvalue <- data[i] } else { if (f == 0.5) { qvalue <- (data[i]+data[i+1])/2 } else { if (f < 0.5) { qvalue <- data[i] } else { qvalue <- data[i+1] } } } } lx <- length(x) qval <- array(NA,dim=c(99,8)) mystep <- 25 mystart <- 25 if (lx>10){ mystep=10 mystart=10 } if (lx>20){ mystep=5 mystart=5 } if (lx>50){ mystep=2 mystart=2 } if (lx>=100){ mystep=1 mystart=1 } for (perc in seq(mystart,99,mystep)) { qval[perc,1] <- q1(x,lx,perc/100,i,f) qval[perc,2] <- q2(x,lx,perc/100,i,f) qval[perc,3] <- q3(x,lx,perc/100,i,f) qval[perc,4] <- q4(x,lx,perc/100,i,f) qval[perc,5] <- q5(x,lx,perc/100,i,f) qval[perc,6] <- q6(x,lx,perc/100,i,f) qval[perc,7] <- q7(x,lx,perc/100,i,f) qval[perc,8] <- q8(x,lx,perc/100,i,f) } bitmap(file='test1.png') myqqnorm <- qqnorm(x,col=2) qqline(x) grid() dev.off() load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Percentiles - Ungrouped Data',9,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'p',1,TRUE) a<-table.element(a, 'Weighted Average at Xnp',1,TRUE) a<-table.element(a, 'Weighted Average at X(n+1)p',1,TRUE) a<-table.element(a, 'Empirical Distribution Function',1,TRUE) a<-table.element(a, 'Empirical Distribution Function - Averaging',1,TRUE) a<-table.element(a, 'Empirical Distribution Function - Interpolation',1,TRUE) a<-table.element(a, 'Closest Observation',1,TRUE) a<-table.element(a, 'True Basic - Statistics Graphics Toolkit',1,TRUE) a<-table.element(a, 'MS Excel (old versions)',1,TRUE) a<-table.row.end(a) for (perc in seq(mystart,99,mystep)) { a<-table.row.start(a) a<-table.element(a,round(perc/100,2),1,TRUE) for (j in 1:8) { a<-table.element(a,signif(qval[perc,j],6)) } a<-table.row.end(a) } a<-table.end(a) table.save(a,file='mytable.tab')
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