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Data:
24.90 25.06 25.10 24.92 25.46 25.89 25.39 25.38 25.25 24.88 25.00 25.00 24.07 23.60 23.18 23.25 23.04 22.77 22.25 22.41 22.50 22.91 22.88 21.69 21.19 21.56 22.00 22.13 22.27 22.30 21.94 22.40 22.77 22.90 23.03 23.05 22.41 22.26 21.90 22.01 22.62 22.76 23.40 23.63 24.05 23.82 23.71 23.95 23.61 23.98 23.56 23.99 24.33 24.48 24.31 24.38 24.63 25.54 25.75 25.73 25.85 25.78 25.86 26.86 27.36 27.38 26.58 27.65 27.73 27.18 27.32 27.30 26.90 26.70 26.75 26.41 26.29 27.51 27.91 27.70 27.28 28.25 27.62 27.30 25.94 24.99 25.50 24.42 26.58 25.84 26.76 26.74 26.68 25.55 26.40 25.19 23.94 24.20 24.20 23.07 24.07 25.02 24.65 24.68 24.63 24.49 25.05 24.31 23.90 23.68 24.50 25.22 25.48 26.00 26.07 26.06 26.22 26.70 27.20 26.77 26.11 25.43 24.99 25.51 24.00 23.86 22.96 23.41 23.17 24.12 23.87 24.27 24.40 24.16 25.15 25.09 24.60 24.33 24.14 24.36 25.40 26.15 26.77 26.94 26.33 26.24 26.23 25.88 27.00 26.91 27.15 27.78 28.73 28.83 28.68 27.56 27.15 27.41 27.47 28.76 28.47 27.94 27.23 27.01 26.15 26.11 27.20 27.36 27.33 27.43 28.92 29.45 29.01 29.25 29.14 29.64 30.40 30.62 31.25 31.75 31.30 30.70 31.03 31.46 31.28 31.03 30.95 31.17 31.29 31.91 32.10 31.71 31.90 32.02 32.65 33.77 33.51 34.26 34.21 34.13 34.73 34.73 34.57 34.80 33.98 34.40 34.21 34.61 35.25 35.23 35.00 34.52 33.82 34.35 34.81 34.96 36.69 36.42 36.44 37.41 36.40 36.15 35.78 36.95 36.14 36.36 37.31 37.58 38.00 37.23 37.00 37.87 37.70 36.17 36.56 37.70 38.77 39.02 39.88 39.56 38.52 37.20 38.58 39.41 39.08 38.81 38.73 38.70 39.23 39.82 39.97 40.37 39.54 39.21 39.07 39.78 39.40 38.92
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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,hyperlink('http://www.xycoon.com/method_1.htm', 'Weighted Average at Xnp',''),1,TRUE) a<-table.element(a,hyperlink('http://www.xycoon.com/method_2.htm','Weighted Average at X(n+1)p',''),1,TRUE) a<-table.element(a,hyperlink('http://www.xycoon.com/method_3.htm','Empirical Distribution Function',''),1,TRUE) a<-table.element(a,hyperlink('http://www.xycoon.com/method_4.htm','Empirical Distribution Function - Averaging',''),1,TRUE) a<-table.element(a,hyperlink('http://www.xycoon.com/method_5.htm','Empirical Distribution Function - Interpolation',''),1,TRUE) a<-table.element(a,hyperlink('http://www.xycoon.com/method_6.htm','Closest Observation',''),1,TRUE) a<-table.element(a,hyperlink('http://www.xycoon.com/method_7.htm','True Basic - Statistics Graphics Toolkit',''),1,TRUE) a<-table.element(a,hyperlink('http://www.xycoon.com/method_8.htm','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,round(qval[perc,j],6)) } a<-table.row.end(a) } a<-table.end(a) table.save(a,file='mytable.tab')
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