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R Software Module: rwasp_percentiles.wasp (opens new window with default values)
Title produced by software: Percentiles
Date of computation: Fri, 02 Nov 2007 05:20:27 -0700
 
Cite this page as follows:
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2007/Nov/02/mv2o6sb9vr44f0w1194005999.htm/, Retrieved Fri, 02 Nov 2007 13:21:59 +0100
 
User-defined keywords:
 
Dataseries X:
» Textbox « » Textfile « » CSV «
112 118 132 129 121 135 148 148 136 119 104 118 115 126 141 135 125 149 170 170 158 133 114 140 145 150 178 163 172 178 199 199 184 162 146 166 171 180 193 181 183 218 230 242 209 191 172 194 196 196 236 235 229 243 264 272 237 211 180 201 204 188 235 227 234 264 302 293 259 229 203 229 242 233 267 269 270 315 364 347 312 274 237 278 284 277 317 313 318 374 413 405 355 306 271 306 315 301 356 348 355 422 465 467 404 347 305 336 340 318 362 348 363 435 491 505 404 359 310 337 360 342 406 396 420 472 548 559 463 407 362 405 417 391 419 461 472 535 622 606 508 461 390 432
 
Text written by user:
betatest
 
Output produced by software:


Summary of compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time7 seconds
R Server193.190.124.21 @ 193.190.124.21


Percentiles - Ungrouped Data
pWeighted Average at XnpWeighted Average at X(n+1)pEmpirical Distribution FunctionEmpirical Distribution Function - AveragingEmpirical Distribution Function - InterpolationClosest ObservationTrue Basic - Statistics Graphics ToolkitMS Excel (old versions)
0.01107.52107.6112112112.86104108.4104
0.02113.76113.8114114114.86114112.2114
0.03115.96116.05118118118115116.95115
0.04118118118118118.72118118118
0.05119.4119.5121121121.6119120.5119
0.06123.56123.8125125125.58125122.2125
0.07126.24126.45129129129.03126128.55126
0.08130.56130.8132132132.44132130.2132
0.09132.96133.1133133134.74133134.9133
0.1135135135135135.3135135135
0.11135.84135.95136136138.92136135.05136
0.12140.28140.4141141141.64140140.6140
0.13143.88144.4145145145.59145141.6145
0.14146.32146.6148148148146147.4146
0.15148148148148148.45148148148
0.16149.04149.2150150149.88149149.8149
0.17153.84155.2158158159.24150152.8158
0.18161.68162.1162162162.74162162.9162
0.19164.08164.65166166166.68163164.35166
0.2169.2170170170170170170170
0.21170.24170.45171171171.03170170.55170
0.22171.68171.9172172172172171.1172
0.23172.72174.1178178177.34172175.9172
0.24178178178178178.64178178178
0.25180180180180180180180180
0.26180.44180.7181181181.36180180.3181
0.27182.76183.15183183183.61183183.85183
0.28185.28186.4188188188.12184185.6188
0.29190.28191.1191191191.94191192.9191
0.3193.2193.5194194193.9193193.5193.5
0.31195.28195.9196196196196194.1196
0.32196.24197.2199199198.28196197.8196
0.33199199199199199.38199199199
0.34200.92201.6201201202.24201202.4201
0.35203.4203.75204204204.25203203.25204
0.36208.2209.4209209209.96209210.6209
0.37212.96215.55218218217.37211213.45218
0.38224.48227.2227227227.68227228.8227
0.39229229229229229229229229
0.4229229229229229.2229229229
0.41230.12231.35233233231.89230231.65230
0.42233.48233.9234234234.06233233.1234
0.43234.92235235235235235235235
0.44235.36235.8236236235.92235235.2236
0.45236.8237237237237237237237
0.46238.2240.5242242240.9237238.5242
0.47242242.15242242242.21242242.85242
0.48244.92252.6259259253.24243249.4259
0.49261.8264264264264264264264
0.5264265.5264265.5265.5264265.5265.5
0.51267.88268.9269269268.86267267.1269
0.52269.88270.4270270270.36270270.6270
0.53271.32271.85272272271.79271271.15272
0.54273.52274.9274274274.66274276.1274
0.55277.2277.75278278277.65277277.25278
0.56281.84285.8284284284.72284291.2284
0.57293.64298.2301301297.08293295.8301
0.58301.52302.3302302301.94302304.7302
0.59304.88305.55305305305.37305305.45306
0.6306306306306306306306306
0.61309.36310.9310310310.46310311.1310
0.62312.28312.9313313312.66312312.1313
0.63314.44315315315315315315315
0.64315.32316.6317317316.04315315.4317
0.65317.6318318318317.95318318318
0.66318.72330.6336336324.84318323.4336
0.67336.48337.45337337336.81336339.55337
0.68339.76341.2340340340.48340340.8342
0.69343.8347347347345.35342347347
0.7347347.5347347347.1347347.5347.5
0.71348348348348348348348348
0.72352.76355355355354.72355355355
0.73355.12355.85356356355.39355355.15356
0.74357.68359.3359359358.46359359.7359
0.75360361.5360361360.5360360.5362
0.76362362.2362362362362362.8362
0.77362.88363.65363363363.11363363.35364
0.78367.2375.6374374369.4364388.4374
0.79386.16390.55390390389.52390390.45391
0.8392396396396393391396396
0.81401.12404404404402.64404404404
0.82404.08404.9405405404.26404404.1405
0.83405405.35405405405405405.65405
0.84405.96406.8406406406.12406406.2407
0.85409.4414413413410.3407416413
0.86416.36418.4417417416.92417417.6419
0.87419.28420.3420420419.41419421.7420
0.88421.44428422422421.68422426432
0.89432.48436.3435435432.81432459.7435
0.9450.6461461461453.2461461461
0.91461.08462.9463463461.26461461.1463
0.92463.96465.8465465464.12463466.2465
0.93466.84471.25467467466.98467467.75472
0.94472477.7472472472472485.3472
0.95487.2501.5491491488.15491494.5505
0.96505.72513.4508508505.84505529.6508
0.97526.36543.45535535527.17535539.55548
0.98549.32563.7559559549.54548601.3559
0.99585.32614.8606606585.79606613.2622
 
Charts produced by software:
 
Parameters:
 
R code (references can be found in the software module):
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)
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')
-SERVER-193.190.124.21
 





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