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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_percentiles.wasp
Title produced by softwarePercentiles
Date of computationTue, 08 Oct 2013 03:09:31 -0400
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2013/Oct/08/t1381216226whab8x8vmg4azb3.htm/, Retrieved Mon, 29 Apr 2024 18:56:27 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=213803, Retrieved Mon, 29 Apr 2024 18:56:27 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact96
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Percentiles] [Percentiles] [2013-10-08 07:09:31] [e7e94b653c867545bbece887609dba22] [Current]
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Dataseries X:
191.835
266.793
246.542
330.563
403.556
208.108
324.04
308.532
199.297
200.156
262.875
287.069
190.157
199.746
265.777
435.956
72.844
756.46
206.771
4202.361
401.422
216.046
39.047
441.437




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 2 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=213803&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=213803&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=213803&T=0

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.wessa.net







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)
0.0545.806447.4962572.84472.84490.4409539.04764.3947539.047
0.1119.7692131.5005190.157190.157190.660472.844131.5005131.5005
0.15191.1638191.4155191.835191.835195.1929191.835190.5765191.835
0.2197.8046199.297199.297199.297199.5664199.297199.297199.297
0.25199.746199.8485199.746199.951200.0535199.746200.0535199.746
0.3201.479203.4635206.771206.771206.1095200.156203.4635203.4635
0.35207.3058207.77375208.108208.108208.5049206.771207.10525208.108
0.4212.8708216.046216.046216.046222.1452216.046216.046216.046
0.45240.4428250.62525246.542246.542252.25855246.542258.79175246.542
0.5262.875264.326262.875264.326264.326262.875264.326264.326
0.55265.9802266.539266.793266.793266.4374265.777266.031266.793
0.6274.9034287.069287.069287.069283.0138266.793287.069287.069
0.65299.9468312.409308.532308.532307.45885308.532320.163308.532
0.7320.9384327.3015324.04324.04324.6923324.04327.3015327.3015
0.75330.563383.70725330.563365.9925348.27775330.563348.27775401.422
0.8401.8488403.556403.556403.556402.2756401.422403.556403.556
0.85416.516437.32625435.956435.956421.376403.556440.06675435.956
0.9439.2446598.9485441.437441.437439.7927441.437598.9485598.9485
0.95693.45543340.88575756.46756.46709.20655756.461617.935254202.361

\begin{tabular}{lllllllll}
\hline
Percentiles - Ungrouped Data \tabularnewline
p & Weighted Average at Xnp & Weighted Average at X(n+1)p & Empirical Distribution Function & Empirical Distribution Function - Averaging & Empirical Distribution Function - Interpolation & Closest Observation & True Basic - Statistics Graphics Toolkit & MS Excel (old versions) \tabularnewline
0.05 & 45.8064 & 47.49625 & 72.844 & 72.844 & 90.44095 & 39.047 & 64.39475 & 39.047 \tabularnewline
0.1 & 119.7692 & 131.5005 & 190.157 & 190.157 & 190.6604 & 72.844 & 131.5005 & 131.5005 \tabularnewline
0.15 & 191.1638 & 191.4155 & 191.835 & 191.835 & 195.1929 & 191.835 & 190.5765 & 191.835 \tabularnewline
0.2 & 197.8046 & 199.297 & 199.297 & 199.297 & 199.5664 & 199.297 & 199.297 & 199.297 \tabularnewline
0.25 & 199.746 & 199.8485 & 199.746 & 199.951 & 200.0535 & 199.746 & 200.0535 & 199.746 \tabularnewline
0.3 & 201.479 & 203.4635 & 206.771 & 206.771 & 206.1095 & 200.156 & 203.4635 & 203.4635 \tabularnewline
0.35 & 207.3058 & 207.77375 & 208.108 & 208.108 & 208.5049 & 206.771 & 207.10525 & 208.108 \tabularnewline
0.4 & 212.8708 & 216.046 & 216.046 & 216.046 & 222.1452 & 216.046 & 216.046 & 216.046 \tabularnewline
0.45 & 240.4428 & 250.62525 & 246.542 & 246.542 & 252.25855 & 246.542 & 258.79175 & 246.542 \tabularnewline
0.5 & 262.875 & 264.326 & 262.875 & 264.326 & 264.326 & 262.875 & 264.326 & 264.326 \tabularnewline
0.55 & 265.9802 & 266.539 & 266.793 & 266.793 & 266.4374 & 265.777 & 266.031 & 266.793 \tabularnewline
0.6 & 274.9034 & 287.069 & 287.069 & 287.069 & 283.0138 & 266.793 & 287.069 & 287.069 \tabularnewline
0.65 & 299.9468 & 312.409 & 308.532 & 308.532 & 307.45885 & 308.532 & 320.163 & 308.532 \tabularnewline
0.7 & 320.9384 & 327.3015 & 324.04 & 324.04 & 324.6923 & 324.04 & 327.3015 & 327.3015 \tabularnewline
0.75 & 330.563 & 383.70725 & 330.563 & 365.9925 & 348.27775 & 330.563 & 348.27775 & 401.422 \tabularnewline
0.8 & 401.8488 & 403.556 & 403.556 & 403.556 & 402.2756 & 401.422 & 403.556 & 403.556 \tabularnewline
0.85 & 416.516 & 437.32625 & 435.956 & 435.956 & 421.376 & 403.556 & 440.06675 & 435.956 \tabularnewline
0.9 & 439.2446 & 598.9485 & 441.437 & 441.437 & 439.7927 & 441.437 & 598.9485 & 598.9485 \tabularnewline
0.95 & 693.4554 & 3340.88575 & 756.46 & 756.46 & 709.20655 & 756.46 & 1617.93525 & 4202.361 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=213803&T=1

[TABLE]
[ROW][C]Percentiles - Ungrouped Data[/C][/ROW]
[ROW][C]p[/C][C]Weighted Average at Xnp[/C][C]Weighted Average at X(n+1)p[/C][C]Empirical Distribution Function[/C][C]Empirical Distribution Function - Averaging[/C][C]Empirical Distribution Function - Interpolation[/C][C]Closest Observation[/C][C]True Basic - Statistics Graphics Toolkit[/C][C]MS Excel (old versions)[/C][/ROW]
[ROW][C]0.05[/C][C]45.8064[/C][C]47.49625[/C][C]72.844[/C][C]72.844[/C][C]90.44095[/C][C]39.047[/C][C]64.39475[/C][C]39.047[/C][/ROW]
[ROW][C]0.1[/C][C]119.7692[/C][C]131.5005[/C][C]190.157[/C][C]190.157[/C][C]190.6604[/C][C]72.844[/C][C]131.5005[/C][C]131.5005[/C][/ROW]
[ROW][C]0.15[/C][C]191.1638[/C][C]191.4155[/C][C]191.835[/C][C]191.835[/C][C]195.1929[/C][C]191.835[/C][C]190.5765[/C][C]191.835[/C][/ROW]
[ROW][C]0.2[/C][C]197.8046[/C][C]199.297[/C][C]199.297[/C][C]199.297[/C][C]199.5664[/C][C]199.297[/C][C]199.297[/C][C]199.297[/C][/ROW]
[ROW][C]0.25[/C][C]199.746[/C][C]199.8485[/C][C]199.746[/C][C]199.951[/C][C]200.0535[/C][C]199.746[/C][C]200.0535[/C][C]199.746[/C][/ROW]
[ROW][C]0.3[/C][C]201.479[/C][C]203.4635[/C][C]206.771[/C][C]206.771[/C][C]206.1095[/C][C]200.156[/C][C]203.4635[/C][C]203.4635[/C][/ROW]
[ROW][C]0.35[/C][C]207.3058[/C][C]207.77375[/C][C]208.108[/C][C]208.108[/C][C]208.5049[/C][C]206.771[/C][C]207.10525[/C][C]208.108[/C][/ROW]
[ROW][C]0.4[/C][C]212.8708[/C][C]216.046[/C][C]216.046[/C][C]216.046[/C][C]222.1452[/C][C]216.046[/C][C]216.046[/C][C]216.046[/C][/ROW]
[ROW][C]0.45[/C][C]240.4428[/C][C]250.62525[/C][C]246.542[/C][C]246.542[/C][C]252.25855[/C][C]246.542[/C][C]258.79175[/C][C]246.542[/C][/ROW]
[ROW][C]0.5[/C][C]262.875[/C][C]264.326[/C][C]262.875[/C][C]264.326[/C][C]264.326[/C][C]262.875[/C][C]264.326[/C][C]264.326[/C][/ROW]
[ROW][C]0.55[/C][C]265.9802[/C][C]266.539[/C][C]266.793[/C][C]266.793[/C][C]266.4374[/C][C]265.777[/C][C]266.031[/C][C]266.793[/C][/ROW]
[ROW][C]0.6[/C][C]274.9034[/C][C]287.069[/C][C]287.069[/C][C]287.069[/C][C]283.0138[/C][C]266.793[/C][C]287.069[/C][C]287.069[/C][/ROW]
[ROW][C]0.65[/C][C]299.9468[/C][C]312.409[/C][C]308.532[/C][C]308.532[/C][C]307.45885[/C][C]308.532[/C][C]320.163[/C][C]308.532[/C][/ROW]
[ROW][C]0.7[/C][C]320.9384[/C][C]327.3015[/C][C]324.04[/C][C]324.04[/C][C]324.6923[/C][C]324.04[/C][C]327.3015[/C][C]327.3015[/C][/ROW]
[ROW][C]0.75[/C][C]330.563[/C][C]383.70725[/C][C]330.563[/C][C]365.9925[/C][C]348.27775[/C][C]330.563[/C][C]348.27775[/C][C]401.422[/C][/ROW]
[ROW][C]0.8[/C][C]401.8488[/C][C]403.556[/C][C]403.556[/C][C]403.556[/C][C]402.2756[/C][C]401.422[/C][C]403.556[/C][C]403.556[/C][/ROW]
[ROW][C]0.85[/C][C]416.516[/C][C]437.32625[/C][C]435.956[/C][C]435.956[/C][C]421.376[/C][C]403.556[/C][C]440.06675[/C][C]435.956[/C][/ROW]
[ROW][C]0.9[/C][C]439.2446[/C][C]598.9485[/C][C]441.437[/C][C]441.437[/C][C]439.7927[/C][C]441.437[/C][C]598.9485[/C][C]598.9485[/C][/ROW]
[ROW][C]0.95[/C][C]693.4554[/C][C]3340.88575[/C][C]756.46[/C][C]756.46[/C][C]709.20655[/C][C]756.46[/C][C]1617.93525[/C][C]4202.361[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=213803&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=213803&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

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)
0.0545.806447.4962572.84472.84490.4409539.04764.3947539.047
0.1119.7692131.5005190.157190.157190.660472.844131.5005131.5005
0.15191.1638191.4155191.835191.835195.1929191.835190.5765191.835
0.2197.8046199.297199.297199.297199.5664199.297199.297199.297
0.25199.746199.8485199.746199.951200.0535199.746200.0535199.746
0.3201.479203.4635206.771206.771206.1095200.156203.4635203.4635
0.35207.3058207.77375208.108208.108208.5049206.771207.10525208.108
0.4212.8708216.046216.046216.046222.1452216.046216.046216.046
0.45240.4428250.62525246.542246.542252.25855246.542258.79175246.542
0.5262.875264.326262.875264.326264.326262.875264.326264.326
0.55265.9802266.539266.793266.793266.4374265.777266.031266.793
0.6274.9034287.069287.069287.069283.0138266.793287.069287.069
0.65299.9468312.409308.532308.532307.45885308.532320.163308.532
0.7320.9384327.3015324.04324.04324.6923324.04327.3015327.3015
0.75330.563383.70725330.563365.9925348.27775330.563348.27775401.422
0.8401.8488403.556403.556403.556402.2756401.422403.556403.556
0.85416.516437.32625435.956435.956421.376403.556440.06675435.956
0.9439.2446598.9485441.437441.437439.7927441.437598.9485598.9485
0.95693.45543340.88575756.46756.46709.20655756.461617.935254202.361



Parameters (Session):
Parameters (R input):
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)
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('method_1.htm', 'Weighted Average at Xnp',''),1,TRUE)
a<-table.element(a,hyperlink('method_2.htm','Weighted Average at X(n+1)p',''),1,TRUE)
a<-table.element(a,hyperlink('method_3.htm','Empirical Distribution Function',''),1,TRUE)
a<-table.element(a,hyperlink('method_4.htm','Empirical Distribution Function - Averaging',''),1,TRUE)
a<-table.element(a,hyperlink('method_5.htm','Empirical Distribution Function - Interpolation',''),1,TRUE)
a<-table.element(a,hyperlink('method_6.htm','Closest Observation',''),1,TRUE)
a<-table.element(a,hyperlink('method_7.htm','True Basic - Statistics Graphics Toolkit',''),1,TRUE)
a<-table.element(a,hyperlink('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')