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Author's title

Author*Unverified author*
R Software Modulerwasp_percentiles.wasp
Title produced by softwarePercentiles
Date of computationSat, 15 Feb 2020 16:27:06 +0100
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2020/Feb/15/t15817805099852au5qtk8j0se.htm/, Retrieved Fri, 07 May 2021 10:39:24 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=319076, Retrieved Fri, 07 May 2021 10:39:24 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact44
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Percentiles] [economic dynamism] [2020-02-15 15:27:06] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataseries X:
25.8057
41.1648
49.1361
50.9866
37.4511
38.0793
61.9281
59.1724
51.915
37.7251
41.9543
39.6282
43.6952
39.6553
44.9346
33.6074
47.8506
42.0265
46.0521
21.6643
43.7178
48.6159
48.3652
58.0767
43.8555
43.6252




Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time0 seconds
R ServerBig Analytics Cloud Computing Center

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input view raw input (R code)  \tabularnewline
Raw Outputview raw output of R engine  \tabularnewline
Computing time0 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=319076&T=0

[TABLE]
[ROW]
Summary of computational transaction[/C][/ROW] [ROW]Raw Input[/C] view raw input (R code) [/C][/ROW] [ROW]Raw Output[/C]view raw output of R engine [/C][/ROW] [ROW]Computing time[/C]0 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=319076&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=319076&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 Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time0 seconds
R ServerBig Analytics Cloud Computing Center







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)
0.0522.906723.113825.805725.805727.756121.664324.356221.6643
0.130.486731.266933.607433.607435.529233.607428.146233.6074
0.1537.066737.464837.451137.451137.656637.451137.711437.4511
0.237.795937.866838.079338.079338.079337.725137.937637.7251
0.2538.853839.24139.628239.628239.63539.628238.466539.6282
0.339.649939.806239.655339.655340.4139.655341.013839.6553
0.3541.243841.520141.954341.954341.756941.164841.59941.1648
0.441.983242.012142.026542.026542.026541.954341.968742.0265
0.4543.145643.635743.625243.625243.642743.625243.684743.6252
0.543.695243.706543.695243.706543.706543.695243.706543.7065
0.5543.759143.834843.855543.855543.821143.717843.738543.8555
0.644.50345.158144.934644.934644.934644.934645.828644.9346
0.6545.940447.041346.052146.052146.501746.052146.861447.8506
0.747.953548.313748.365248.365248.107947.850647.902148.3652
0.7548.490648.74648.615948.615948.553248.615949.00648.6159
0.849.032150.246449.136149.136149.136149.136149.876350.9866
0.8551.079451.868651.91551.91551.218750.986651.03351.915
0.954.379758.405458.076758.076754.995851.91558.843758.0767
0.9558.843760.963659.172459.172458.898559.172460.136961.9281

\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 & 22.9067 & 23.1138 & 25.8057 & 25.8057 & 27.7561 & 21.6643 & 24.3562 & 21.6643 \tabularnewline
0.1 & 30.4867 & 31.2669 & 33.6074 & 33.6074 & 35.5292 & 33.6074 & 28.1462 & 33.6074 \tabularnewline
0.15 & 37.0667 & 37.4648 & 37.4511 & 37.4511 & 37.6566 & 37.4511 & 37.7114 & 37.4511 \tabularnewline
0.2 & 37.7959 & 37.8668 & 38.0793 & 38.0793 & 38.0793 & 37.7251 & 37.9376 & 37.7251 \tabularnewline
0.25 & 38.8538 & 39.241 & 39.6282 & 39.6282 & 39.635 & 39.6282 & 38.4665 & 39.6282 \tabularnewline
0.3 & 39.6499 & 39.8062 & 39.6553 & 39.6553 & 40.41 & 39.6553 & 41.0138 & 39.6553 \tabularnewline
0.35 & 41.2438 & 41.5201 & 41.9543 & 41.9543 & 41.7569 & 41.1648 & 41.599 & 41.1648 \tabularnewline
0.4 & 41.9832 & 42.0121 & 42.0265 & 42.0265 & 42.0265 & 41.9543 & 41.9687 & 42.0265 \tabularnewline
0.45 & 43.1456 & 43.6357 & 43.6252 & 43.6252 & 43.6427 & 43.6252 & 43.6847 & 43.6252 \tabularnewline
0.5 & 43.6952 & 43.7065 & 43.6952 & 43.7065 & 43.7065 & 43.6952 & 43.7065 & 43.7065 \tabularnewline
0.55 & 43.7591 & 43.8348 & 43.8555 & 43.8555 & 43.8211 & 43.7178 & 43.7385 & 43.8555 \tabularnewline
0.6 & 44.503 & 45.1581 & 44.9346 & 44.9346 & 44.9346 & 44.9346 & 45.8286 & 44.9346 \tabularnewline
0.65 & 45.9404 & 47.0413 & 46.0521 & 46.0521 & 46.5017 & 46.0521 & 46.8614 & 47.8506 \tabularnewline
0.7 & 47.9535 & 48.3137 & 48.3652 & 48.3652 & 48.1079 & 47.8506 & 47.9021 & 48.3652 \tabularnewline
0.75 & 48.4906 & 48.746 & 48.6159 & 48.6159 & 48.5532 & 48.6159 & 49.006 & 48.6159 \tabularnewline
0.8 & 49.0321 & 50.2464 & 49.1361 & 49.1361 & 49.1361 & 49.1361 & 49.8763 & 50.9866 \tabularnewline
0.85 & 51.0794 & 51.8686 & 51.915 & 51.915 & 51.2187 & 50.9866 & 51.033 & 51.915 \tabularnewline
0.9 & 54.3797 & 58.4054 & 58.0767 & 58.0767 & 54.9958 & 51.915 & 58.8437 & 58.0767 \tabularnewline
0.95 & 58.8437 & 60.9636 & 59.1724 & 59.1724 & 58.8985 & 59.1724 & 60.1369 & 61.9281 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=319076&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]22.9067[/C][C]23.1138[/C][C]25.8057[/C][C]25.8057[/C][C]27.7561[/C][C]21.6643[/C][C]24.3562[/C][C]21.6643[/C][/ROW]
[ROW][C]0.1[/C][C]30.4867[/C][C]31.2669[/C][C]33.6074[/C][C]33.6074[/C][C]35.5292[/C][C]33.6074[/C][C]28.1462[/C][C]33.6074[/C][/ROW]
[ROW][C]0.15[/C][C]37.0667[/C][C]37.4648[/C][C]37.4511[/C][C]37.4511[/C][C]37.6566[/C][C]37.4511[/C][C]37.7114[/C][C]37.4511[/C][/ROW]
[ROW][C]0.2[/C][C]37.7959[/C][C]37.8668[/C][C]38.0793[/C][C]38.0793[/C][C]38.0793[/C][C]37.7251[/C][C]37.9376[/C][C]37.7251[/C][/ROW]
[ROW][C]0.25[/C][C]38.8538[/C][C]39.241[/C][C]39.6282[/C][C]39.6282[/C][C]39.635[/C][C]39.6282[/C][C]38.4665[/C][C]39.6282[/C][/ROW]
[ROW][C]0.3[/C][C]39.6499[/C][C]39.8062[/C][C]39.6553[/C][C]39.6553[/C][C]40.41[/C][C]39.6553[/C][C]41.0138[/C][C]39.6553[/C][/ROW]
[ROW][C]0.35[/C][C]41.2438[/C][C]41.5201[/C][C]41.9543[/C][C]41.9543[/C][C]41.7569[/C][C]41.1648[/C][C]41.599[/C][C]41.1648[/C][/ROW]
[ROW][C]0.4[/C][C]41.9832[/C][C]42.0121[/C][C]42.0265[/C][C]42.0265[/C][C]42.0265[/C][C]41.9543[/C][C]41.9687[/C][C]42.0265[/C][/ROW]
[ROW][C]0.45[/C][C]43.1456[/C][C]43.6357[/C][C]43.6252[/C][C]43.6252[/C][C]43.6427[/C][C]43.6252[/C][C]43.6847[/C][C]43.6252[/C][/ROW]
[ROW][C]0.5[/C][C]43.6952[/C][C]43.7065[/C][C]43.6952[/C][C]43.7065[/C][C]43.7065[/C][C]43.6952[/C][C]43.7065[/C][C]43.7065[/C][/ROW]
[ROW][C]0.55[/C][C]43.7591[/C][C]43.8348[/C][C]43.8555[/C][C]43.8555[/C][C]43.8211[/C][C]43.7178[/C][C]43.7385[/C][C]43.8555[/C][/ROW]
[ROW][C]0.6[/C][C]44.503[/C][C]45.1581[/C][C]44.9346[/C][C]44.9346[/C][C]44.9346[/C][C]44.9346[/C][C]45.8286[/C][C]44.9346[/C][/ROW]
[ROW][C]0.65[/C][C]45.9404[/C][C]47.0413[/C][C]46.0521[/C][C]46.0521[/C][C]46.5017[/C][C]46.0521[/C][C]46.8614[/C][C]47.8506[/C][/ROW]
[ROW][C]0.7[/C][C]47.9535[/C][C]48.3137[/C][C]48.3652[/C][C]48.3652[/C][C]48.1079[/C][C]47.8506[/C][C]47.9021[/C][C]48.3652[/C][/ROW]
[ROW][C]0.75[/C][C]48.4906[/C][C]48.746[/C][C]48.6159[/C][C]48.6159[/C][C]48.5532[/C][C]48.6159[/C][C]49.006[/C][C]48.6159[/C][/ROW]
[ROW][C]0.8[/C][C]49.0321[/C][C]50.2464[/C][C]49.1361[/C][C]49.1361[/C][C]49.1361[/C][C]49.1361[/C][C]49.8763[/C][C]50.9866[/C][/ROW]
[ROW][C]0.85[/C][C]51.0794[/C][C]51.8686[/C][C]51.915[/C][C]51.915[/C][C]51.2187[/C][C]50.9866[/C][C]51.033[/C][C]51.915[/C][/ROW]
[ROW][C]0.9[/C][C]54.3797[/C][C]58.4054[/C][C]58.0767[/C][C]58.0767[/C][C]54.9958[/C][C]51.915[/C][C]58.8437[/C][C]58.0767[/C][/ROW]
[ROW][C]0.95[/C][C]58.8437[/C][C]60.9636[/C][C]59.1724[/C][C]59.1724[/C][C]58.8985[/C][C]59.1724[/C][C]60.1369[/C][C]61.9281[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=319076&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=319076&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)
0.0522.906723.113825.805725.805727.756121.664324.356221.6643
0.130.486731.266933.607433.607435.529233.607428.146233.6074
0.1537.066737.464837.451137.451137.656637.451137.711437.4511
0.237.795937.866838.079338.079338.079337.725137.937637.7251
0.2538.853839.24139.628239.628239.63539.628238.466539.6282
0.339.649939.806239.655339.655340.4139.655341.013839.6553
0.3541.243841.520141.954341.954341.756941.164841.59941.1648
0.441.983242.012142.026542.026542.026541.954341.968742.0265
0.4543.145643.635743.625243.625243.642743.625243.684743.6252
0.543.695243.706543.695243.706543.706543.695243.706543.7065
0.5543.759143.834843.855543.855543.821143.717843.738543.8555
0.644.50345.158144.934644.934644.934644.934645.828644.9346
0.6545.940447.041346.052146.052146.501746.052146.861447.8506
0.747.953548.313748.365248.365248.107947.850647.902148.3652
0.7548.490648.74648.615948.615948.553248.615949.00648.6159
0.849.032150.246449.136149.136149.136149.136149.876350.9866
0.8551.079451.868651.91551.91551.218750.986651.03351.915
0.954.379758.405458.076758.076754.995851.91558.843758.0767
0.9558.843760.963659.172459.172458.898559.172460.136961.9281



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, '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')