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Author's title

Author*Unverified author*
R Software Modulerwasp_percentiles.wasp
Title produced by softwarePercentiles
Date of computationMon, 16 May 2016 17:13:25 +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/2016/May/16/t146341525929lln45rlf0c76y.htm/, Retrieved Mon, 06 May 2024 00:24:03 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=295384, Retrieved Mon, 06 May 2024 00:24:03 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact144
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Percentiles] [Mississippi Valle...] [2016-05-16 16:13:25] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataseries X:
13
14
16
20
24
24
24
27
29
34
34
41
45
52
59




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Sir Maurice George Kendall' @ kendall.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 & 1 seconds \tabularnewline
R Server & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=295384&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]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=295384&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=295384&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 time1 seconds
R Server'Sir Maurice George Kendall' @ kendall.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)
0.113.513.6141414.81413.414
0.21616.8161819.21619.216
0.32223.22424242420.824
0.42424242424242424
0.525.527272727272727
0.629322931.531293134
0.73435.43434343439.634
0.84144.2414341.84141.845
0.948.554.8525249.25256.252

\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
0.1 & 13.5 & 13.6 & 14 & 14 & 14.8 & 14 & 13.4 & 14 \tabularnewline
0.2 & 16 & 16.8 & 16 & 18 & 19.2 & 16 & 19.2 & 16 \tabularnewline
0.3 & 22 & 23.2 & 24 & 24 & 24 & 24 & 20.8 & 24 \tabularnewline
0.4 & 24 & 24 & 24 & 24 & 24 & 24 & 24 & 24 \tabularnewline
0.5 & 25.5 & 27 & 27 & 27 & 27 & 27 & 27 & 27 \tabularnewline
0.6 & 29 & 32 & 29 & 31.5 & 31 & 29 & 31 & 34 \tabularnewline
0.7 & 34 & 35.4 & 34 & 34 & 34 & 34 & 39.6 & 34 \tabularnewline
0.8 & 41 & 44.2 & 41 & 43 & 41.8 & 41 & 41.8 & 45 \tabularnewline
0.9 & 48.5 & 54.8 & 52 & 52 & 49.2 & 52 & 56.2 & 52 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=295384&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]0.1[/C][C]13.5[/C][C]13.6[/C][C]14[/C][C]14[/C][C]14.8[/C][C]14[/C][C]13.4[/C][C]14[/C][/ROW]
[ROW][C]0.2[/C][C]16[/C][C]16.8[/C][C]16[/C][C]18[/C][C]19.2[/C][C]16[/C][C]19.2[/C][C]16[/C][/ROW]
[ROW][C]0.3[/C][C]22[/C][C]23.2[/C][C]24[/C][C]24[/C][C]24[/C][C]24[/C][C]20.8[/C][C]24[/C][/ROW]
[ROW][C]0.4[/C][C]24[/C][C]24[/C][C]24[/C][C]24[/C][C]24[/C][C]24[/C][C]24[/C][C]24[/C][/ROW]
[ROW][C]0.5[/C][C]25.5[/C][C]27[/C][C]27[/C][C]27[/C][C]27[/C][C]27[/C][C]27[/C][C]27[/C][/ROW]
[ROW][C]0.6[/C][C]29[/C][C]32[/C][C]29[/C][C]31.5[/C][C]31[/C][C]29[/C][C]31[/C][C]34[/C][/ROW]
[ROW][C]0.7[/C][C]34[/C][C]35.4[/C][C]34[/C][C]34[/C][C]34[/C][C]34[/C][C]39.6[/C][C]34[/C][/ROW]
[ROW][C]0.8[/C][C]41[/C][C]44.2[/C][C]41[/C][C]43[/C][C]41.8[/C][C]41[/C][C]41.8[/C][C]45[/C][/ROW]
[ROW][C]0.9[/C][C]48.5[/C][C]54.8[/C][C]52[/C][C]52[/C][C]49.2[/C][C]52[/C][C]56.2[/C][C]52[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=295384&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=295384&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)
0.113.513.6141414.81413.414
0.21616.8161819.21619.216
0.32223.22424242420.824
0.42424242424242424
0.525.527272727272727
0.629322931.531293134
0.73435.43434343439.634
0.84144.2414341.84141.845
0.948.554.8525249.25256.252



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')