Free Statistics

of Irreproducible Research!

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_percentiles.wasp
Title produced by softwarePercentiles
Date of computationFri, 22 Jan 2016 08:34:42 +0000
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/Jan/22/t1453451691qn0uotrvlxhssmt.htm/, Retrieved Tue, 07 May 2024 20:00:38 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=290306, Retrieved Tue, 07 May 2024 20:00:38 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact51
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Percentiles] [] [2016-01-22 08:34:42] [faf99fea829628c53c7f48588dc4e154] [Current]
Feedback Forum

Post a new message
Dataseries X:
0.7923
-2.468
-2.996
3.119
0.04315
0.731
2.45
2.119
-1.429
-1.644
-3.065
-1.461
1.141
1.329
0.3396
0.8429
2.225
-1.924
0.4999
-0.6433




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time0 seconds
R Server'Gwilym Jenkins' @ jenkins.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 & 0 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=290306&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]0 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=290306&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=290306&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 time0 seconds
R Server'Gwilym Jenkins' @ jenkins.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)
0.1-2.996-2.9432-2.996-2.732-2.5208-2.996-2.5208-2.996
0.2-1.924-1.868-1.924-1.784-1.7-1.924-1.7-1.924
0.3-1.461-1.4514-1.461-1.445-1.4386-1.461-1.4386-1.461
0.4-0.6433-0.36872-0.6433-0.300075-0.23143-0.6433-0.23143-0.6433
0.50.33960.419750.33960.419750.419750.33960.419750.41975
0.60.7310.767780.7310.761650.755520.7310.755520.7923
0.70.84291.051570.84290.991950.932330.84290.932331.141
0.81.3291.9611.3291.7241.4871.3291.4872.119
0.92.2252.42752.2252.33752.24752.2252.24752.45

\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 & -2.996 & -2.9432 & -2.996 & -2.732 & -2.5208 & -2.996 & -2.5208 & -2.996 \tabularnewline
0.2 & -1.924 & -1.868 & -1.924 & -1.784 & -1.7 & -1.924 & -1.7 & -1.924 \tabularnewline
0.3 & -1.461 & -1.4514 & -1.461 & -1.445 & -1.4386 & -1.461 & -1.4386 & -1.461 \tabularnewline
0.4 & -0.6433 & -0.36872 & -0.6433 & -0.300075 & -0.23143 & -0.6433 & -0.23143 & -0.6433 \tabularnewline
0.5 & 0.3396 & 0.41975 & 0.3396 & 0.41975 & 0.41975 & 0.3396 & 0.41975 & 0.41975 \tabularnewline
0.6 & 0.731 & 0.76778 & 0.731 & 0.76165 & 0.75552 & 0.731 & 0.75552 & 0.7923 \tabularnewline
0.7 & 0.8429 & 1.05157 & 0.8429 & 0.99195 & 0.93233 & 0.8429 & 0.93233 & 1.141 \tabularnewline
0.8 & 1.329 & 1.961 & 1.329 & 1.724 & 1.487 & 1.329 & 1.487 & 2.119 \tabularnewline
0.9 & 2.225 & 2.4275 & 2.225 & 2.3375 & 2.2475 & 2.225 & 2.2475 & 2.45 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=290306&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]-2.996[/C][C]-2.9432[/C][C]-2.996[/C][C]-2.732[/C][C]-2.5208[/C][C]-2.996[/C][C]-2.5208[/C][C]-2.996[/C][/ROW]
[ROW][C]0.2[/C][C]-1.924[/C][C]-1.868[/C][C]-1.924[/C][C]-1.784[/C][C]-1.7[/C][C]-1.924[/C][C]-1.7[/C][C]-1.924[/C][/ROW]
[ROW][C]0.3[/C][C]-1.461[/C][C]-1.4514[/C][C]-1.461[/C][C]-1.445[/C][C]-1.4386[/C][C]-1.461[/C][C]-1.4386[/C][C]-1.461[/C][/ROW]
[ROW][C]0.4[/C][C]-0.6433[/C][C]-0.36872[/C][C]-0.6433[/C][C]-0.300075[/C][C]-0.23143[/C][C]-0.6433[/C][C]-0.23143[/C][C]-0.6433[/C][/ROW]
[ROW][C]0.5[/C][C]0.3396[/C][C]0.41975[/C][C]0.3396[/C][C]0.41975[/C][C]0.41975[/C][C]0.3396[/C][C]0.41975[/C][C]0.41975[/C][/ROW]
[ROW][C]0.6[/C][C]0.731[/C][C]0.76778[/C][C]0.731[/C][C]0.76165[/C][C]0.75552[/C][C]0.731[/C][C]0.75552[/C][C]0.7923[/C][/ROW]
[ROW][C]0.7[/C][C]0.8429[/C][C]1.05157[/C][C]0.8429[/C][C]0.99195[/C][C]0.93233[/C][C]0.8429[/C][C]0.93233[/C][C]1.141[/C][/ROW]
[ROW][C]0.8[/C][C]1.329[/C][C]1.961[/C][C]1.329[/C][C]1.724[/C][C]1.487[/C][C]1.329[/C][C]1.487[/C][C]2.119[/C][/ROW]
[ROW][C]0.9[/C][C]2.225[/C][C]2.4275[/C][C]2.225[/C][C]2.3375[/C][C]2.2475[/C][C]2.225[/C][C]2.2475[/C][C]2.45[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=290306&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=290306&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)
0.1-2.996-2.9432-2.996-2.732-2.5208-2.996-2.5208-2.996
0.2-1.924-1.868-1.924-1.784-1.7-1.924-1.7-1.924
0.3-1.461-1.4514-1.461-1.445-1.4386-1.461-1.4386-1.461
0.4-0.6433-0.36872-0.6433-0.300075-0.23143-0.6433-0.23143-0.6433
0.50.33960.419750.33960.419750.419750.33960.419750.41975
0.60.7310.767780.7310.761650.755520.7310.755520.7923
0.70.84291.051570.84290.991950.932330.84290.932331.141
0.81.3291.9611.3291.7241.4871.3291.4872.119
0.92.2252.42752.2252.33752.24752.2252.24752.45



Parameters (Session):
par1 = 1 ; par2 = 2 ; par4 = TRUE ;
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')