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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 computationSat, 07 Dec 2013 05:36:42 -0500
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/Dec/07/t1386412629buaqpfjq7unanp0.htm/, Retrieved Fri, 19 Apr 2024 15:48:34 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=231366, Retrieved Fri, 19 Apr 2024 15:48:34 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact98
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Percentiles] [] [2013-12-07 10:36:42] [02b53344bfc7e15f5310bf5039e578c4] [Current]
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Dataseries X:
185
188
175
190
198
185
196
183
185
188
196
188
183
208
183
178
178
180
183
203
203
178
190
190
190
196
183
188
185
188
193
193
183
188
185
180
198
190
185
190
183
185
190
185
188
198
196
180
185
190




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 seconds
R Server'Herman Ole Andreas Wold' @ wold.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 & 4 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231366&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]4 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231366&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231366&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 time4 seconds
R Server'Herman Ole Andreas Wold' @ wold.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)
0.05178178178178178178178178
0.1180180180180180180180180
0.15181.5181.95183183183183181.05183
0.2183183183183183183183183
0.25183183183183183183183183
0.3185185185185185185185185
0.35185185185185185185185185
0.4185185185185185185185185
0.45185185185185185.15185185185
0.5188188188188188188188188
0.55188188188188188188188188
0.6188189.2188189188.8188188.8190
0.65190190190190190190190190
0.7190190190190190190190190
0.75190190.75190190190190192.25190
0.8193195.4193194.5193.6193193.6196
0.85196196196196196196196196
0.9198198198198198198198198
0.95200.5203203203200.75203203203

\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 & 178 & 178 & 178 & 178 & 178 & 178 & 178 & 178 \tabularnewline
0.1 & 180 & 180 & 180 & 180 & 180 & 180 & 180 & 180 \tabularnewline
0.15 & 181.5 & 181.95 & 183 & 183 & 183 & 183 & 181.05 & 183 \tabularnewline
0.2 & 183 & 183 & 183 & 183 & 183 & 183 & 183 & 183 \tabularnewline
0.25 & 183 & 183 & 183 & 183 & 183 & 183 & 183 & 183 \tabularnewline
0.3 & 185 & 185 & 185 & 185 & 185 & 185 & 185 & 185 \tabularnewline
0.35 & 185 & 185 & 185 & 185 & 185 & 185 & 185 & 185 \tabularnewline
0.4 & 185 & 185 & 185 & 185 & 185 & 185 & 185 & 185 \tabularnewline
0.45 & 185 & 185 & 185 & 185 & 185.15 & 185 & 185 & 185 \tabularnewline
0.5 & 188 & 188 & 188 & 188 & 188 & 188 & 188 & 188 \tabularnewline
0.55 & 188 & 188 & 188 & 188 & 188 & 188 & 188 & 188 \tabularnewline
0.6 & 188 & 189.2 & 188 & 189 & 188.8 & 188 & 188.8 & 190 \tabularnewline
0.65 & 190 & 190 & 190 & 190 & 190 & 190 & 190 & 190 \tabularnewline
0.7 & 190 & 190 & 190 & 190 & 190 & 190 & 190 & 190 \tabularnewline
0.75 & 190 & 190.75 & 190 & 190 & 190 & 190 & 192.25 & 190 \tabularnewline
0.8 & 193 & 195.4 & 193 & 194.5 & 193.6 & 193 & 193.6 & 196 \tabularnewline
0.85 & 196 & 196 & 196 & 196 & 196 & 196 & 196 & 196 \tabularnewline
0.9 & 198 & 198 & 198 & 198 & 198 & 198 & 198 & 198 \tabularnewline
0.95 & 200.5 & 203 & 203 & 203 & 200.75 & 203 & 203 & 203 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231366&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]178[/C][C]178[/C][C]178[/C][C]178[/C][C]178[/C][C]178[/C][C]178[/C][C]178[/C][/ROW]
[ROW][C]0.1[/C][C]180[/C][C]180[/C][C]180[/C][C]180[/C][C]180[/C][C]180[/C][C]180[/C][C]180[/C][/ROW]
[ROW][C]0.15[/C][C]181.5[/C][C]181.95[/C][C]183[/C][C]183[/C][C]183[/C][C]183[/C][C]181.05[/C][C]183[/C][/ROW]
[ROW][C]0.2[/C][C]183[/C][C]183[/C][C]183[/C][C]183[/C][C]183[/C][C]183[/C][C]183[/C][C]183[/C][/ROW]
[ROW][C]0.25[/C][C]183[/C][C]183[/C][C]183[/C][C]183[/C][C]183[/C][C]183[/C][C]183[/C][C]183[/C][/ROW]
[ROW][C]0.3[/C][C]185[/C][C]185[/C][C]185[/C][C]185[/C][C]185[/C][C]185[/C][C]185[/C][C]185[/C][/ROW]
[ROW][C]0.35[/C][C]185[/C][C]185[/C][C]185[/C][C]185[/C][C]185[/C][C]185[/C][C]185[/C][C]185[/C][/ROW]
[ROW][C]0.4[/C][C]185[/C][C]185[/C][C]185[/C][C]185[/C][C]185[/C][C]185[/C][C]185[/C][C]185[/C][/ROW]
[ROW][C]0.45[/C][C]185[/C][C]185[/C][C]185[/C][C]185[/C][C]185.15[/C][C]185[/C][C]185[/C][C]185[/C][/ROW]
[ROW][C]0.5[/C][C]188[/C][C]188[/C][C]188[/C][C]188[/C][C]188[/C][C]188[/C][C]188[/C][C]188[/C][/ROW]
[ROW][C]0.55[/C][C]188[/C][C]188[/C][C]188[/C][C]188[/C][C]188[/C][C]188[/C][C]188[/C][C]188[/C][/ROW]
[ROW][C]0.6[/C][C]188[/C][C]189.2[/C][C]188[/C][C]189[/C][C]188.8[/C][C]188[/C][C]188.8[/C][C]190[/C][/ROW]
[ROW][C]0.65[/C][C]190[/C][C]190[/C][C]190[/C][C]190[/C][C]190[/C][C]190[/C][C]190[/C][C]190[/C][/ROW]
[ROW][C]0.7[/C][C]190[/C][C]190[/C][C]190[/C][C]190[/C][C]190[/C][C]190[/C][C]190[/C][C]190[/C][/ROW]
[ROW][C]0.75[/C][C]190[/C][C]190.75[/C][C]190[/C][C]190[/C][C]190[/C][C]190[/C][C]192.25[/C][C]190[/C][/ROW]
[ROW][C]0.8[/C][C]193[/C][C]195.4[/C][C]193[/C][C]194.5[/C][C]193.6[/C][C]193[/C][C]193.6[/C][C]196[/C][/ROW]
[ROW][C]0.85[/C][C]196[/C][C]196[/C][C]196[/C][C]196[/C][C]196[/C][C]196[/C][C]196[/C][C]196[/C][/ROW]
[ROW][C]0.9[/C][C]198[/C][C]198[/C][C]198[/C][C]198[/C][C]198[/C][C]198[/C][C]198[/C][C]198[/C][/ROW]
[ROW][C]0.95[/C][C]200.5[/C][C]203[/C][C]203[/C][C]203[/C][C]200.75[/C][C]203[/C][C]203[/C][C]203[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231366&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231366&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)
0.05178178178178178178178178
0.1180180180180180180180180
0.15181.5181.95183183183183181.05183
0.2183183183183183183183183
0.25183183183183183183183183
0.3185185185185185185185185
0.35185185185185185185185185
0.4185185185185185185185185
0.45185185185185185.15185185185
0.5188188188188188188188188
0.55188188188188188188188188
0.6188189.2188189188.8188188.8190
0.65190190190190190190190190
0.7190190190190190190190190
0.75190190.75190190190190192.25190
0.8193195.4193194.5193.6193193.6196
0.85196196196196196196196196
0.9198198198198198198198198
0.95200.5203203203200.75203203203



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')