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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 computationSun, 21 Dec 2008 06:04:15 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2008/Dec/21/t1229864696agioega0coafd80.htm/, Retrieved Sun, 19 May 2024 11:28:41 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=35547, Retrieved Sun, 19 May 2024 11:28:41 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact156
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Standard Deviation-Mean Plot] [dollarkoers] [2007-11-29 14:04:00] [707a919fab5d6f3020ea3c395672cd86]
- RMPD    [Percentiles] [] [2008-12-21 13:04:15] [e7fa5259715477c9f32960f5b339b707] [Current]
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Dataseries X:
98,6
98
106,8
96,6
100,1
107,7
91,5
97,8
107,4
117,5
105,6
97,4
99,5
98
104,3
100,6
101,1
103,9
96,9
95,5
108,4
117
103,8
100,8
110,6
104
112,6
107,3
98,9
109,8
104,9
102,2
123,9
124,9
112,7
121,9




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'George Udny Yule' @ 72.249.76.132

\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 & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=35547&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=35547&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=35547&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'George Udny Yule' @ 72.249.76.132







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)
0.0594.794.995.595.596.32595.592.195.5
0.196.7896.8196.996.997.1596.996.6996.9
0.1597.5697.6297.897.897.8597.497.5897.8
0.29898989898989898
0.2598.698.67598.698.7598.82598.698.82598.6
0.399.3899.5699.599.599.899.5100.0499.5
0.35100.4100.575100.6100.6100.65100.6100.125100.6
0.4100.92101.04101.1101.1101.1100.8100.86101.1
0.45102.52103.24103.8103.8103.4102.2102.76103.8
0.5103.9103.95103.9103.95103.95103.9103.95103.95
0.55104.24104.51104.3104.3104.45104.3104.69104.3
0.6105.32105.84105.6105.6105.6105.6106.56105.6
0.65107107.305107.3107.3107.175106.8107.395107.3
0.7107.46107.67107.7107.7107.55107.4107.43107.7
0.75108.4109.45108.4109.1108.75108.4108.75109.8
0.8110.44111.8110.6110.6110.6110.6111.4112.6
0.85112.66114.635112.7112.7112.675112.7115.065112.7
0.9117.2118.82117.5117.5117.25117120.58117.5
0.95122.3124.05123.9123.9122.4121.9124.75123.9

\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 & 94.7 & 94.9 & 95.5 & 95.5 & 96.325 & 95.5 & 92.1 & 95.5 \tabularnewline
0.1 & 96.78 & 96.81 & 96.9 & 96.9 & 97.15 & 96.9 & 96.69 & 96.9 \tabularnewline
0.15 & 97.56 & 97.62 & 97.8 & 97.8 & 97.85 & 97.4 & 97.58 & 97.8 \tabularnewline
0.2 & 98 & 98 & 98 & 98 & 98 & 98 & 98 & 98 \tabularnewline
0.25 & 98.6 & 98.675 & 98.6 & 98.75 & 98.825 & 98.6 & 98.825 & 98.6 \tabularnewline
0.3 & 99.38 & 99.56 & 99.5 & 99.5 & 99.8 & 99.5 & 100.04 & 99.5 \tabularnewline
0.35 & 100.4 & 100.575 & 100.6 & 100.6 & 100.65 & 100.6 & 100.125 & 100.6 \tabularnewline
0.4 & 100.92 & 101.04 & 101.1 & 101.1 & 101.1 & 100.8 & 100.86 & 101.1 \tabularnewline
0.45 & 102.52 & 103.24 & 103.8 & 103.8 & 103.4 & 102.2 & 102.76 & 103.8 \tabularnewline
0.5 & 103.9 & 103.95 & 103.9 & 103.95 & 103.95 & 103.9 & 103.95 & 103.95 \tabularnewline
0.55 & 104.24 & 104.51 & 104.3 & 104.3 & 104.45 & 104.3 & 104.69 & 104.3 \tabularnewline
0.6 & 105.32 & 105.84 & 105.6 & 105.6 & 105.6 & 105.6 & 106.56 & 105.6 \tabularnewline
0.65 & 107 & 107.305 & 107.3 & 107.3 & 107.175 & 106.8 & 107.395 & 107.3 \tabularnewline
0.7 & 107.46 & 107.67 & 107.7 & 107.7 & 107.55 & 107.4 & 107.43 & 107.7 \tabularnewline
0.75 & 108.4 & 109.45 & 108.4 & 109.1 & 108.75 & 108.4 & 108.75 & 109.8 \tabularnewline
0.8 & 110.44 & 111.8 & 110.6 & 110.6 & 110.6 & 110.6 & 111.4 & 112.6 \tabularnewline
0.85 & 112.66 & 114.635 & 112.7 & 112.7 & 112.675 & 112.7 & 115.065 & 112.7 \tabularnewline
0.9 & 117.2 & 118.82 & 117.5 & 117.5 & 117.25 & 117 & 120.58 & 117.5 \tabularnewline
0.95 & 122.3 & 124.05 & 123.9 & 123.9 & 122.4 & 121.9 & 124.75 & 123.9 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=35547&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]94.7[/C][C]94.9[/C][C]95.5[/C][C]95.5[/C][C]96.325[/C][C]95.5[/C][C]92.1[/C][C]95.5[/C][/ROW]
[ROW][C]0.1[/C][C]96.78[/C][C]96.81[/C][C]96.9[/C][C]96.9[/C][C]97.15[/C][C]96.9[/C][C]96.69[/C][C]96.9[/C][/ROW]
[ROW][C]0.15[/C][C]97.56[/C][C]97.62[/C][C]97.8[/C][C]97.8[/C][C]97.85[/C][C]97.4[/C][C]97.58[/C][C]97.8[/C][/ROW]
[ROW][C]0.2[/C][C]98[/C][C]98[/C][C]98[/C][C]98[/C][C]98[/C][C]98[/C][C]98[/C][C]98[/C][/ROW]
[ROW][C]0.25[/C][C]98.6[/C][C]98.675[/C][C]98.6[/C][C]98.75[/C][C]98.825[/C][C]98.6[/C][C]98.825[/C][C]98.6[/C][/ROW]
[ROW][C]0.3[/C][C]99.38[/C][C]99.56[/C][C]99.5[/C][C]99.5[/C][C]99.8[/C][C]99.5[/C][C]100.04[/C][C]99.5[/C][/ROW]
[ROW][C]0.35[/C][C]100.4[/C][C]100.575[/C][C]100.6[/C][C]100.6[/C][C]100.65[/C][C]100.6[/C][C]100.125[/C][C]100.6[/C][/ROW]
[ROW][C]0.4[/C][C]100.92[/C][C]101.04[/C][C]101.1[/C][C]101.1[/C][C]101.1[/C][C]100.8[/C][C]100.86[/C][C]101.1[/C][/ROW]
[ROW][C]0.45[/C][C]102.52[/C][C]103.24[/C][C]103.8[/C][C]103.8[/C][C]103.4[/C][C]102.2[/C][C]102.76[/C][C]103.8[/C][/ROW]
[ROW][C]0.5[/C][C]103.9[/C][C]103.95[/C][C]103.9[/C][C]103.95[/C][C]103.95[/C][C]103.9[/C][C]103.95[/C][C]103.95[/C][/ROW]
[ROW][C]0.55[/C][C]104.24[/C][C]104.51[/C][C]104.3[/C][C]104.3[/C][C]104.45[/C][C]104.3[/C][C]104.69[/C][C]104.3[/C][/ROW]
[ROW][C]0.6[/C][C]105.32[/C][C]105.84[/C][C]105.6[/C][C]105.6[/C][C]105.6[/C][C]105.6[/C][C]106.56[/C][C]105.6[/C][/ROW]
[ROW][C]0.65[/C][C]107[/C][C]107.305[/C][C]107.3[/C][C]107.3[/C][C]107.175[/C][C]106.8[/C][C]107.395[/C][C]107.3[/C][/ROW]
[ROW][C]0.7[/C][C]107.46[/C][C]107.67[/C][C]107.7[/C][C]107.7[/C][C]107.55[/C][C]107.4[/C][C]107.43[/C][C]107.7[/C][/ROW]
[ROW][C]0.75[/C][C]108.4[/C][C]109.45[/C][C]108.4[/C][C]109.1[/C][C]108.75[/C][C]108.4[/C][C]108.75[/C][C]109.8[/C][/ROW]
[ROW][C]0.8[/C][C]110.44[/C][C]111.8[/C][C]110.6[/C][C]110.6[/C][C]110.6[/C][C]110.6[/C][C]111.4[/C][C]112.6[/C][/ROW]
[ROW][C]0.85[/C][C]112.66[/C][C]114.635[/C][C]112.7[/C][C]112.7[/C][C]112.675[/C][C]112.7[/C][C]115.065[/C][C]112.7[/C][/ROW]
[ROW][C]0.9[/C][C]117.2[/C][C]118.82[/C][C]117.5[/C][C]117.5[/C][C]117.25[/C][C]117[/C][C]120.58[/C][C]117.5[/C][/ROW]
[ROW][C]0.95[/C][C]122.3[/C][C]124.05[/C][C]123.9[/C][C]123.9[/C][C]122.4[/C][C]121.9[/C][C]124.75[/C][C]123.9[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=35547&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=35547&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)
0.0594.794.995.595.596.32595.592.195.5
0.196.7896.8196.996.997.1596.996.6996.9
0.1597.5697.6297.897.897.8597.497.5897.8
0.29898989898989898
0.2598.698.67598.698.7598.82598.698.82598.6
0.399.3899.5699.599.599.899.5100.0499.5
0.35100.4100.575100.6100.6100.65100.6100.125100.6
0.4100.92101.04101.1101.1101.1100.8100.86101.1
0.45102.52103.24103.8103.8103.4102.2102.76103.8
0.5103.9103.95103.9103.95103.95103.9103.95103.95
0.55104.24104.51104.3104.3104.45104.3104.69104.3
0.6105.32105.84105.6105.6105.6105.6106.56105.6
0.65107107.305107.3107.3107.175106.8107.395107.3
0.7107.46107.67107.7107.7107.55107.4107.43107.7
0.75108.4109.45108.4109.1108.75108.4108.75109.8
0.8110.44111.8110.6110.6110.6110.6111.4112.6
0.85112.66114.635112.7112.7112.675112.7115.065112.7
0.9117.2118.82117.5117.5117.25117120.58117.5
0.95122.3124.05123.9123.9122.4121.9124.75123.9



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')