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Author's title

Author*Unverified author*
R Software Modulerwasp_percentiles.wasp
Title produced by softwarePercentiles
Date of computationThu, 13 Feb 2020 18:30:33 +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/13/t158161515315fpydcneggo19f.htm/, Retrieved Wed, 21 Apr 2021 07:12:49 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=319075, Retrieved Wed, 21 Apr 2021 07:12:49 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsDistribute
Estimated Impact37
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Percentiles] [Spot Speed ] [2020-02-13 17:30:33] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataseries X:
55
56
61
51
59
51
51
5
68
49
77
32
53
49
28
60
45
42
35
25
29
46
49
58
47
56
40
34
48
35
62
33
40
44
28
57
50
47
64
33
42
30
28
33
22
59
32
55
38





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
R Framework error message
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.

\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
R Framework error message & 
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
\tabularnewline \hline \end{tabular} %Source: https://freestatistics.org/blog/index.php?pk=319075&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] [ROW]R Framework error message[/C][C]
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=319075&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=319075&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
R Framework error message
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.







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)
0.0523.3523.5252526.22223.523.5
0.12828282828282828
0.1529.3529.5303030.42929.529.5
0.23232323232.6323232
0.253333333333333333
0.334.735353535353535
0.3538.339404039.6383939
0.441.242424242424242
0.4544.0544.5454544.64444.544.5
0.546.547474747474747
0.5547.9548.5484848.44848.549
0.64949494949494949
0.6550.8551515151515151
0.751.653535352.2515353
0.755555.55555555555.555.5
0.856.257575756.4565757
0.8558.6559595958.8595959
0.960.161616160.2606161
0.9563.166646463.2646666

\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 & 23.35 & 23.5 & 25 & 25 & 26.2 & 22 & 23.5 & 23.5 \tabularnewline
0.1 & 28 & 28 & 28 & 28 & 28 & 28 & 28 & 28 \tabularnewline
0.15 & 29.35 & 29.5 & 30 & 30 & 30.4 & 29 & 29.5 & 29.5 \tabularnewline
0.2 & 32 & 32 & 32 & 32 & 32.6 & 32 & 32 & 32 \tabularnewline
0.25 & 33 & 33 & 33 & 33 & 33 & 33 & 33 & 33 \tabularnewline
0.3 & 34.7 & 35 & 35 & 35 & 35 & 35 & 35 & 35 \tabularnewline
0.35 & 38.3 & 39 & 40 & 40 & 39.6 & 38 & 39 & 39 \tabularnewline
0.4 & 41.2 & 42 & 42 & 42 & 42 & 42 & 42 & 42 \tabularnewline
0.45 & 44.05 & 44.5 & 45 & 45 & 44.6 & 44 & 44.5 & 44.5 \tabularnewline
0.5 & 46.5 & 47 & 47 & 47 & 47 & 47 & 47 & 47 \tabularnewline
0.55 & 47.95 & 48.5 & 48 & 48 & 48.4 & 48 & 48.5 & 49 \tabularnewline
0.6 & 49 & 49 & 49 & 49 & 49 & 49 & 49 & 49 \tabularnewline
0.65 & 50.85 & 51 & 51 & 51 & 51 & 51 & 51 & 51 \tabularnewline
0.7 & 51.6 & 53 & 53 & 53 & 52.2 & 51 & 53 & 53 \tabularnewline
0.75 & 55 & 55.5 & 55 & 55 & 55 & 55 & 55.5 & 55.5 \tabularnewline
0.8 & 56.2 & 57 & 57 & 57 & 56.4 & 56 & 57 & 57 \tabularnewline
0.85 & 58.65 & 59 & 59 & 59 & 58.8 & 59 & 59 & 59 \tabularnewline
0.9 & 60.1 & 61 & 61 & 61 & 60.2 & 60 & 61 & 61 \tabularnewline
0.95 & 63.1 & 66 & 64 & 64 & 63.2 & 64 & 66 & 66 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=319075&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]23.35[/C][C]23.5[/C][C]25[/C][C]25[/C][C]26.2[/C][C]22[/C][C]23.5[/C][C]23.5[/C][/ROW]
[ROW][C]0.1[/C][C]28[/C][C]28[/C][C]28[/C][C]28[/C][C]28[/C][C]28[/C][C]28[/C][C]28[/C][/ROW]
[ROW][C]0.15[/C][C]29.35[/C][C]29.5[/C][C]30[/C][C]30[/C][C]30.4[/C][C]29[/C][C]29.5[/C][C]29.5[/C][/ROW]
[ROW][C]0.2[/C][C]32[/C][C]32[/C][C]32[/C][C]32[/C][C]32.6[/C][C]32[/C][C]32[/C][C]32[/C][/ROW]
[ROW][C]0.25[/C][C]33[/C][C]33[/C][C]33[/C][C]33[/C][C]33[/C][C]33[/C][C]33[/C][C]33[/C][/ROW]
[ROW][C]0.3[/C][C]34.7[/C][C]35[/C][C]35[/C][C]35[/C][C]35[/C][C]35[/C][C]35[/C][C]35[/C][/ROW]
[ROW][C]0.35[/C][C]38.3[/C][C]39[/C][C]40[/C][C]40[/C][C]39.6[/C][C]38[/C][C]39[/C][C]39[/C][/ROW]
[ROW][C]0.4[/C][C]41.2[/C][C]42[/C][C]42[/C][C]42[/C][C]42[/C][C]42[/C][C]42[/C][C]42[/C][/ROW]
[ROW][C]0.45[/C][C]44.05[/C][C]44.5[/C][C]45[/C][C]45[/C][C]44.6[/C][C]44[/C][C]44.5[/C][C]44.5[/C][/ROW]
[ROW][C]0.5[/C][C]46.5[/C][C]47[/C][C]47[/C][C]47[/C][C]47[/C][C]47[/C][C]47[/C][C]47[/C][/ROW]
[ROW][C]0.55[/C][C]47.95[/C][C]48.5[/C][C]48[/C][C]48[/C][C]48.4[/C][C]48[/C][C]48.5[/C][C]49[/C][/ROW]
[ROW][C]0.6[/C][C]49[/C][C]49[/C][C]49[/C][C]49[/C][C]49[/C][C]49[/C][C]49[/C][C]49[/C][/ROW]
[ROW][C]0.65[/C][C]50.85[/C][C]51[/C][C]51[/C][C]51[/C][C]51[/C][C]51[/C][C]51[/C][C]51[/C][/ROW]
[ROW][C]0.7[/C][C]51.6[/C][C]53[/C][C]53[/C][C]53[/C][C]52.2[/C][C]51[/C][C]53[/C][C]53[/C][/ROW]
[ROW][C]0.75[/C][C]55[/C][C]55.5[/C][C]55[/C][C]55[/C][C]55[/C][C]55[/C][C]55.5[/C][C]55.5[/C][/ROW]
[ROW][C]0.8[/C][C]56.2[/C][C]57[/C][C]57[/C][C]57[/C][C]56.4[/C][C]56[/C][C]57[/C][C]57[/C][/ROW]
[ROW][C]0.85[/C][C]58.65[/C][C]59[/C][C]59[/C][C]59[/C][C]58.8[/C][C]59[/C][C]59[/C][C]59[/C][/ROW]
[ROW][C]0.9[/C][C]60.1[/C][C]61[/C][C]61[/C][C]61[/C][C]60.2[/C][C]60[/C][C]61[/C][C]61[/C][/ROW]
[ROW][C]0.95[/C][C]63.1[/C][C]66[/C][C]64[/C][C]64[/C][C]63.2[/C][C]64[/C][C]66[/C][C]66[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=319075&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=319075&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)
0.0523.3523.5252526.22223.523.5
0.12828282828282828
0.1529.3529.5303030.42929.529.5
0.23232323232.6323232
0.253333333333333333
0.334.735353535353535
0.3538.339404039.6383939
0.441.242424242424242
0.4544.0544.5454544.64444.544.5
0.546.547474747474747
0.5547.9548.5484848.44848.549
0.64949494949494949
0.6550.8551515151515151
0.751.653535352.2515353
0.755555.55555555555.555.5
0.856.257575756.4565757
0.8558.6559595958.8595959
0.960.161616160.2606161
0.9563.166646463.2646666



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')