Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_percentiles.wasp
Title produced by softwarePercentiles
Date of computationMon, 03 Feb 2020 00:14:03 +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/03/t15806852998edxavzwqteu8b0.htm/, Retrieved Fri, 07 May 2021 11:17:11 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=319068, Retrieved Fri, 07 May 2021 11:17:11 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact56
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Percentiles] [] [2020-02-02 23:14:03] [d41d8cd98f00b204e9800998ecf8427e] [Current]
Feedback Forum

Post a new message
Dataseries X:
1.83
-1.8
0.09
-1.53
-0.58
0.21
1.25
-1.22
1.32
3.63
-2.3
0.65
-0.01
-1.11
0.13
-1.07
0.8
-1.98
0.02
0.25
3.3
1.036
2.042
1.04
-0.87
-0.39
-0.29
2.08
3.36
-0.53
-0.07
0.57
2.92
1.99
1.74
-0.76
2.35
-1.91
2.22
2.57




Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R ServerBig Analytics Cloud Computing Center

\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 time1 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=319068&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]1 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=319068&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=319068&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 time1 seconds
R ServerBig Analytics Cloud Computing Center







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)
0.05-1.98-1.9765-1.98-1.945-1.9135-1.98-1.9135-1.98
0.1-1.8-1.773-1.8-1.665-1.557-1.8-1.557-1.8
0.15-1.22-1.2035-1.22-1.165-1.1265-1.22-1.1265-1.22
0.2-1.07-1.03-1.07-0.97-0.91-1.07-0.91-1.07
0.25-0.76-0.715-0.76-0.67-0.625-0.76-0.625-0.76
0.3-0.53-0.488-0.53-0.46-0.432-0.53-0.432-0.53
0.35-0.29-0.213-0.29-0.18-0.147-0.29-0.147-0.29
0.4-0.010.002-0.010.0050.008-0.010.008-0.01
0.450.090.1080.090.110.1120.090.1120.09
0.50.210.230.210.230.230.210.230.23
0.550.570.6140.570.610.6060.570.6060.65
0.60.80.94160.80.9180.89440.80.89441.036
0.651.041.17651.041.1451.11351.041.11351.25
0.71.321.6141.321.531.4461.321.4461.74
0.751.831.951.831.911.871.831.871.99
0.82.0422.07242.0422.0612.04962.0422.04962.08
0.852.222.33052.222.2852.23952.222.23952.35
0.92.572.8852.572.7452.6052.572.6052.92
0.953.33.3573.33.333.3033.33.3033.36

\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 & -1.98 & -1.9765 & -1.98 & -1.945 & -1.9135 & -1.98 & -1.9135 & -1.98 \tabularnewline
0.1 & -1.8 & -1.773 & -1.8 & -1.665 & -1.557 & -1.8 & -1.557 & -1.8 \tabularnewline
0.15 & -1.22 & -1.2035 & -1.22 & -1.165 & -1.1265 & -1.22 & -1.1265 & -1.22 \tabularnewline
0.2 & -1.07 & -1.03 & -1.07 & -0.97 & -0.91 & -1.07 & -0.91 & -1.07 \tabularnewline
0.25 & -0.76 & -0.715 & -0.76 & -0.67 & -0.625 & -0.76 & -0.625 & -0.76 \tabularnewline
0.3 & -0.53 & -0.488 & -0.53 & -0.46 & -0.432 & -0.53 & -0.432 & -0.53 \tabularnewline
0.35 & -0.29 & -0.213 & -0.29 & -0.18 & -0.147 & -0.29 & -0.147 & -0.29 \tabularnewline
0.4 & -0.01 & 0.002 & -0.01 & 0.005 & 0.008 & -0.01 & 0.008 & -0.01 \tabularnewline
0.45 & 0.09 & 0.108 & 0.09 & 0.11 & 0.112 & 0.09 & 0.112 & 0.09 \tabularnewline
0.5 & 0.21 & 0.23 & 0.21 & 0.23 & 0.23 & 0.21 & 0.23 & 0.23 \tabularnewline
0.55 & 0.57 & 0.614 & 0.57 & 0.61 & 0.606 & 0.57 & 0.606 & 0.65 \tabularnewline
0.6 & 0.8 & 0.9416 & 0.8 & 0.918 & 0.8944 & 0.8 & 0.8944 & 1.036 \tabularnewline
0.65 & 1.04 & 1.1765 & 1.04 & 1.145 & 1.1135 & 1.04 & 1.1135 & 1.25 \tabularnewline
0.7 & 1.32 & 1.614 & 1.32 & 1.53 & 1.446 & 1.32 & 1.446 & 1.74 \tabularnewline
0.75 & 1.83 & 1.95 & 1.83 & 1.91 & 1.87 & 1.83 & 1.87 & 1.99 \tabularnewline
0.8 & 2.042 & 2.0724 & 2.042 & 2.061 & 2.0496 & 2.042 & 2.0496 & 2.08 \tabularnewline
0.85 & 2.22 & 2.3305 & 2.22 & 2.285 & 2.2395 & 2.22 & 2.2395 & 2.35 \tabularnewline
0.9 & 2.57 & 2.885 & 2.57 & 2.745 & 2.605 & 2.57 & 2.605 & 2.92 \tabularnewline
0.95 & 3.3 & 3.357 & 3.3 & 3.33 & 3.303 & 3.3 & 3.303 & 3.36 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=319068&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]-1.98[/C][C]-1.9765[/C][C]-1.98[/C][C]-1.945[/C][C]-1.9135[/C][C]-1.98[/C][C]-1.9135[/C][C]-1.98[/C][/ROW]
[ROW][C]0.1[/C][C]-1.8[/C][C]-1.773[/C][C]-1.8[/C][C]-1.665[/C][C]-1.557[/C][C]-1.8[/C][C]-1.557[/C][C]-1.8[/C][/ROW]
[ROW][C]0.15[/C][C]-1.22[/C][C]-1.2035[/C][C]-1.22[/C][C]-1.165[/C][C]-1.1265[/C][C]-1.22[/C][C]-1.1265[/C][C]-1.22[/C][/ROW]
[ROW][C]0.2[/C][C]-1.07[/C][C]-1.03[/C][C]-1.07[/C][C]-0.97[/C][C]-0.91[/C][C]-1.07[/C][C]-0.91[/C][C]-1.07[/C][/ROW]
[ROW][C]0.25[/C][C]-0.76[/C][C]-0.715[/C][C]-0.76[/C][C]-0.67[/C][C]-0.625[/C][C]-0.76[/C][C]-0.625[/C][C]-0.76[/C][/ROW]
[ROW][C]0.3[/C][C]-0.53[/C][C]-0.488[/C][C]-0.53[/C][C]-0.46[/C][C]-0.432[/C][C]-0.53[/C][C]-0.432[/C][C]-0.53[/C][/ROW]
[ROW][C]0.35[/C][C]-0.29[/C][C]-0.213[/C][C]-0.29[/C][C]-0.18[/C][C]-0.147[/C][C]-0.29[/C][C]-0.147[/C][C]-0.29[/C][/ROW]
[ROW][C]0.4[/C][C]-0.01[/C][C]0.002[/C][C]-0.01[/C][C]0.005[/C][C]0.008[/C][C]-0.01[/C][C]0.008[/C][C]-0.01[/C][/ROW]
[ROW][C]0.45[/C][C]0.09[/C][C]0.108[/C][C]0.09[/C][C]0.11[/C][C]0.112[/C][C]0.09[/C][C]0.112[/C][C]0.09[/C][/ROW]
[ROW][C]0.5[/C][C]0.21[/C][C]0.23[/C][C]0.21[/C][C]0.23[/C][C]0.23[/C][C]0.21[/C][C]0.23[/C][C]0.23[/C][/ROW]
[ROW][C]0.55[/C][C]0.57[/C][C]0.614[/C][C]0.57[/C][C]0.61[/C][C]0.606[/C][C]0.57[/C][C]0.606[/C][C]0.65[/C][/ROW]
[ROW][C]0.6[/C][C]0.8[/C][C]0.9416[/C][C]0.8[/C][C]0.918[/C][C]0.8944[/C][C]0.8[/C][C]0.8944[/C][C]1.036[/C][/ROW]
[ROW][C]0.65[/C][C]1.04[/C][C]1.1765[/C][C]1.04[/C][C]1.145[/C][C]1.1135[/C][C]1.04[/C][C]1.1135[/C][C]1.25[/C][/ROW]
[ROW][C]0.7[/C][C]1.32[/C][C]1.614[/C][C]1.32[/C][C]1.53[/C][C]1.446[/C][C]1.32[/C][C]1.446[/C][C]1.74[/C][/ROW]
[ROW][C]0.75[/C][C]1.83[/C][C]1.95[/C][C]1.83[/C][C]1.91[/C][C]1.87[/C][C]1.83[/C][C]1.87[/C][C]1.99[/C][/ROW]
[ROW][C]0.8[/C][C]2.042[/C][C]2.0724[/C][C]2.042[/C][C]2.061[/C][C]2.0496[/C][C]2.042[/C][C]2.0496[/C][C]2.08[/C][/ROW]
[ROW][C]0.85[/C][C]2.22[/C][C]2.3305[/C][C]2.22[/C][C]2.285[/C][C]2.2395[/C][C]2.22[/C][C]2.2395[/C][C]2.35[/C][/ROW]
[ROW][C]0.9[/C][C]2.57[/C][C]2.885[/C][C]2.57[/C][C]2.745[/C][C]2.605[/C][C]2.57[/C][C]2.605[/C][C]2.92[/C][/ROW]
[ROW][C]0.95[/C][C]3.3[/C][C]3.357[/C][C]3.3[/C][C]3.33[/C][C]3.303[/C][C]3.3[/C][C]3.303[/C][C]3.36[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=319068&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=319068&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)
0.05-1.98-1.9765-1.98-1.945-1.9135-1.98-1.9135-1.98
0.1-1.8-1.773-1.8-1.665-1.557-1.8-1.557-1.8
0.15-1.22-1.2035-1.22-1.165-1.1265-1.22-1.1265-1.22
0.2-1.07-1.03-1.07-0.97-0.91-1.07-0.91-1.07
0.25-0.76-0.715-0.76-0.67-0.625-0.76-0.625-0.76
0.3-0.53-0.488-0.53-0.46-0.432-0.53-0.432-0.53
0.35-0.29-0.213-0.29-0.18-0.147-0.29-0.147-0.29
0.4-0.010.002-0.010.0050.008-0.010.008-0.01
0.450.090.1080.090.110.1120.090.1120.09
0.50.210.230.210.230.230.210.230.23
0.550.570.6140.570.610.6060.570.6060.65
0.60.80.94160.80.9180.89440.80.89441.036
0.651.041.17651.041.1451.11351.041.11351.25
0.71.321.6141.321.531.4461.321.4461.74
0.751.831.951.831.911.871.831.871.99
0.82.0422.07242.0422.0612.04962.0422.04962.08
0.852.222.33052.222.2852.23952.222.23952.35
0.92.572.8852.572.7452.6052.572.6052.92
0.953.33.3573.33.333.3033.33.3033.36



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')