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Author's title

Author

*Unverified author*

R Software Module

rwasp_percentiles.wasp

Title produced by software

Percentiles

Date of computation

Tue, 19 Feb 2019 15:12:26 +0100

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2019/Feb/19/t1550586918ntq2lgrjk5qnkhm.htm/, Retrieved Sat, 04 May 2024 12:34:45 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=318731, Retrieved Sat, 04 May 2024 12:34:45 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

111

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

-       [Percentiles] [] [2019-02-19 14:12:26] [d41d8cd98f00b204e9800998ecf8427e] [Current]

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Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	1 seconds
R Server	Big 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=318731&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=318731&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=318731&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 Output	view raw output of R engine
Computing time	1 seconds
R Server	Big Analytics Cloud Computing Center

Percentiles - Ungrouped Data
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)
0.05	95.65	95.7	96	96	97.2	96	95.3	96
0.1	98	98	98	98	98	98	98	98
0.15	98	98	98	98	98	98	98	98
0.2	98	98	98	98	98.8	98	98	98
0.25	100	100	100	100	100	100	100	100
0.3	100	100	100	100	100	100	100	100
0.35	101.1	101.8	102	102	102	102	100.2	102
0.4	102	102	102	102	102	102	102	102
0.45	104.55	105	105	105	105	105	105	105
0.5	105	105	105	105	105	105	105	105
0.55	106.15	106.7	107	107	106.6	106	106.3	107
0.6	111	112	112	112	112	112	112	112
0.65	112	112	112	112	112	112	112	112
0.7	112.1	112.8	113	113	112.4	112	112.2	113
0.75	113	114.5	113	113	113	113	114.5	114.5
0.8	116	116	116	116	116	116	116	116
0.85	116	116	116	116	116	116	116	116
0.9	116	116	116	116	116	116	116	116
0.95	116	116.6	116	116	116	116	117.4	116

\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 & 95.65 & 95.7 & 96 & 96 & 97.2 & 96 & 95.3 & 96 \tabularnewline
0.1 & 98 & 98 & 98 & 98 & 98 & 98 & 98 & 98 \tabularnewline
0.15 & 98 & 98 & 98 & 98 & 98 & 98 & 98 & 98 \tabularnewline
0.2 & 98 & 98 & 98 & 98 & 98.8 & 98 & 98 & 98 \tabularnewline
0.25 & 100 & 100 & 100 & 100 & 100 & 100 & 100 & 100 \tabularnewline
0.3 & 100 & 100 & 100 & 100 & 100 & 100 & 100 & 100 \tabularnewline
0.35 & 101.1 & 101.8 & 102 & 102 & 102 & 102 & 100.2 & 102 \tabularnewline
0.4 & 102 & 102 & 102 & 102 & 102 & 102 & 102 & 102 \tabularnewline
0.45 & 104.55 & 105 & 105 & 105 & 105 & 105 & 105 & 105 \tabularnewline
0.5 & 105 & 105 & 105 & 105 & 105 & 105 & 105 & 105 \tabularnewline
0.55 & 106.15 & 106.7 & 107 & 107 & 106.6 & 106 & 106.3 & 107 \tabularnewline
0.6 & 111 & 112 & 112 & 112 & 112 & 112 & 112 & 112 \tabularnewline
0.65 & 112 & 112 & 112 & 112 & 112 & 112 & 112 & 112 \tabularnewline
0.7 & 112.1 & 112.8 & 113 & 113 & 112.4 & 112 & 112.2 & 113 \tabularnewline
0.75 & 113 & 114.5 & 113 & 113 & 113 & 113 & 114.5 & 114.5 \tabularnewline
0.8 & 116 & 116 & 116 & 116 & 116 & 116 & 116 & 116 \tabularnewline
0.85 & 116 & 116 & 116 & 116 & 116 & 116 & 116 & 116 \tabularnewline
0.9 & 116 & 116 & 116 & 116 & 116 & 116 & 116 & 116 \tabularnewline
0.95 & 116 & 116.6 & 116 & 116 & 116 & 116 & 117.4 & 116 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=318731&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]95.65[/C][C]95.7[/C][C]96[/C][C]96[/C][C]97.2[/C][C]96[/C][C]95.3[/C][C]96[/C][/ROW]
[ROW][C]0.1[/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]0.15[/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]0.2[/C][C]98[/C][C]98[/C][C]98[/C][C]98[/C][C]98.8[/C][C]98[/C][C]98[/C][C]98[/C][/ROW]
[ROW][C]0.25[/C][C]100[/C][C]100[/C][C]100[/C][C]100[/C][C]100[/C][C]100[/C][C]100[/C][C]100[/C][/ROW]
[ROW][C]0.3[/C][C]100[/C][C]100[/C][C]100[/C][C]100[/C][C]100[/C][C]100[/C][C]100[/C][C]100[/C][/ROW]
[ROW][C]0.35[/C][C]101.1[/C][C]101.8[/C][C]102[/C][C]102[/C][C]102[/C][C]102[/C][C]100.2[/C][C]102[/C][/ROW]
[ROW][C]0.4[/C][C]102[/C][C]102[/C][C]102[/C][C]102[/C][C]102[/C][C]102[/C][C]102[/C][C]102[/C][/ROW]
[ROW][C]0.45[/C][C]104.55[/C][C]105[/C][C]105[/C][C]105[/C][C]105[/C][C]105[/C][C]105[/C][C]105[/C][/ROW]
[ROW][C]0.5[/C][C]105[/C][C]105[/C][C]105[/C][C]105[/C][C]105[/C][C]105[/C][C]105[/C][C]105[/C][/ROW]
[ROW][C]0.55[/C][C]106.15[/C][C]106.7[/C][C]107[/C][C]107[/C][C]106.6[/C][C]106[/C][C]106.3[/C][C]107[/C][/ROW]
[ROW][C]0.6[/C][C]111[/C][C]112[/C][C]112[/C][C]112[/C][C]112[/C][C]112[/C][C]112[/C][C]112[/C][/ROW]
[ROW][C]0.65[/C][C]112[/C][C]112[/C][C]112[/C][C]112[/C][C]112[/C][C]112[/C][C]112[/C][C]112[/C][/ROW]
[ROW][C]0.7[/C][C]112.1[/C][C]112.8[/C][C]113[/C][C]113[/C][C]112.4[/C][C]112[/C][C]112.2[/C][C]113[/C][/ROW]
[ROW][C]0.75[/C][C]113[/C][C]114.5[/C][C]113[/C][C]113[/C][C]113[/C][C]113[/C][C]114.5[/C][C]114.5[/C][/ROW]
[ROW][C]0.8[/C][C]116[/C][C]116[/C][C]116[/C][C]116[/C][C]116[/C][C]116[/C][C]116[/C][C]116[/C][/ROW]
[ROW][C]0.85[/C][C]116[/C][C]116[/C][C]116[/C][C]116[/C][C]116[/C][C]116[/C][C]116[/C][C]116[/C][/ROW]
[ROW][C]0.9[/C][C]116[/C][C]116[/C][C]116[/C][C]116[/C][C]116[/C][C]116[/C][C]116[/C][C]116[/C][/ROW]
[ROW][C]0.95[/C][C]116[/C][C]116.6[/C][C]116[/C][C]116[/C][C]116[/C][C]116[/C][C]117.4[/C][C]116[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=318731&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=318731&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
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)
0.05	95.65	95.7	96	96	97.2	96	95.3	96
0.1	98	98	98	98	98	98	98	98
0.15	98	98	98	98	98	98	98	98
0.2	98	98	98	98	98.8	98	98	98
0.25	100	100	100	100	100	100	100	100
0.3	100	100	100	100	100	100	100	100
0.35	101.1	101.8	102	102	102	102	100.2	102
0.4	102	102	102	102	102	102	102	102
0.45	104.55	105	105	105	105	105	105	105
0.5	105	105	105	105	105	105	105	105
0.55	106.15	106.7	107	107	106.6	106	106.3	107
0.6	111	112	112	112	112	112	112	112
0.65	112	112	112	112	112	112	112	112
0.7	112.1	112.8	113	113	112.4	112	112.2	113
0.75	113	114.5	113	113	113	113	114.5	114.5
0.8	116	116	116	116	116	116	116	116
0.85	116	116	116	116	116	116	116	116
0.9	116	116	116	116	116	116	116	116
0.95	116	116.6	116	116	116	116	117.4	116

Figure 1

PNG link

Postscript link

PDF link

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')

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Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code