## Free Statistics

of Irreproducible Research!

Author's title
Author*Unverified author*
R Software Modulerwasp_percentiles.wasp
Title produced by softwarePercentiles
Date of computationSat, 15 Feb 2020 16:27:06 +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/15/t15817805099852au5qtk8j0se.htm/, Retrieved Fri, 07 May 2021 10:39:24 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=319076, Retrieved Fri, 07 May 2021 10:39:24 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact44
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Percentiles] [economic dynamism] [2020-02-15 15:27:06] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataseries X:
25.8057
41.1648
49.1361
50.9866
37.4511
38.0793
61.9281
59.1724
51.915
37.7251
41.9543
39.6282
43.6952
39.6553
44.9346
33.6074
47.8506
42.0265
46.0521
21.6643
43.7178
48.6159
48.3652
58.0767
43.8555
43.6252

 Summary of computational transaction Raw Input view raw input (R code) Raw Output view raw output of R engine Computing time 0 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 time0 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=319076&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] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=319076&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=319076&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 0 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 22.9067 23.1138 25.8057 25.8057 27.7561 21.6643 24.3562 21.6643 0.1 30.4867 31.2669 33.6074 33.6074 35.5292 33.6074 28.1462 33.6074 0.15 37.0667 37.4648 37.4511 37.4511 37.6566 37.4511 37.7114 37.4511 0.2 37.7959 37.8668 38.0793 38.0793 38.0793 37.7251 37.9376 37.7251 0.25 38.8538 39.241 39.6282 39.6282 39.635 39.6282 38.4665 39.6282 0.3 39.6499 39.8062 39.6553 39.6553 40.41 39.6553 41.0138 39.6553 0.35 41.2438 41.5201 41.9543 41.9543 41.7569 41.1648 41.599 41.1648 0.4 41.9832 42.0121 42.0265 42.0265 42.0265 41.9543 41.9687 42.0265 0.45 43.1456 43.6357 43.6252 43.6252 43.6427 43.6252 43.6847 43.6252 0.5 43.6952 43.7065 43.6952 43.7065 43.7065 43.6952 43.7065 43.7065 0.55 43.7591 43.8348 43.8555 43.8555 43.8211 43.7178 43.7385 43.8555 0.6 44.503 45.1581 44.9346 44.9346 44.9346 44.9346 45.8286 44.9346 0.65 45.9404 47.0413 46.0521 46.0521 46.5017 46.0521 46.8614 47.8506 0.7 47.9535 48.3137 48.3652 48.3652 48.1079 47.8506 47.9021 48.3652 0.75 48.4906 48.746 48.6159 48.6159 48.5532 48.6159 49.006 48.6159 0.8 49.0321 50.2464 49.1361 49.1361 49.1361 49.1361 49.8763 50.9866 0.85 51.0794 51.8686 51.915 51.915 51.2187 50.9866 51.033 51.915 0.9 54.3797 58.4054 58.0767 58.0767 54.9958 51.915 58.8437 58.0767 0.95 58.8437 60.9636 59.1724 59.1724 58.8985 59.1724 60.1369 61.9281

\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 & 22.9067 & 23.1138 & 25.8057 & 25.8057 & 27.7561 & 21.6643 & 24.3562 & 21.6643 \tabularnewline
0.1 & 30.4867 & 31.2669 & 33.6074 & 33.6074 & 35.5292 & 33.6074 & 28.1462 & 33.6074 \tabularnewline
0.15 & 37.0667 & 37.4648 & 37.4511 & 37.4511 & 37.6566 & 37.4511 & 37.7114 & 37.4511 \tabularnewline
0.2 & 37.7959 & 37.8668 & 38.0793 & 38.0793 & 38.0793 & 37.7251 & 37.9376 & 37.7251 \tabularnewline
0.25 & 38.8538 & 39.241 & 39.6282 & 39.6282 & 39.635 & 39.6282 & 38.4665 & 39.6282 \tabularnewline
0.3 & 39.6499 & 39.8062 & 39.6553 & 39.6553 & 40.41 & 39.6553 & 41.0138 & 39.6553 \tabularnewline
0.35 & 41.2438 & 41.5201 & 41.9543 & 41.9543 & 41.7569 & 41.1648 & 41.599 & 41.1648 \tabularnewline
0.4 & 41.9832 & 42.0121 & 42.0265 & 42.0265 & 42.0265 & 41.9543 & 41.9687 & 42.0265 \tabularnewline
0.45 & 43.1456 & 43.6357 & 43.6252 & 43.6252 & 43.6427 & 43.6252 & 43.6847 & 43.6252 \tabularnewline
0.5 & 43.6952 & 43.7065 & 43.6952 & 43.7065 & 43.7065 & 43.6952 & 43.7065 & 43.7065 \tabularnewline
0.55 & 43.7591 & 43.8348 & 43.8555 & 43.8555 & 43.8211 & 43.7178 & 43.7385 & 43.8555 \tabularnewline
0.6 & 44.503 & 45.1581 & 44.9346 & 44.9346 & 44.9346 & 44.9346 & 45.8286 & 44.9346 \tabularnewline
0.65 & 45.9404 & 47.0413 & 46.0521 & 46.0521 & 46.5017 & 46.0521 & 46.8614 & 47.8506 \tabularnewline
0.7 & 47.9535 & 48.3137 & 48.3652 & 48.3652 & 48.1079 & 47.8506 & 47.9021 & 48.3652 \tabularnewline
0.75 & 48.4906 & 48.746 & 48.6159 & 48.6159 & 48.5532 & 48.6159 & 49.006 & 48.6159 \tabularnewline
0.8 & 49.0321 & 50.2464 & 49.1361 & 49.1361 & 49.1361 & 49.1361 & 49.8763 & 50.9866 \tabularnewline
0.85 & 51.0794 & 51.8686 & 51.915 & 51.915 & 51.2187 & 50.9866 & 51.033 & 51.915 \tabularnewline
0.9 & 54.3797 & 58.4054 & 58.0767 & 58.0767 & 54.9958 & 51.915 & 58.8437 & 58.0767 \tabularnewline
0.95 & 58.8437 & 60.9636 & 59.1724 & 59.1724 & 58.8985 & 59.1724 & 60.1369 & 61.9281 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=319076&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]22.9067[/C][C]23.1138[/C][C]25.8057[/C][C]25.8057[/C][C]27.7561[/C][C]21.6643[/C][C]24.3562[/C][C]21.6643[/C][/ROW]
[ROW][C]0.1[/C][C]30.4867[/C][C]31.2669[/C][C]33.6074[/C][C]33.6074[/C][C]35.5292[/C][C]33.6074[/C][C]28.1462[/C][C]33.6074[/C][/ROW]
[ROW][C]0.15[/C][C]37.0667[/C][C]37.4648[/C][C]37.4511[/C][C]37.4511[/C][C]37.6566[/C][C]37.4511[/C][C]37.7114[/C][C]37.4511[/C][/ROW]
[ROW][C]0.2[/C][C]37.7959[/C][C]37.8668[/C][C]38.0793[/C][C]38.0793[/C][C]38.0793[/C][C]37.7251[/C][C]37.9376[/C][C]37.7251[/C][/ROW]
[ROW][C]0.25[/C][C]38.8538[/C][C]39.241[/C][C]39.6282[/C][C]39.6282[/C][C]39.635[/C][C]39.6282[/C][C]38.4665[/C][C]39.6282[/C][/ROW]
[ROW][C]0.3[/C][C]39.6499[/C][C]39.8062[/C][C]39.6553[/C][C]39.6553[/C][C]40.41[/C][C]39.6553[/C][C]41.0138[/C][C]39.6553[/C][/ROW]
[ROW][C]0.35[/C][C]41.2438[/C][C]41.5201[/C][C]41.9543[/C][C]41.9543[/C][C]41.7569[/C][C]41.1648[/C][C]41.599[/C][C]41.1648[/C][/ROW]
[ROW][C]0.4[/C][C]41.9832[/C][C]42.0121[/C][C]42.0265[/C][C]42.0265[/C][C]42.0265[/C][C]41.9543[/C][C]41.9687[/C][C]42.0265[/C][/ROW]
[ROW][C]0.45[/C][C]43.1456[/C][C]43.6357[/C][C]43.6252[/C][C]43.6252[/C][C]43.6427[/C][C]43.6252[/C][C]43.6847[/C][C]43.6252[/C][/ROW]
[ROW][C]0.5[/C][C]43.6952[/C][C]43.7065[/C][C]43.6952[/C][C]43.7065[/C][C]43.7065[/C][C]43.6952[/C][C]43.7065[/C][C]43.7065[/C][/ROW]
[ROW][C]0.55[/C][C]43.7591[/C][C]43.8348[/C][C]43.8555[/C][C]43.8555[/C][C]43.8211[/C][C]43.7178[/C][C]43.7385[/C][C]43.8555[/C][/ROW]
[ROW][C]0.6[/C][C]44.503[/C][C]45.1581[/C][C]44.9346[/C][C]44.9346[/C][C]44.9346[/C][C]44.9346[/C][C]45.8286[/C][C]44.9346[/C][/ROW]
[ROW][C]0.65[/C][C]45.9404[/C][C]47.0413[/C][C]46.0521[/C][C]46.0521[/C][C]46.5017[/C][C]46.0521[/C][C]46.8614[/C][C]47.8506[/C][/ROW]
[ROW][C]0.7[/C][C]47.9535[/C][C]48.3137[/C][C]48.3652[/C][C]48.3652[/C][C]48.1079[/C][C]47.8506[/C][C]47.9021[/C][C]48.3652[/C][/ROW]
[ROW][C]0.75[/C][C]48.4906[/C][C]48.746[/C][C]48.6159[/C][C]48.6159[/C][C]48.5532[/C][C]48.6159[/C][C]49.006[/C][C]48.6159[/C][/ROW]
[ROW][C]0.8[/C][C]49.0321[/C][C]50.2464[/C][C]49.1361[/C][C]49.1361[/C][C]49.1361[/C][C]49.1361[/C][C]49.8763[/C][C]50.9866[/C][/ROW]
[ROW][C]0.85[/C][C]51.0794[/C][C]51.8686[/C][C]51.915[/C][C]51.915[/C][C]51.2187[/C][C]50.9866[/C][C]51.033[/C][C]51.915[/C][/ROW]
[ROW][C]0.9[/C][C]54.3797[/C][C]58.4054[/C][C]58.0767[/C][C]58.0767[/C][C]54.9958[/C][C]51.915[/C][C]58.8437[/C][C]58.0767[/C][/ROW]
[ROW][C]0.95[/C][C]58.8437[/C][C]60.9636[/C][C]59.1724[/C][C]59.1724[/C][C]58.8985[/C][C]59.1724[/C][C]60.1369[/C][C]61.9281[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=319076&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=319076&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 22.9067 23.1138 25.8057 25.8057 27.7561 21.6643 24.3562 21.6643 0.1 30.4867 31.2669 33.6074 33.6074 35.5292 33.6074 28.1462 33.6074 0.15 37.0667 37.4648 37.4511 37.4511 37.6566 37.4511 37.7114 37.4511 0.2 37.7959 37.8668 38.0793 38.0793 38.0793 37.7251 37.9376 37.7251 0.25 38.8538 39.241 39.6282 39.6282 39.635 39.6282 38.4665 39.6282 0.3 39.6499 39.8062 39.6553 39.6553 40.41 39.6553 41.0138 39.6553 0.35 41.2438 41.5201 41.9543 41.9543 41.7569 41.1648 41.599 41.1648 0.4 41.9832 42.0121 42.0265 42.0265 42.0265 41.9543 41.9687 42.0265 0.45 43.1456 43.6357 43.6252 43.6252 43.6427 43.6252 43.6847 43.6252 0.5 43.6952 43.7065 43.6952 43.7065 43.7065 43.6952 43.7065 43.7065 0.55 43.7591 43.8348 43.8555 43.8555 43.8211 43.7178 43.7385 43.8555 0.6 44.503 45.1581 44.9346 44.9346 44.9346 44.9346 45.8286 44.9346 0.65 45.9404 47.0413 46.0521 46.0521 46.5017 46.0521 46.8614 47.8506 0.7 47.9535 48.3137 48.3652 48.3652 48.1079 47.8506 47.9021 48.3652 0.75 48.4906 48.746 48.6159 48.6159 48.5532 48.6159 49.006 48.6159 0.8 49.0321 50.2464 49.1361 49.1361 49.1361 49.1361 49.8763 50.9866 0.85 51.0794 51.8686 51.915 51.915 51.2187 50.9866 51.033 51.915 0.9 54.3797 58.4054 58.0767 58.0767 54.9958 51.915 58.8437 58.0767 0.95 58.8437 60.9636 59.1724 59.1724 58.8985 59.1724 60.1369 61.9281

x <-sort(x[!is.na(x)])q1 <- function(data,n,p,i,f) {np <- n*p;i <<- floor(np)f <<- np - iqvalue <- (1-f)*data[i] + f*data[i+1]}q2 <- function(data,n,p,i,f) {np <- (n+1)*pi <<- floor(np)f <<- np - iqvalue <- (1-f)*data[i] + f*data[i+1]}q3 <- function(data,n,p,i,f) {np <- n*pi <<- floor(np)f <<- np - iif (f==0) {qvalue <- data[i]} else {qvalue <- data[i+1]}}q4 <- function(data,n,p,i,f) {np <- n*pi <<- floor(np)f <<- np - iif (f==0) {qvalue <- (data[i]+data[i+1])/2} else {qvalue <- data[i+1]}}q5 <- function(data,n,p,i,f) {np <- (n-1)*pi <<- floor(np)f <<- np - iif (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+0.5i <<- floor(np)f <<- np - iqvalue <- data[i]}q7 <- function(data,n,p,i,f) {np <- (n+1)*pi <<- floor(np)f <<- np - iif (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)*pi <<- floor(np)f <<- np - iif (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 <- 25mystart <- 25if (lx>10){mystep=10mystart=10}if (lx>20){mystep=5mystart=5}if (lx>50){mystep=2mystart=2}if (lx>=100){mystep=1mystart=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')