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Author's title
Author*Unverified author*
R Software Modulerwasp_percentiles.wasp
Title produced by softwarePercentiles
Date of computationTue, 23 Mar 2010 05:34:37 -0600
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Mar/23/t1269344183w1lxzu28sizwsnj.htm/, Retrieved Fri, 27 May 2022 02:18:17 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=74568, Retrieved Fri, 27 May 2022 02:18:17 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact181
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Percentiles] [Percentile of dep...] [2010-03-23 11:34:37] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataseries X:
226175
237059
220113
268518
303609

 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 'RServer@AstonUniversity' @ vre.aston.ac.uk

\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 & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=74568&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]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=74568&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=74568&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 'RServer@AstonUniversity' @ vre.aston.ac.uk

 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) 0.25 221628.5 223144 226175 226175 226175 220113 223144 223144 0.5 231617 237059 237059 237059 237059 237059 237059 237059 0.75 260653.25 286063.5 268518 268518 268518 268518 286063.5 286063.5

\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
0.25 & 221628.5 & 223144 & 226175 & 226175 & 226175 & 220113 & 223144 & 223144 \tabularnewline
0.5 & 231617 & 237059 & 237059 & 237059 & 237059 & 237059 & 237059 & 237059 \tabularnewline
0.75 & 260653.25 & 286063.5 & 268518 & 268518 & 268518 & 268518 & 286063.5 & 286063.5 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=74568&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]0.25[/C][C]221628.5[/C][C]223144[/C][C]226175[/C][C]226175[/C][C]226175[/C][C]220113[/C][C]223144[/C][C]223144[/C][/ROW]
[ROW][C]0.5[/C][C]231617[/C][C]237059[/C][C]237059[/C][C]237059[/C][C]237059[/C][C]237059[/C][C]237059[/C][C]237059[/C][/ROW]
[ROW][C]0.75[/C][C]260653.25[/C][C]286063.5[/C][C]268518[/C][C]268518[/C][C]268518[/C][C]268518[/C][C]286063.5[/C][C]286063.5[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=74568&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=74568&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) 0.25 221628.5 223144 226175 226175 226175 220113 223144 223144 0.5 231617 237059 237059 237059 237059 237059 237059 237059 0.75 260653.25 286063.5 268518 268518 268518 268518 286063.5 286063.5

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,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')