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Percentiles index bl en pl Noorwegen

*Unverified author*

R Software Module: /rwasp_percentiles.wasp (opens new window with default values)

Title produced by software: Percentiles

Date of computation: Thu, 03 Dec 2009 07:23:12 -0700

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2009/Dec/03/t12598503103uqn713h44jzasi.htm/, Retrieved Tue, 21 May 2013 10:34:08 +0000

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords:

KDGP1W42

System-generated keywords (parent):

t1256118172dr4b9wtnrzis235 (pk = 49309)

Estimated Impact

Dataseries X:

» Textfile « » CSV « » Stem and Leaf « » Histogram « » Kernel Density « » Harrell-Davis Quantiles « » Central Tendency « » Variability «

Output produced by software:

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	'Gwilym Jenkins' @ 72.249.127.135

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)
0.01	75.98	75.99	76.9	76.9	76.97	75.9	76.81	75.9
0.02	77.06	77.08	77.9	77.9	78.04	76.9	77.72	76.9
0.03	78.14	78.17	78.9	78.9	79.11	77.9	78.63	77.9
0.04	79.22	79.26	79.9	79.9	80.18	78.9	79.54	78.9
0.05	80.3	80.35	80.9	80.9	81.25	79.9	80.45	79.9
0.06	81.38	81.44	81.9	81.9	82.32	80.9	81.36	81.9
0.07	82.46	82.53	82.9	82.9	83.39	82.9	82.27	82.9
0.08	83.54	83.62	83.9	83.9	84.46	83.9	83.18	83.9
0.09	84.62	84.71	84.9	84.9	85.53	84.9	84.09	84.9
0.1	85.7	85.8	85.9	85.9	86.6	85.9	85	85.9
0.11	86.78	86.89	86.9	86.9	87.67	86.9	85.91	86.9
0.12	87.86	87.98	87.9	87.9	88.74	87.9	88.82	87.9
0.13	88.94	89.07	89.9	89.9	89.81	88.9	89.73	88.9
0.14	90.02	90.16	90.9	90.9	90.88	89.9	90.64	89.9
0.15	91.1	91.25	91.9	91.9	91.95	90.9	91.55	90.9
0.16	92.18	92.34	92.9	92.9	93.02	91.9	92.46	91.9
0.17	93.26	93.43	93.9	93.9	94.09	92.9	93.37	93.9
0.18	94.34	94.52	94.9	94.9	95.16	93.9	94.28	94.9
0.19	95.42	95.61	95.9	95.9	96.23	95.9	95.19	95.9
0.2	96.5	96.7	96.9	96.9	97.3	96.9	96.1	96.9
0.21	97.58	97.79	97.9	97.9	98.37	97.9	97.01	97.9
0.22	98.66	98.88	98.9	98.9	99.44	98.9	97.92	98.9
0.23	99.74	99.97	99.9	99.9	100.51	99.9	100.83	99.9
0.24	100.82	101.06	100.9	100.9	101.58	100.9	101.74	100.9
0.25	101.9	102.15	101.9	102.4	102.65	101.9	102.65	101.9
0.26	102.98	103.24	103.9	103.9	103.72	102.9	103.56	102.9
0.27	104.06	104.33	104.9	104.9	104.79	103.9	104.47	103.9
0.28	105.14	105.42	105.9	105.9	105.86	104.9	105.38	105.9
0.29	106.22	106.51	106.9	106.9	106.93	105.9	106.29	106.9
0.3	107.3	107.6	107.9	107.9	108	106.9	107.2	107.9
0.31	108.38	108.69	108.9	108.9	109.07	107.9	108.11	108.9
0.32	109.46	109.78	109.9	109.9	110.14	109.9	109.02	109.9
0.33	110.54	110.87	110.9	110.9	111.21	110.9	109.93	110.9
0.34	111.62	111.96	111.9	111.9	112.28	111.9	112.84	111.9
0.35	112.7	113.05	112.9	112.9	113.35	112.9	113.75	112.9
0.36	113.78	114.14	113.9	113.9	114.42	113.9	114.66	113.9
0.37	114.86	115.23	114.9	114.9	115.49	114.9	115.57	114.9
0.38	115.94	116.32	116.9	116.9	116.56	115.9	116.48	115.9
0.39	117.02	117.41	117.9	117.9	117.63	116.9	117.39	117.9
0.4	118.1	118.5	118.9	118.9	118.7	117.9	118.3	118.9
0.41	119.18	119.59	119.9	119.9	119.77	118.9	119.21	119.9
0.42	120.26	120.68	120.9	120.9	120.84	119.9	120.12	120.9
0.43	121.34	121.77	121.9	121.9	121.91	120.9	121.03	121.9
0.44	122.42	122.86	122.9	122.9	122.98	122.9	121.94	122.9
0.45	123.5	123.95	123.9	123.9	124.05	123.9	124.85	123.9
0.46	124.58	125.04	124.9	124.9	125.12	124.9	125.76	124.9
0.47	125.66	126.13	125.9	125.9	126.19	125.9	126.67	125.9
0.48	126.74	127.22	126.9	126.9	127.26	126.9	127.58	126.9
0.49	127.82	128.31	127.9	127.9	128.33	127.9	128.49	127.9
0.5	128.9	129.4	128.9	129.4	129.4	128.9	129.4	129.4
0.51	129.98	130.49	130.9	130.9	130.47	129.9	130.31	130.9
0.52	131.06	131.58	131.9	131.9	131.54	130.9	131.22	131.9
0.53	132.14	132.67	132.9	132.9	132.61	131.9	132.13	132.9
0.54	133.22	133.76	133.9	133.9	133.68	132.9	133.04	133.9
0.55	134.3	134.85	134.9	134.9	134.75	133.9	133.95	134.9
0.56	135.38	135.94	135.9	135.9	135.82	134.9	136.86	135.9
0.57	136.46	137.03	136.9	136.9	136.89	136.9	137.77	136.9
0.58	137.54	138.12	137.9	137.9	137.96	137.9	138.68	137.9
0.59	138.62	139.21	138.9	138.9	139.03	138.9	139.59	138.9
0.6	139.7	140.3	139.9	139.9	140.1	139.9	140.5	139.9
0.61	140.78	141.39	140.9	140.9	141.17	140.9	141.41	140.9
0.62	141.86	142.48	141.9	141.9	142.24	141.9	142.32	142.9
0.63	142.94	143.57	143.9	143.9	143.31	142.9	143.23	143.9
0.64	144.02	144.66	144.9	144.9	144.38	143.9	144.14	144.9
0.65	145.1	145.75	145.9	145.9	145.45	144.9	145.05	145.9
0.66	146.18	146.84	146.9	146.9	146.52	145.9	145.96	146.9
0.67	147.26	147.93	147.9	147.9	147.59	146.9	148.87	147.9
0.68	148.34	149.02	148.9	148.9	148.66	147.9	149.78	148.9
0.69	149.42	150.11	149.9	149.9	149.73	149.9	150.69	149.9
0.7	150.5	151.2	150.9	150.9	150.8	150.9	151.6	150.9
0.71	151.58	152.29	151.9	151.9	151.87	151.9	152.51	151.9
0.72	152.66	153.38	152.9	152.9	152.94	152.9	153.42	152.9
0.73	153.74	154.47	153.9	153.9	154.01	153.9	154.33	154.9
0.74	154.82	155.56	154.9	154.9	155.08	154.9	155.24	155.9
0.75	155.9	156.65	155.9	156.4	156.15	155.9	156.15	156.9
0.76	156.98	157.74	157.9	157.9	157.22	156.9	157.06	157.9
0.77	158.06	158.83	158.9	158.9	158.29	157.9	157.97	158.9
0.78	159.14	159.92	159.9	159.9	159.36	158.9	160.88	159.9
0.79	160.22	161.01	160.9	160.9	160.43	159.9	161.79	160.9
0.8	161.3	162.1	161.9	161.9	161.5	160.9	162.7	161.9
0.81	162.38	163.19	162.9	162.9	162.57	161.9	163.61	162.9
0.82	163.46	164.28	163.9	163.9	163.64	163.9	164.52	163.9
0.83	164.54	165.37	164.9	164.9	164.71	164.9	165.43	164.9
0.84	165.62	166.46	165.9	165.9	165.78	165.9	166.34	166.9
0.85	166.7	167.55	166.9	166.9	166.85	166.9	167.25	167.9
0.86	167.78	168.64	167.9	167.9	167.92	167.9	168.16	168.9
0.87	168.86	169.73	168.9	168.9	168.99	168.9	169.07	169.9
0.88	169.94	170.82	170.9	170.9	170.06	169.9	169.98	170.9
0.89	171.02	171.91	171.9	171.9	171.13	170.9	172.89	171.9
0.9	172.1	173	172.9	172.9	172.2	171.9	173.8	172.9
0.91	173.18	174.09	173.9	173.9	173.27	172.9	174.71	173.9
0.92	174.26	175.18	174.9	174.9	174.34	173.9	175.62	174.9
0.93	175.34	176.27	175.9	175.9	175.41	174.9	176.53	175.9
0.94	176.42	177.36	176.9	176.9	176.48	176.9	177.44	176.9
0.95	177.5	178.45	177.9	177.9	177.55	177.9	178.35	178.9
0.96	178.58	179.54	178.9	178.9	178.62	178.9	179.26	179.9
0.97	179.66	180.63	179.9	179.9	179.69	179.9	180.17	180.9
0.98	180.74	181.72	180.9	180.9	180.76	180.9	181.08	181.9
0.99	181.82	182.81	181.9	181.9	181.83	181.9	181.99	182.9

Charts produced by software:

http://www.freestatistics.org/blog/date/2009/Dec/03/t12598503103uqn713h44jzasi/1l20x1259850191.png (opens in new window)

http://www.freestatistics.org/blog/date/2009/Dec/03/t12598503103uqn713h44jzasi/1l20x1259850191.ps (opens in new window)

Click here to open pdf file.

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,hyperlink('http://www.xycoon.com/method_1.htm', 'Weighted Average at Xnp',''),1,TRUE)
a<-table.element(a,hyperlink('http://www.xycoon.com/method_2.htm','Weighted Average at X(n+1)p',''),1,TRUE)
a<-table.element(a,hyperlink('http://www.xycoon.com/method_3.htm','Empirical Distribution Function',''),1,TRUE)
a<-table.element(a,hyperlink('http://www.xycoon.com/method_4.htm','Empirical Distribution Function - Averaging',''),1,TRUE)
a<-table.element(a,hyperlink('http://www.xycoon.com/method_5.htm','Empirical Distribution Function - Interpolation',''),1,TRUE)
a<-table.element(a,hyperlink('http://www.xycoon.com/method_6.htm','Closest Observation',''),1,TRUE)
a<-table.element(a,hyperlink('http://www.xycoon.com/method_7.htm','True Basic - Statistics Graphics Toolkit',''),1,TRUE)
a<-table.element(a,hyperlink('http://www.xycoon.com/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')