ws2Q9METAALVERWERKEND
| Summary of compuational 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 |
| Central Tendency - Ungrouped Data | |||
| Measure | Value | S.E. | Value/S.E. |
| Arithmetic Mean | 10251 | 256.826587274648 | 39.9140918733529 |
| Geometric Mean | 10001.7634921678 | ||
| Harmonic Mean | 9737.02969565045 | ||
| Quadratic Mean | 10476.9343613058 | ||
| Winsorized Mean ( 1 / 24 ) | 10254.1805555556 | 256.123830977053 | 40.0360267782902 |
| Winsorized Mean ( 2 / 24 ) | 10253.2638888889 | 255.69273636074 | 40.099941964809 |
| Winsorized Mean ( 3 / 24 ) | 10254.0972222222 | 255.493600916809 | 40.1344581055126 |
| Winsorized Mean ( 4 / 24 ) | 10254.6527777778 | 255.10257085873 | 40.1981553665195 |
| Winsorized Mean ( 5 / 24 ) | 10257.2916666667 | 253.922036077824 | 40.3954372180717 |
| Winsorized Mean ( 6 / 24 ) | 10252.7083333333 | 253.224936994299 | 40.4885413539037 |
| Winsorized Mean ( 7 / 24 ) | 10253.2916666667 | 253.11644907213 | 40.5081997011771 |
| Winsorized Mean ( 8 / 24 ) | 10259.5138888889 | 250.516607073899 | 40.9534282326539 |
| Winsorized Mean ( 9 / 24 ) | 10265.3888888889 | 249.10220683593 | 41.2095461508703 |
| Winsorized Mean ( 10 / 24 ) | 10273.8611111111 | 247.026933888465 | 41.5900442489799 |
| Winsorized Mean ( 11 / 24 ) | 10295.4027777778 | 241.388448122969 | 42.650768327294 |
| Winsorized Mean ( 12 / 24 ) | 10303.0694444444 | 235.924817875336 | 43.6709861100270 |
| Winsorized Mean ( 13 / 24 ) | 10312.0972222222 | 234.183432276801 | 44.034273142062 |
| Winsorized Mean ( 14 / 24 ) | 10316.375 | 232.274725060639 | 44.4145397107101 |
| Winsorized Mean ( 15 / 24 ) | 10323.25 | 230.399778222906 | 44.8058156983663 |
| Winsorized Mean ( 16 / 24 ) | 10335.0277777778 | 227.864693306107 | 45.3559857291889 |
| Winsorized Mean ( 17 / 24 ) | 10330.3055555556 | 224.173741653967 | 46.0816930624343 |
| Winsorized Mean ( 18 / 24 ) | 10435.8055555556 | 207.014927526151 | 50.4108842790443 |
| Winsorized Mean ( 19 / 24 ) | 10471.6944444444 | 199.365639741216 | 52.5250713113708 |
| Winsorized Mean ( 20 / 24 ) | 10489.75 | 195.440465731997 | 53.6723547025535 |
| Winsorized Mean ( 21 / 24 ) | 10510.4583333333 | 188.199109735209 | 55.8475454433407 |
| Winsorized Mean ( 22 / 24 ) | 10523.5972222222 | 185.131790873601 | 56.8438147363207 |
| Winsorized Mean ( 23 / 24 ) | 10665.4305555556 | 161.341129368719 | 66.1048462799677 |
| Winsorized Mean ( 24 / 24 ) | 10824.4305555556 | 138.407504334197 | 78.2069628928432 |
| Trimmed Mean ( 1 / 24 ) | 10268.9 | 256.162935944201 | 40.0873762714714 |
| Trimmed Mean ( 2 / 24 ) | 10284.4852941176 | 255.968074526404 | 40.1787813310162 |
| Trimmed Mean ( 3 / 24 ) | 10301.5151515152 | 255.749249138090 | 40.2797473941084 |
| Trimmed Mean ( 4 / 24 ) | 10319.296875 | 255.313448886628 | 40.4181484367566 |
| Trimmed Mean ( 5 / 24 ) | 10338.0645161290 | 254.658505558291 | 40.5957951157561 |
| Trimmed Mean ( 6 / 24 ) | 10357.45 | 253.942029757583 | 40.7866709181122 |
| Trimmed Mean ( 7 / 24 ) | 10379.1206896552 | 252.954650280160 | 41.0315472680963 |
| Trimmed Mean ( 8 / 24 ) | 10402.2321428571 | 251.474182133905 | 41.3650103346122 |
| Trimmed Mean ( 9 / 24 ) | 10426.0185185185 | 249.952794272436 | 41.711950245912 |
| Trimmed Mean ( 10 / 24 ) | 10450.7307692308 | 248.062852559686 | 42.1293662529186 |
| Trimmed Mean ( 11 / 24 ) | 10476.2 | 245.829001460738 | 42.6158017880293 |
| Trimmed Mean ( 12 / 24 ) | 10500.8541666667 | 243.893455675346 | 43.0550878767517 |
| Trimmed Mean ( 13 / 24 ) | 10526.6521739130 | 242.174359707825 | 43.4672447843491 |
| Trimmed Mean ( 14 / 24 ) | 10553.6590909091 | 239.899886499505 | 43.9919303210294 |
| Trimmed Mean ( 15 / 24 ) | 10582.7142857143 | 236.899487857063 | 44.671748265237 |
| Trimmed Mean ( 16 / 24 ) | 10613.85 | 232.917338561482 | 45.5691708721732 |
| Trimmed Mean ( 17 / 24 ) | 10646.8684210526 | 227.766279758339 | 46.7447087968816 |
| Trimmed Mean ( 18 / 24 ) | 10684.1111111111 | 221.187835057503 | 48.3033395952067 |
| Trimmed Mean ( 19 / 24 ) | 10713.3235294118 | 216.565496963856 | 49.4692076051237 |
| Trimmed Mean ( 20 / 24 ) | 10741.9375 | 211.681783092799 | 50.7456869601805 |
| Trimmed Mean ( 21 / 24 ) | 10772.2 | 205.257513617777 | 52.4813918386424 |
| Trimmed Mean ( 22 / 24 ) | 10804.25 | 197.582791065914 | 54.6821407963392 |
| Trimmed Mean ( 23 / 24 ) | 10839.5769230769 | 186.468254036213 | 58.130950917639 |
| Trimmed Mean ( 24 / 24 ) | 10862.2916666667 | 179.019192550208 | 60.6766878563604 |
| Median | 11006 | ||
| Midrange | 9624.5 | ||
| Midmean - Weighted Average at Xnp | 10603.5135135135 | ||
| Midmean - Weighted Average at X(n+1)p | 10684.1111111111 | ||
| Midmean - Empirical Distribution Function | 10603.5135135135 | ||
| Midmean - Empirical Distribution Function - Averaging | 10684.1111111111 | ||
| Midmean - Empirical Distribution Function - Interpolation | 10684.1111111111 | ||
| Midmean - Closest Observation | 10603.5135135135 | ||
| Midmean - True Basic - Statistics Graphics Toolkit | 10684.1111111111 | ||
| Midmean - MS Excel (old versions) | 10646.8684210526 | ||
| Number of observations | 72 | ||
 |
| http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Oct/22/0ag1l5h2fpce0pe1193070060/1f0lm1193070342.png (open in new window) |
| http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Oct/22/0ag1l5h2fpce0pe1193070060/1f0lm1193070342.ps (open in new window) |
 |
| http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Oct/22/0ag1l5h2fpce0pe1193070060/2l8n81193070342.png (open in new window) |
| http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Oct/22/0ag1l5h2fpce0pe1193070060/2l8n81193070342.ps (open in new window) |
return(exp(mean(log(x))))
}
harmean <- function(x) {
return(1/mean(1/x))
}
quamean <- function(x) {
return(sqrt(mean(x*x)))
}
winmean <- function(x) {
x <-sort(x[!is.na(x)])
n<-length(x)
denom <- 3
nodenom <- n/denom
if (nodenom>40) denom <- n/40
sqrtn = sqrt(n)
roundnodenom = floor(nodenom)
win <- array(NA,dim=c(roundnodenom,2))
for (j in 1:roundnodenom) {
win[j,1] <- (j*x[j+1]+sum(x[(j+1):(n-j)])+j*x[n-j])/n
win[j,2] <- sd(c(rep(x[j+1],j),x[(j+1):(n-j)],rep(x[n-j],j)))/sqrtn
}
return(win)
}
trimean <- function(x) {
x <-sort(x[!is.na(x)])
n<-length(x)
denom <- 3
nodenom <- n/denom
if (nodenom>40) denom <- n/40
sqrtn = sqrt(n)
roundnodenom = floor(nodenom)
tri <- array(NA,dim=c(roundnodenom,2))
for (j in 1:roundnodenom) {
tri[j,1] <- mean(x,trim=j/n)
tri[j,2] <- sd(x[(j+1):(n-j)]) / sqrt(n-j*2)
}
return(tri)
}
midrange <- function(x) {
return((max(x)+min(x))/2)
}
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]
}
}
}
}
midmean <- function(x,def) {
x <-sort(x[!is.na(x)])
n<-length(x)
if (def==1) {
qvalue1 <- q1(x,n,0.25,i,f)
qvalue3 <- q1(x,n,0.75,i,f)
}
if (def==2) {
qvalue1 <- q2(x,n,0.25,i,f)
qvalue3 <- q2(x,n,0.75,i,f)
}
if (def==3) {
qvalue1 <- q3(x,n,0.25,i,f)
qvalue3 <- q3(x,n,0.75,i,f)
}
if (def==4) {
qvalue1 <- q4(x,n,0.25,i,f)
qvalue3 <- q4(x,n,0.75,i,f)
}
if (def==5) {
qvalue1 <- q5(x,n,0.25,i,f)
qvalue3 <- q5(x,n,0.75,i,f)
}
if (def==6) {
qvalue1 <- q6(x,n,0.25,i,f)
qvalue3 <- q6(x,n,0.75,i,f)
}
if (def==7) {
qvalue1 <- q7(x,n,0.25,i,f)
qvalue3 <- q7(x,n,0.75,i,f)
}
if (def==8) {
qvalue1 <- q8(x,n,0.25,i,f)
qvalue3 <- q8(x,n,0.75,i,f)
}
midm <- 0
myn <- 0
roundno4 <- round(n/4)
round3no4 <- round(3*n/4)
for (i in 1:n) {
if ((x[i]>=qvalue1) & (x[i]<=qvalue3)){
midm = midm + x[i]
myn = myn + 1
}
}
midm = midm / myn
return(midm)
}
(arm <- mean(x))
sqrtn <- sqrt(length(x))
(armse <- sd(x) / sqrtn)
(armose <- arm / armse)
(geo <- geomean(x))
(har <- harmean(x))
(qua <- quamean(x))
(win <- winmean(x))
(tri <- trimean(x))
(midr <- midrange(x))
midm <- array(NA,dim=8)
for (j in 1:8) midm[j] <- midmean(x,j)
midm
bitmap(file='test1.png')
lb <- win[,1] - 2*win[,2]
ub <- win[,1] + 2*win[,2]
if ((ylimmin == '') | (ylimmax == '')) plot(win[,1],type='b',main=main, xlab='j', pch=19, ylab='Winsorized Mean(j/n)', ylim=c(min(lb),max(ub))) else plot(win[,1],type='l',main=main, xlab='j', pch=19, ylab='Winsorized Mean(j/n)', ylim=c(ylimmin,ylimmax))
lines(ub,lty=3)
lines(lb,lty=3)
grid()
dev.off()
bitmap(file='test2.png')
lb <- tri[,1] - 2*tri[,2]
ub <- tri[,1] + 2*tri[,2]
if ((ylimmin == '') | (ylimmax == '')) plot(tri[,1],type='b',main=main, xlab='j', pch=19, ylab='Trimmed Mean(j/n)', ylim=c(min(lb),max(ub))) else plot(tri[,1],type='l',main=main, xlab='j', pch=19, ylab='Trimmed Mean(j/n)', ylim=c(ylimmin,ylimmax))
lines(ub,lty=3)
lines(lb,lty=3)
grid()
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Central Tendency - Ungrouped Data',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Measure',header=TRUE)
a<-table.element(a,'Value',header=TRUE)
a<-table.element(a,'S.E.',header=TRUE)
a<-table.element(a,'Value/S.E.',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('http://www.xycoon.com/arithmetic_mean.htm', 'Arithmetic Mean', 'click to view the definition of the Arithmetic Mean'),header=TRUE)
a<-table.element(a,arm)
a<-table.element(a,hyperlink('http://www.xycoon.com/arithmetic_mean_standard_error.htm', armse, 'click to view the definition of the Standard Error of the Arithmetic Mean'))
a<-table.element(a,armose)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('http://www.xycoon.com/geometric_mean.htm', 'Geometric Mean', 'click to view the definition of the Geometric Mean'),header=TRUE)
a<-table.element(a,geo)
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('http://www.xycoon.com/harmonic_mean.htm', 'Harmonic Mean', 'click to view the definition of the Harmonic Mean'),header=TRUE)
a<-table.element(a,har)
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('http://www.xycoon.com/quadratic_mean.htm', 'Quadratic Mean', 'click to view the definition of the Quadratic Mean'),header=TRUE)
a<-table.element(a,qua)
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
for (j in 1:length(win[,1])) {
a<-table.row.start(a)
mylabel <- paste('Winsorized Mean (',j)
mylabel <- paste(mylabel,'/')
mylabel <- paste(mylabel,length(win[,1]))
mylabel <- paste(mylabel,')')
a<-table.element(a,hyperlink('http://www.xycoon.com/winsorized_mean.htm', mylabel, 'click to view the definition of the Winsorized Mean'),header=TRUE)
a<-table.element(a,win[j,1])
a<-table.element(a,win[j,2])
a<-table.element(a,win[j,1]/win[j,2])
a<-table.row.end(a)
}
for (j in 1:length(tri[,1])) {
a<-table.row.start(a)
mylabel <- paste('Trimmed Mean (',j)
mylabel <- paste(mylabel,'/')
mylabel <- paste(mylabel,length(tri[,1]))
mylabel <- paste(mylabel,')')
a<-table.element(a,hyperlink('http://www.xycoon.com/arithmetic_mean.htm', mylabel, 'click to view the definition of the Trimmed Mean'),header=TRUE)
a<-table.element(a,tri[j,1])
a<-table.element(a,tri[j,2])
a<-table.element(a,tri[j,1]/tri[j,2])
a<-table.row.end(a)
}
a<-table.row.start(a)
a<-table.element(a,hyperlink('http://www.xycoon.com/median_1.htm', 'Median', 'click to view the definition of the Median'),header=TRUE)
a<-table.element(a,median(x))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('http://www.xycoon.com/midrange.htm', 'Midrange', 'click to view the definition of the Midrange'),header=TRUE)
a<-table.element(a,midr)
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/method_1.htm','Weighted Average at Xnp',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[1])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/method_2.htm','Weighted Average at X(n+1)p',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[2])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/method_3.htm','Empirical Distribution Function',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[3])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/method_4.htm','Empirical Distribution Function - Averaging',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[4])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/method_5.htm','Empirical Distribution Function - Interpolation',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[5])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/method_6.htm','Closest Observation',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[6])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/method_7.htm','True Basic - Statistics Graphics Toolkit',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[7])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/method_8.htm','MS Excel (old versions)',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[8])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Number of observations',header=TRUE)
a<-table.element(a,length(x))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')
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As a general rule, we do not log on-line behavior of individuals (other than normal logging of webserver 'hits'). However, in cases of abuse, hacking, unauthorized access, Denial of Service attacks, illegal copying, hotlinking, non-compliance with international webstandards (such as robots.txt), or any other harmful behavior, our system engineers are empowered to log, track, identify, publish, and ban misbehaving individuals - even if this leads to ban entire blocks of IP addresses, or disclosing user's identity.