Home » date » 2009 » Dec » 29 »

2

*The author of this computation has been verified*

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

Title produced by software: Central Tendency

Date of computation: Tue, 29 Dec 2009 10:08:39 -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/29/t12621065492ii9pu7jo5wx24d.htm/, Retrieved Tue, 29 Dec 2009 18:09:11 +0100

BibTeX entries for LaTeX users:

@Manual{KEY,
    author = {{YOUR NAME}},
    publisher = {Office for Research Development and Education},
    title = {Statistical Computations at FreeStatistics.org, URL http://www.freestatistics.org/blog/date/2009/Dec/29/t12621065492ii9pu7jo5wx24d.htm/},
    year = {2009},
}
@Manual{R,
    title = {R: A Language and Environment for Statistical Computing},
    author = {{R Development Core Team}},
    organization = {R Foundation for Statistical Computing},
    address = {Vienna, Austria},
    year = {2009},
    note = {{ISBN} 3-900051-07-0},
    url = {http://www.R-project.org},
}

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords:

Dataseries X:

» Textbox « » Textfile « » CSV «

262.262 261.631 258.953 259.966 262.850 262.204 263.418 262.752 266.433 267.722 266.003 262.971 265.521 264.676 270.223 269.508 268.457 265.814 266.680 263.018 269.285 269.829 270.911 266.844 271.244 269.907 271.296 270.157 271.322 267.179 264.101 265.518 269.419 268.714 272.482 268.351 268.175 270.674 272.764 272.599 270.333 270.846 270.491 269.160 274.027 273.784 276.663 274.525 271.344 271.115 270.798 273.911 273.985 271.917 273.338 270.601 273.547 275.363 281.229 277.793 279.913 282.500 280.041 282.166 290.304 283.519 287.816 285.226 287.595 289.741 289.148 288.301 290.155 289.648 288.225 289.351 294.735 305.333 309.030 310.215 321.935 325.734 320.846 323.023 319.753 321.753 320.757 324.479 324.641 322.767

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	3 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

Central Tendency - Ungrouped Data
Measure	Value	S.E.	Value/S.E.
Arithmetic Mean	279.725033333333	1.93399938871967	144.635533477865
Geometric Mean	279.162328410012
Harmonic Mean	278.630651557574
Quadratic Mean	280.31943519296
Winsorized Mean ( 1 / 30 )	279.724144444444	1.92946124022830	144.975259731751
Winsorized Mean ( 2 / 30 )	279.757544444444	1.92443369429440	145.371360558628
Winsorized Mean ( 3 / 30 )	279.728111111111	1.90992074306896	146.460585930717
Winsorized Mean ( 4 / 30 )	279.719311111111	1.90676322538065	146.698503195262
Winsorized Mean ( 5 / 30 )	279.700311111111	1.89233479020319	147.806990897778
Winsorized Mean ( 6 / 30 )	279.694711111111	1.88863936340553	148.093233960122
Winsorized Mean ( 7 / 30 )	279.633577777778	1.87013696708286	149.525720682355
Winsorized Mean ( 8 / 30 )	279.629844444444	1.86776102771660	149.713930366296
Winsorized Mean ( 9 / 30 )	279.569444444444	1.83904333609563	152.01895407097
Winsorized Mean ( 10 / 30 )	278.585555555556	1.58140316493461	176.163524730947
Winsorized Mean ( 11 / 30 )	278.511	1.54186156103855	180.632948532943
Winsorized Mean ( 12 / 30 )	278.130333333333	1.42277191087048	195.484835769049
Winsorized Mean ( 13 / 30 )	276.599944444444	1.11550186780164	247.960090815043
Winsorized Mean ( 14 / 30 )	275.956255555556	0.990914494782629	278.486445610113
Winsorized Mean ( 15 / 30 )	275.962922222222	0.9832768489113	280.656381290552
Winsorized Mean ( 16 / 30 )	275.965766666667	0.96278894575598	286.631631868165
Winsorized Mean ( 17 / 30 )	275.994855555556	0.954813328758198	289.056349804528
Winsorized Mean ( 18 / 30 )	275.968255555556	0.941715868862893	293.048322408311
Winsorized Mean ( 19 / 30 )	275.996122222222	0.927251290919192	297.649757865125
Winsorized Mean ( 20 / 30 )	275.928566666667	0.884722496827118	311.88148561411
Winsorized Mean ( 21 / 30 )	276.016533333333	0.87107792783112	316.867784746402
Winsorized Mean ( 22 / 30 )	275.959577777778	0.851043504138902	324.260248078619
Winsorized Mean ( 23 / 30 )	275.930188888889	0.839498939628019	328.684380484332
Winsorized Mean ( 24 / 30 )	275.366988888889	0.735596324544079	374.345248475189
Winsorized Mean ( 25 / 30 )	275.016711111111	0.652582979688703	421.427955786252
Winsorized Mean ( 26 / 30 )	274.758444444444	0.606249968863375	453.209828545763
Winsorized Mean ( 27 / 30 )	274.698444444444	0.587842695994206	467.299238922843
Winsorized Mean ( 28 / 30 )	274.434622222222	0.543755640107997	504.70211613385
Winsorized Mean ( 29 / 30 )	274.155255555556	0.47997706732596	571.18407152851
Winsorized Mean ( 30 / 30 )	274.138588888889	0.471474340136188	581.449647524195
Trimmed Mean ( 1 / 30 )	279.43825	1.89195806426595	147.697908995894
Trimmed Mean ( 2 / 30 )	279.139058139535	1.84837478887583	151.018646120631
Trimmed Mean ( 3 / 30 )	278.807726190476	1.80054946363963	154.845913328532
Trimmed Mean ( 4 / 30 )	278.471	1.75094509301674	159.040395447362
Trimmed Mean ( 5 / 30 )	278.1199125	1.69363912446603	164.214388108024
Trimmed Mean ( 6 / 30 )	277.755205128205	1.63024116718656	170.376758186980
Trimmed Mean ( 7 / 30 )	277.372407894737	1.55557605059513	178.308484364118
Trimmed Mean ( 8 / 30 )	276.979540540541	1.47069238520089	188.332749477523
Trimmed Mean ( 9 / 30 )	276.565430555556	1.36755118002180	202.234062312130
Trimmed Mean ( 10 / 30 )	276.136285714286	1.24690345004084	221.457632269155
Trimmed Mean ( 11 / 30 )	275.812117647059	1.1661920565992	236.506599480167
Trimmed Mean ( 12 / 30 )	275.477545454545	1.07540300445749	256.162149736151
Trimmed Mean ( 13 / 30 )	275.477545454545	0.991609546437836	277.808484644127
Trimmed Mean ( 14 / 30 )	275.006629032258	0.960218324766995	286.400104995904
Trimmed Mean ( 15 / 30 )	274.904883333333	0.945990888470253	290.599927212700
Trimmed Mean ( 16 / 30 )	274.795431034483	0.9293619379354	295.681821922842
Trimmed Mean ( 17 / 30 )	274.677875	0.911927284802828	301.205896103207
Trimmed Mean ( 18 / 30 )	274.548759259259	0.891059748359716	308.114870820565
Trimmed Mean ( 19 / 30 )	274.412269230769	0.866885727383034	316.549529612362
Trimmed Mean ( 20 / 30 )	274.26222	0.838454868652659	327.104332330637
Trimmed Mean ( 21 / 30 )	274.106	0.810320410426142	338.268660733659
Trimmed Mean ( 22 / 30 )	273.928	0.775641375869901	353.163212435364
Trimmed Mean ( 23 / 30 )	273.739113636364	0.734171646531469	372.854379394275
Trimmed Mean ( 24 / 30 )	273.534976190476	0.680816706115879	401.774770996761
Trimmed Mean ( 25 / 30 )	273.363225	0.639042162333898	427.77024915168
Trimmed Mean ( 26 / 30 )	273.363225	0.605408007715412	451.535528959342
Trimmed Mean ( 27 / 30 )	273.057361111111	0.572364547160006	477.068963243765
Trimmed Mean ( 28 / 30 )	272.896470588235	0.530439220748082	514.472648163851
Trimmed Mean ( 29 / 30 )	272.74196875	0.485698433926339	561.545909351983
Trimmed Mean ( 30 / 30 )	272.595766666667	0.444135799578725	613.766705870662
Median	271.6305
Midrange	292.3435
Midmean - Weighted Average at Xnp	273.619377777778
Midmean - Weighted Average at X(n+1)p	273.928
Midmean - Empirical Distribution Function	273.928
Midmean - Empirical Distribution Function - Averaging	273.928
Midmean - Empirical Distribution Function - Interpolation	273.739113636364
Midmean - Closest Observation	273.928
Midmean - True Basic - Statistics Graphics Toolkit	273.928
Midmean - MS Excel (old versions)	273.928
Number of observations	90

Charts produced by software:

http://www.freestatistics.org/blog/date/2009/Dec/29/t12621065492ii9pu7jo5wx24d/1d0141262106516.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/29/t12621065492ii9pu7jo5wx24d/1d0141262106516.ps (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/29/t12621065492ii9pu7jo5wx24d/2av9a1262106516.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/29/t12621065492ii9pu7jo5wx24d/2av9a1262106516.ps (open in new window)

Parameters (Session):

Parameters (R input):

R code (references can be found in the software module):

geomean <- function(x) {

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')

This work is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 3.0 License.

Software written by Ed van Stee & Patrick Wessa

Disclaimer

Information provided on this web site is provided "AS IS" without warranty of any kind, either express or implied, including, without limitation, warranties of merchantability, fitness for a particular purpose, and noninfringement. We use reasonable efforts to include accurate and timely information and periodically update the information, and software without notice. However, we make no warranties or representations as to the accuracy or completeness of such information (or software), and we assume no liability or responsibility for errors or omissions in the content of this web site, or any software bugs in online applications. Your use of this web site is AT YOUR OWN RISK. Under no circumstances and under no legal theory shall we be liable to you or any other person for any direct, indirect, special, incidental, exemplary, or consequential damages arising from your access to, or use of, this web site.

We may request personal information to be submitted to our servers in order to be able to:

personalize online software applications according to your needs
enforce strict security rules with respect to the data that you upload (e.g. statistical data)
manage user sessions of online applications
alert you about important changes or upgrades in resources or applications

We NEVER allow other companies to directly offer registered users information about their products and services. Banner references and hyperlinks of third parties NEVER contain any personal data of the visitor.

We do NOT sell, nor transmit by any means, personal information, nor statistical data series uploaded by you to third parties.

We carefully protect your data from loss, misuse, alteration, and destruction. However, at any time, and under any circumstance you are solely responsible for managing your passwords, and keeping them secret.

We store a unique ANONYMOUS USER ID in the form of a small 'Cookie' on your computer. This allows us to track your progress when using this website which is necessary to create state-dependent features. The cookie is used for NO OTHER PURPOSE. At any time you may opt to disallow cookies from this website - this will not affect other features of this website.

We examine cookies that are used by third-parties (banner and online ads) very closely: abuse from third-parties automatically results in termination of the advertising contract without refund. We have very good reason to believe that the cookies that are produced by third parties (banner ads) do NOT cause any privacy or security risk.

FreeStatistics.org is safe. There is no need to download any software to use the applications and services contained in this website. Hence, your system's security is not compromised by their use, and your personal data - other than data you submit in the account application form, and the user-agent information that is transmitted by your browser - is never transmitted to our servers.

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.

FreeStatistics.org is powered by