Home » date » 2009 » Oct » 21 »

workshop 3 deel 2.2 central tendency

*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: Wed, 21 Oct 2009 09:15:54 -0600

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2009/Oct/21/t12561382230fl4aj89cnyess5.htm/, Retrieved Wed, 21 Oct 2009 17:17:03 +0200

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/Oct/21/t12561382230fl4aj89cnyess5.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:

workshop 3 deel 2.2 central tendency

Dataseries X:

» Textbox « » Textfile « » CSV «

-0.9136 -0.90493 -0.88768 -0.86839 -0.85537 -0.84792 -0.85478 -0.85791 -0.8659 -0.85207 -0.85173 -0.82897 -0.82805 -0.8237 -0.82727 -0.83431 -0.83506 -0.83021 -0.82573 -0.80499 -0.79763 -0.78695 -0.80738 -0.80228 -0.83886 -0.84715 -0.84081 -0.85047 -0.85087 -0.86622 -0.85244 -0.87355 -0.8965 -0.89576 -0.88938 -0.86843 -0.85492 -0.86124 -0.86928 -0.8618 -0.85116 -0.82298 -0.8414 -0.84823 -0.86042 -0.85707 -0.86457 -0.86081 -0.87015 -0.87024 -0.86753 -0.872 -0.86763 -0.86557 -0.86868 -0.86342 -0.87503 -0.87975 -0.88017 -0.8731 -0.87344 -0.88088 -0.90081 -0.90899 -0.91726 -0.91823 -0.92404 -0.95209 -0.9532 -0.93219 -0.95816 -0.96924 -0.97868 -0.9823 -0.96064 -0.95863 -0.97446 -0.93954 -0.93856 -0.87305

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	2 seconds
R Server	'Sir Ronald Aylmer Fisher' @ 193.190.124.24

Central Tendency - Ungrouped Data
Measure	Value	S.E.	Value/S.E.
Arithmetic Mean	-0.874559875	0.00500173755092	-174.851212422998
Geometric Mean	NaN
Harmonic Mean	-0.872367845787753
Quadratic Mean	0.875689070311917
Winsorized Mean ( 1 / 26 )	-0.874648125	0.00496164068252231	-176.28203672245
Winsorized Mean ( 2 / 26 )	-0.874658875	0.00491180520578219	-178.072793678859
Winsorized Mean ( 3 / 26 )	-0.87456475	0.00484369067942442	-180.557514482722
Winsorized Mean ( 4 / 26 )	-0.87425425	0.00471904829353093	-185.260712673457
Winsorized Mean ( 5 / 26 )	-0.875103625	0.00453106826215642	-193.134063397121
Winsorized Mean ( 6 / 26 )	-0.875122375	0.00451502824347303	-193.824341246389
Winsorized Mean ( 7 / 26 )	-0.874866	0.00439008658329887	-199.282174371740
Winsorized Mean ( 8 / 26 )	-0.874909	0.00434346656383346	-201.431042956578
Winsorized Mean ( 9 / 26 )	-0.873584875	0.00402543199581943	-217.016428524256
Winsorized Mean ( 10 / 26 )	-0.873577375	0.00398369760868724	-219.288073747112
Winsorized Mean ( 11 / 26 )	-0.872872	0.00378198033651985	-230.797603988394
Winsorized Mean ( 12 / 26 )	-0.8722645	0.00345783955150091	-252.257077579376
Winsorized Mean ( 13 / 26 )	-0.87144225	0.00326558556002469	-266.856352094297
Winsorized Mean ( 14 / 26 )	-0.8719375	0.00314347511129267	-277.380118858787
Winsorized Mean ( 15 / 26 )	-0.871616875	0.00297108899713828	-293.366127988604
Winsorized Mean ( 16 / 26 )	-0.870812875	0.00279318459755254	-311.763453000217
Winsorized Mean ( 17 / 26 )	-0.871172	0.00248793485735266	-350.158685797340
Winsorized Mean ( 18 / 26 )	-0.87041825	0.00230977372155336	-376.841351114960
Winsorized Mean ( 19 / 26 )	-0.86946825	0.00213312953352669	-407.602180896401
Winsorized Mean ( 20 / 26 )	-0.86984325	0.00203429823198990	-427.588854142169
Winsorized Mean ( 21 / 26 )	-0.8682735	0.00175858626962726	-493.733810502248
Winsorized Mean ( 22 / 26 )	-0.86788575	0.00167813383180148	-517.173144092044
Winsorized Mean ( 23 / 26 )	-0.866094625	0.00137691830447826	-629.009449713272
Winsorized Mean ( 24 / 26 )	-0.865983625	0.0013346457032798	-648.84907123434
Winsorized Mean ( 25 / 26 )	-0.865968	0.00130178682460258	-665.214905877059
Winsorized Mean ( 26 / 26 )	-0.8651945	0.00100277936383416	-862.796474682027
Trimmed Mean ( 1 / 26 )	-0.874301794871795	0.00480767667068164	-181.855364817583
Trimmed Mean ( 2 / 26 )	-0.873937236842105	0.0046271081097812	-188.873312684157
Trimmed Mean ( 3 / 26 )	-0.873547162162162	0.00444612516788781	-196.473812404421
Trimmed Mean ( 4 / 26 )	-0.873170277777778	0.00426341806148404	-204.805220878067
Trimmed Mean ( 5 / 26 )	-0.872860571428571	0.00409345877171916	-213.233018849238
Trimmed Mean ( 6 / 26 )	-0.872332794117647	0.00394958425616645	-220.866991951288
Trimmed Mean ( 7 / 26 )	-0.871769242424242	0.0037806280931942	-230.588468618106
Trimmed Mean ( 8 / 26 )	-0.87121625	0.00361006972201611	-241.329480338528
Trimmed Mean ( 9 / 26 )	-0.87062064516129	0.00341295113123019	-255.093205758114
Trimmed Mean ( 10 / 26 )	-0.8701815	0.00325385118040719	-267.431253537264
Trimmed Mean ( 11 / 26 )	-0.869713103448276	0.00306676988181037	-283.592554044149
Trimmed Mean ( 12 / 26 )	-0.869302857142857	0.00288412040333403	-301.410043817154
Trimmed Mean ( 13 / 26 )	-0.868937222222222	0.00273395385164777	-317.831707985308
Trimmed Mean ( 14 / 26 )	-0.86864076923077	0.00259146523608666	-335.192908295576
Trimmed Mean ( 15 / 26 )	-0.868264	0.00243714401272791	-356.262902588241
Trimmed Mean ( 16 / 26 )	-0.867891458333333	0.00228086172960418	-380.510333909608
Trimmed Mean ( 17 / 26 )	-0.867573913043478	0.00212427095714009	-408.410193684281
Trimmed Mean ( 18 / 26 )	-0.867189090909091	0.00199388623735241	-434.924056680681
Trimmed Mean ( 19 / 26 )	-0.866847380952381	0.00186900170423788	-463.802349129399
Trimmed Mean ( 20 / 26 )	-0.8665715	0.00175161191514618	-494.72802308934
Trimmed Mean ( 21 / 26 )	-0.866227105263158	0.00161575000125541	-536.114562642806
Trimmed Mean ( 22 / 26 )	-0.866010555555556	0.00151630968820579	-571.130397894036
Trimmed Mean ( 23 / 26 )	-0.86581	0.00140203391853921	-617.538554917484
Trimmed Mean ( 24 / 26 )	-0.8657790625	0.00133958515179374	-646.303866044424
Trimmed Mean ( 25 / 26 )	-0.865756333333333	0.00126176281387091	-686.148239443921
Trimmed Mean ( 26 / 26 )	-0.865732142857143	0.00115694113631375	-748.294027832345
Median	-0.866875
Midrange	-0.884625
Midmean - Weighted Average at Xnp	-0.867301463414634
Midmean - Weighted Average at X(n+1)p	-0.8665715
Midmean - Empirical Distribution Function	-0.867301463414634
Midmean - Empirical Distribution Function - Averaging	-0.8665715
Midmean - Empirical Distribution Function - Interpolation	-0.8665715
Midmean - Closest Observation	-0.867301463414634
Midmean - True Basic - Statistics Graphics Toolkit	-0.8665715
Midmean - MS Excel (old versions)	-0.866847380952381
Number of observations	80

Charts produced by software:

http://www.freestatistics.org/blog/date/2009/Oct/21/t12561382230fl4aj89cnyess5/168yp1256138150.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Oct/21/t12561382230fl4aj89cnyess5/168yp1256138150.ps (open in new window)

http://www.freestatistics.org/blog/date/2009/Oct/21/t12561382230fl4aj89cnyess5/2lety1256138150.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Oct/21/t12561382230fl4aj89cnyess5/2lety1256138150.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