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werkloosheid gemiddelde

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

Title produced by software: Central Tendency

Date of computation: Thu, 22 Nov 2007 08:08:22 -0700

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2007/Nov/22/t11957436133sd56wnl5aitpwn.htm/, Retrieved Thu, 22 Nov 2007 16:00:15 +0100

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bridome

Dataseries X:

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17.0234037008088 9.56996242724384 9.4449624272435 7.56996242724347 0.569962427243631 -8.30503757275661 -6.55503757275662 -3.35967987142745 -5.73467987142732 -10.6096798714273 7.51532012857262 -6.35967987142736 -10.9876053340285 -20.4410466075928 -24.5660466075928 -20.4410466075928 -22.4410466075928 -24.3160466075928 -22.5660466075928 -11.3706889062636 -15.7456889062636 -16.6206889062636 -5.4956889062636 3.62931109373641 5.00138563113531 -15.4520556424290 -15.577055642429 -13.4520556424290 -9.452055642429 -4.32705564242898 -6.57705564242899 5.6183020589002 7.24330205890018 14.3683020589002 7.49330205890017 11.6183020589002 18.9903765962991 20.5369353227347 23.4119353227348 27.5369353227348 30.5369353227348 33.6619353227348 39.4119353227348 -30.9555685865694 -24.3305685865694 -16.2055685865694 -20.0805685865694 -15.9555685865694 -17.5834940491705 -24.0369353227348 -16.1619353227348 -12.0369353227348 -8.03693532273481 -3.91193532273477 -8.16193532273478 3.0334223785944 9.65842237859439 6.78342237859437 8.90842237859439 17.0334223785944 26.4054969159933 20.9520556424289 21.8270556424290 14.952055642429 17.9520556424290 23.077055642429 18.827055642429 31.0224133437582 33.6474133437582 31.7724133437581 24.8974133437582 30.0224133437582 25.3944878811571 19.9410466075927 21.8160466075928 14.9410466075928 16.9410466075927 17.0660466075928 17.8160466075928 35.0114043089220 35.6364043089219 28.7614043089219 19.8864043089219 20.0114043089219 -0.616521153679177 -11.0699624272435 -20.1949624272435 -19.0699624272435 -26.0699624272435 -32.9449624272434 -32.1949624272435 -28.9996047259143 -40.3746047259143 -38.2496047259143 -43.1246047259143 -59.9996047259143 -63.6275301885154

Text written by user:

Output produced by software:

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 9.90544988529932e-16 2.26508290035088 4.37310699920294e-16 Geometric Mean NaN Harmonic Mean -5992.31904242385 Quadratic Mean 22.1931893238522 Winsorized Mean ( 1 / 32 ) -0.00152170671352280 2.24766714424339 -0.000677016041908213 Winsorized Mean ( 2 / 32 ) 0.333529839678232 2.16046443924316 0.154378768573980 Winsorized Mean ( 3 / 32 ) 0.376845231858009 2.13622419234505 0.176407154833466 Winsorized Mean ( 4 / 32 ) 0.46387525334351 2.11908082158837 0.21890399300382 Winsorized Mean ( 5 / 32 ) 0.640660938842005 2.05422121657943 0.311875339263021 Winsorized Mean ( 6 / 32 ) 0.640660938842005 2.03911761987658 0.314185377340215 Winsorized Mean ( 7 / 32 ) 0.695067235105458 2.01889629952345 0.344280800984937 Winsorized Mean ( 8 / 32 ) 0.813949039779973 1.98659432730716 0.409720811436769 Winsorized Mean ( 9 / 32 ) 0.968770682816164 1.9277214748342 0.50254702012877 Winsorized Mean ( 10 / 32 ) 0.997579634719628 1.88672005871795 0.528737493466569 Winsorized Mean ( 11 / 32 ) 0.895975879638194 1.86440859700450 0.480568412459446 Winsorized Mean ( 12 / 32 ) 0.772699130459687 1.84655474073081 0.418454494424507 Winsorized Mean ( 13 / 32 ) 0.743487560531525 1.83207132296659 0.405818022044921 Winsorized Mean ( 14 / 32 ) 0.741381887517714 1.77357557549856 0.418015390919730 Winsorized Mean ( 15 / 32 ) 0.708926266851869 1.76406367584332 0.401871132295132 Winsorized Mean ( 16 / 32 ) 0.832637607058054 1.692964683032 0.49182219534955 Winsorized Mean ( 17 / 32 ) 0.830708188581607 1.69271548237357 0.490754764892187 Winsorized Mean ( 18 / 32 ) 0.716045073873743 1.66624641094363 0.429735403581893 Winsorized Mean ( 19 / 32 ) 0.657139887261559 1.65308131403765 0.397524236515924 Winsorized Mean ( 20 / 32 ) 0.757155381181786 1.61259378688362 0.469526415976716 Winsorized Mean ( 21 / 32 ) 1.06373604315725 1.57017010400995 0.677465479976116 Winsorized Mean ( 22 / 32 ) 1.26971112123141 1.54190884259198 0.823467046921532 Winsorized Mean ( 23 / 32 ) 1.15568153321742 1.50355151475077 0.768634477687973 Winsorized Mean ( 24 / 32 ) 1.12606808413647 1.49726836797855 0.75208166299323 Winsorized Mean ( 25 / 32 ) 0.953739923354354 1.46333634932434 0.651757146465145 Winsorized Mean ( 26 / 32 ) 0.973540302552391 1.45216932280698 0.670404123859728 Winsorized Mean ( 27 / 32 ) 0.811716571867178 1.42149033628020 0.571032071868532 Winsorized Mean ( 28 / 32 ) 0.838381742877948 1.41603983512829 0.592060846086292 Winsorized Mean ( 29 / 32 ) 1.43332461240596 1.34536159363553 1.06538243635507 Winsorized Mean ( 30 / 32 ) 1.84551942471878 1.29255675136976 1.42780533447605 Winsorized Mean ( 31 / 32 ) 1.42278663080674 1.19247635176401 1.19313613951508 Winsorized Mean ( 32 / 32 ) 1.51836351960968 1.18099535956190 1.28566425542344 Trimmed Mean ( 1 / 32 ) 0.254900998587165 2.17303582794832 0.117301792869118 Trimmed Mean ( 2 / 32 ) 0.522352637449173 2.08736005133682 0.25024558514217 Trimmed Mean ( 3 / 32 ) 0.622988963733686 2.04299436396685 0.304939149476672 Trimmed Mean ( 4 / 32 ) 0.71241196744882 2.00263323692971 0.355737613014471 Trimmed Mean ( 5 / 32 ) 0.781688005575874 1.96219882788791 0.398373495318655 Trimmed Mean ( 6 / 32 ) 0.813875359630427 1.93411716324658 0.420799409206558 Trimmed Mean ( 7 / 32 ) 0.813875359630427 1.90530848500204 0.427161987697522 Trimmed Mean ( 8 / 32 ) 0.873710961924768 1.87635509430358 0.465642651850529 Trimmed Mean ( 9 / 32 ) 0.882883282253953 1.84924005214510 0.47743032670627 Trimmed Mean ( 10 / 32 ) 0.870861524888103 1.82863058702238 0.476236989071783 Trimmed Mean ( 11 / 32 ) 0.854472649349892 1.81139075119792 0.471721879326594 Trimmed Mean ( 12 / 32 ) 0.849459183175589 1.79437457778418 0.47340125840646 Trimmed Mean ( 13 / 32 ) 0.858198297158503 1.77663110088966 0.483048110960543 Trimmed Mean ( 14 / 32 ) 0.858198297158503 1.75732152796508 0.488355877681797 Trimmed Mean ( 15 / 32 ) 0.883965856150572 1.74287562369369 0.507188145920118 Trimmed Mean ( 16 / 32 ) 0.901380051188494 1.72619289313883 0.522178057140223 Trimmed Mean ( 17 / 32 ) 0.907995147498665 1.71603835387687 0.529122875049573 Trimmed Mean ( 18 / 32 ) 0.915224496596982 1.70257030882068 0.537554597220088 Trimmed Mean ( 19 / 32 ) 0.933416967410687 1.68902281389703 0.552637276258596 Trimmed Mean ( 20 / 32 ) 0.9581620059836 1.67320346165914 0.572651221408237 Trimmed Mean ( 21 / 32 ) 0.975887135625215 1.65878799087708 0.588313359508478 Trimmed Mean ( 22 / 32 ) 0.968230941527634 1.64613000631074 0.588186192959088 Trimmed Mean ( 23 / 32 ) 0.942167147025614 1.63308350557181 0.576925272841894 Trimmed Mean ( 24 / 32 ) 0.92379013241993 1.62109724615960 0.569854852698321 Trimmed Mean ( 25 / 32 ) 0.92379013241993 1.60487376675073 0.575615448117307 Trimmed Mean ( 26 / 32 ) 0.902313535844951 1.58808837991905 0.568175894524804 Trimmed Mean ( 27 / 32 ) 0.896133753760316 1.56625137345649 0.572151934834494 Trimmed Mean ( 28 / 32 ) 0.896133753760316 1.54160642833521 0.581298661765477 Trimmed Mean ( 29 / 32 ) 0.909317787445241 1.50793284847770 0.603022732983912 Trimmed Mean ( 30 / 32 ) 0.861947179783368 1.47650947550850 0.58377355112233 Trimmed Mean ( 31 / 32 ) 0.861947179783368 1.44322796893887 0.597235640061154 Trimmed Mean ( 32 / 32 ) 0.709289928210949 1.42023081441365 0.499418771239507 Median 0.569962427243631 Midrange -12.1077974328903 Midmean - Weighted Average at Xnp 0.550805434294742 Midmean - Weighted Average at X(n+1)p 0.92379013241993 Midmean - Empirical Distribution Function 0.92379013241993 Midmean - Empirical Distribution Function - Averaging 0.92379013241993 Midmean - Empirical Distribution Function - Interpolation 0.92379013241993 Midmean - Closest Observation 0.581202958040145 Midmean - True Basic - Statistics Graphics Toolkit 0.92379013241993 Midmean - MS Excel (old versions) 0.92379013241993 Number of observations 97

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Nov/22/t11957436133sd56wnl5aitpwn/1nkzq1195744099.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Nov/22/t11957436133sd56wnl5aitpwn/1nkzq1195744099.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Nov/22/t11957436133sd56wnl5aitpwn/28mg51195744099.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Nov/22/t11957436133sd56wnl5aitpwn/28mg51195744099.ps (open in new window)

Parameters:

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')

Copyright

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.

Privacy Policy

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.

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