Central tendency multiple regression

*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, 16 Dec 2008 13:09:35 -0700

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2008/Dec/16/t122945827277gkb3nlp98mdia.htm/, Retrieved Tue, 16 Dec 2008 21:11:12 +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/2008/Dec/16/t122945827277gkb3nlp98mdia.htm/}, year = {2008}, } @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 = {2008}, note = {{ISBN} 3-900051-07-0}, url = {http://www.R-project.org}, }

Original text written by user:

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Dataseries X:

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24.70833333 35.58333333 21.33333333 14.58333333 15.08333333 14.95833333 13.08333333 6.083333333 -2.791666667 -1.041666667 -7.916666667 -10.29166667 -16.5625 -0.6875 -14.9375 -16.6875 -18.1875 -22.3125 -18.1875 -20.1875 -22.0625 -20.3125 -19.1875 -23.5625 -25.83333333 -16.95833333 -8.208333333 -3.958333333 -16.45833333 -16.58333333 -14.45833333 -10.45833333 -5.333333333 -7.583333333 -5.458333333 -3.833333333 1.895833333 -7.229166667 -3.479166667 6.770833333 16.27083333 19.14583333 23.27083333 26.27083333 29.39583333 35.14583333 35.27083333 41.89583333 -20.14583333 -26.27083333 -22.52083333 -21.27083333 -19.77083333 -11.89583333 -7.770833333 -3.770833333 0.354166667 -3.895833333 -2.770833333 3.854166667 -0.416666667 -0.541666667 7.208333333 19.45833333 21.95833333 22.83333333 15.95833333 18.95833333 24.08333333 19.83333333 21.95833333 24.58333333 21.3125 12.1875 16.9375 15.1875 17.6875 19.5625 12.6875 14.6875 14.8125 15.5625 22.6875 23.3125 15.04166667 3.916666667 3.666666667 -14.08333333 -16.58333333 -25.70833333 -24.58333333 -31.58333333 -38.45833333 -37.70833333 -44.58333333 -55.95833333

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 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 Central Tendency - Ungrouped Data Measure Value S.E. Value/S.E. Arithmetic Mean -9.37500441138226e-11 2.04628628350480 -4.5814725373251e-11 Geometric Mean NaN Harmonic Mean -19.5496650837555 Quadratic Mean 19.9447315759247 Winsorized Mean ( 1 / 32 ) 0.05273437490625 2.00205614776406 0.0263401078761676 Winsorized Mean ( 2 / 32 ) 0.17382812490625 1.97269932529807 0.0881168876964993 Winsorized Mean ( 3 / 32 ) 0.19335937490625 1.96717579199524 0.0982928804294263 Winsorized Mean ( 4 / 32 ) 0.20898437490625 1.87637935693516 0.111376398452603 Winsorized Mean ( 5 / 32 ) 0.322916666572917 1.80451829125913 0.178948957257505 Winsorized Mean ( 6 / 32 ) 0.252604166572917 1.78586409510845 0.141446466875508 Winsorized Mean ( 7 / 32 ) 0.252604166572916 1.78315347501773 0.141661483496481 Winsorized Mean ( 8 / 32 ) 0.30468749990625 1.76305298256040 0.172818118865473 Winsorized Mean ( 9 / 32 ) 0.32812499990625 1.73886283196937 0.188700910660462 Winsorized Mean ( 10 / 32 ) 0.432291666572916 1.72280193656763 0.250923601487342 Winsorized Mean ( 11 / 32 ) 0.406032985635416 1.71250810332602 0.237098431736949 Winsorized Mean ( 12 / 32 ) 0.419053819385417 1.70564916325045 0.245685823564576 Winsorized Mean ( 13 / 32 ) 0.427517361052083 1.67745613784436 0.254860530422852 Winsorized Mean ( 14 / 32 ) 0.567274305010417 1.65868059594076 0.342003340726773 Winsorized Mean ( 15 / 32 ) 0.489149305010416 1.64294293390199 0.297727507703926 Winsorized Mean ( 16 / 32 ) 0.49262152834375 1.64155979629293 0.300093563119795 Winsorized Mean ( 17 / 32 ) 0.297092013864583 1.59843474261598 0.185864337119179 Winsorized Mean ( 18 / 32 ) 0.355685763864583 1.57755476505145 0.225466507879353 Winsorized Mean ( 19 / 32 ) 0.532986110427083 1.54941532351757 0.34399176407851 Winsorized Mean ( 20 / 32 ) 0.467881943760416 1.54107690928574 0.303607134038022 Winsorized Mean ( 21 / 32 ) 0.695746527822917 1.50206587174188 0.463193086875806 Winsorized Mean ( 22 / 32 ) 0.46657986115625 1.4576290095686 0.320095070894850 Winsorized Mean ( 23 / 32 ) 0.311848959177084 1.4323821226367 0.217713523681124 Winsorized Mean ( 24 / 32 ) 0.145182291677083 1.41218275030595 0.102807013926228 Winsorized Mean ( 25 / 32 ) 0.0692274296979167 1.40175961961514 0.0493860921153682 Winsorized Mean ( 26 / 32 ) -0.0097656240520833 1.38549738795270 -0.00704846081775267 Winsorized Mean ( 27 / 32 ) 0.312500000010417 1.32025708851917 0.236696324320382 Winsorized Mean ( 28 / 32 ) 0.421875000010417 1.29973358862836 0.324585748726885 Winsorized Mean ( 29 / 32 ) 0.522569446468749 1.28463261055677 0.406785132320643 Winsorized Mean ( 30 / 32 ) 1.18012152771875 1.20138795029037 0.982298455243806 Winsorized Mean ( 31 / 32 ) 1.59722222323958 1.14330819179531 1.39701808725039 Winsorized Mean ( 32 / 32 ) 1.61111110990625 1.13208280085452 1.42313893355694 Trimmed Mean ( 1 / 32 ) 0.149601063734042 1.95169774595833 0.0766517582160679 Trimmed Mean ( 2 / 32 ) 0.250679347728261 1.89429948209840 0.132333535482241 Trimmed Mean ( 3 / 32 ) 0.291666666566667 1.84671277324312 0.157938294894909 Trimmed Mean ( 4 / 32 ) 0.327414772625 1.79464119531128 0.182440241247338 Trimmed Mean ( 5 / 32 ) 0.360465116174419 1.76586418439325 0.204129581063039 Trimmed Mean ( 6 / 32 ) 0.369047618940476 1.75255000089342 0.210577512055201 Trimmed Mean ( 7 / 32 ) 0.391768292573171 1.74111122915234 0.225010491009184 Trimmed Mean ( 8 / 32 ) 0.4156249998875 1.72786726825090 0.24054220339982 Trimmed Mean ( 9 / 32 ) 0.432692307576923 1.71589253237543 0.252167486840167 Trimmed Mean ( 10 / 32 ) 0.447368420934210 1.70572398559199 0.262274802203093 Trimmed Mean ( 11 / 32 ) 0.449324324202703 1.69585096356854 0.264955077925716 Trimmed Mean ( 12 / 32 ) 0.454571759180556 1.68513952639512 0.269753187828301 Trimmed Mean ( 13 / 32 ) 0.4586309523 1.67277550503945 0.274173641901328 Trimmed Mean ( 14 / 32 ) 0.462009803838235 1.66173637550374 0.278028338699742 Trimmed Mean ( 15 / 32 ) 0.451073232287879 1.65053579888573 0.27328897234001 Trimmed Mean ( 16 / 32 ) 0.447265625015625 1.63853423027431 0.272966909541308 Trimmed Mean ( 17 / 32 ) 0.442876344048387 1.62327532787492 0.272828851916435 Trimmed Mean ( 18 / 32 ) 0.456597222183333 1.61044095230517 0.283523106842113 Trimmed Mean ( 19 / 32 ) 0.465876436741379 1.59685583621221 0.291746083883473 Trimmed Mean ( 20 / 32 ) 0.459821428589286 1.58334124152699 0.290412083339551 Trimmed Mean ( 21 / 32 ) 0.459104938351852 1.56666179973465 0.293046615695623 Trimmed Mean ( 22 / 32 ) 0.438301282134615 1.55091629162003 0.282607955376355 Trimmed Mean ( 23 / 32 ) 0.43583333342 1.53704420989331 0.283552893673925 Trimmed Mean ( 24 / 32 ) 0.446614583354167 1.52202715653648 0.293434043825133 Trimmed Mean ( 25 / 32 ) 0.472826086978261 1.50453706233602 0.314266825866109 Trimmed Mean ( 26 / 32 ) 0.508049242522727 1.48203832069568 0.342804390027003 Trimmed Mean ( 27 / 32 ) 0.553571428595238 1.45411392220046 0.380693300671750 Trimmed Mean ( 28 / 32 ) 0.575000000025 1.42930293249751 0.402294004267009 Trimmed Mean ( 29 / 32 ) 0.5888157895 1.39864662824479 0.420989675025296 Trimmed Mean ( 30 / 32 ) 0.59490740725 1.35876824094737 0.437828460602830 Trimmed Mean ( 31 / 32 ) 0.539828431205882 1.32299243301187 0.408035917466989 Trimmed Mean ( 32 / 32 ) 0.43749999971875 1.28532461139728 0.340380940222674 Median -0.8645833335 Midrange -7.03125 Midmean - Weighted Average at Xnp 0.099064625938774 Midmean - Weighted Average at X(n+1)p 0.099064625938774 Midmean - Empirical Distribution Function 0.099064625938774 Midmean - Empirical Distribution Function - Averaging 0.099064625938774 Midmean - Empirical Distribution Function - Interpolation 0.099064625938774 Midmean - Closest Observation 0.099064625938774 Midmean - True Basic - Statistics Graphics Toolkit 0.099064625938774 Midmean - MS Excel (old versions) 0.435833333419998 Number of observations 96

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/16/t122945827277gkb3nlp98mdia/16p8l1229458169.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/16/t122945827277gkb3nlp98mdia/16p8l1229458169.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/16/t122945827277gkb3nlp98mdia/290z51229458169.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/16/t122945827277gkb3nlp98mdia/290z51229458169.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')

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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