Nicky Van Calster 2MAR04b-Opgave 5 oefening2 Centrummaten

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

Title produced by software: Central Tendency

Date of computation: Sun, 20 Apr 2008 15:10:04 -0600

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2008/Apr/20/t120872585941rrvemw7gy5bl2.htm/, Retrieved Sun, 20 Apr 2008 23:10:59 +0200

User-defined keywords:

Dataseries X:

» Textbox « » Textfile « » CSV «

0,70291 0,6885 0,67127 0,66502 0,65825 0,65025 0,65779 0,66014 0,64683 0,64587 0,63702 0,62651 0,61834 0,61466 0,61063 0,59802 0,60151 0,62927 0,62304 0,6071 0,60773 0,58933 0,60039 0,61342 0,6348 0,634 0,62915 0,62168 0,61328 0,6089 0,60857 0,62672 0,62291 0,62393 0,61838 0,62012 0,61659 0,6116 0,61573 0,61407 0,62823 0,64405 0,6387 0,63633 0,63059 0,62994 0,63709 0,64217 0,65711 0,66977 0,68255 0,68902 0,71322 0,70224 0,70045 0,69919 0,69693 0,69763 0,69278 0,70196 0,69215 0,6769 0,67124 0,66532 0,67157 0,66428 0,66576 0,66942 0,6813 0,69144 0,69862 0,695 0,69867 0,68968 0,69233 0,68293 0,68399 0,66895 0,68756 0,68527 0,6776 0,68137 0,67933 0,67922 0,68598 0,68297 0,68935 0,69463 0,6833 0,68666 0,68782 0,67669 0,67511 0,67254 0,67397 0,67286 0,66341 0,668 0,68021 0,67934 0,68136 0,67562 0,6744 0,67766 0,68887 0,69614 0,70896 0,72064 0,74725

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 3 seconds R Server 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 Central Tendency - Ungrouped Data Measure Value S.E. Value/S.E. Arithmetic Mean 0.660805688073394 0.00320427515393045 206.226262205614 Geometric Mean 0.659957915527108 Harmonic Mean 0.659101849750553 Quadratic Mean 0.661644190143357 Winsorized Mean ( 1 / 36 ) 0.66064128440367 0.00313645707473687 210.632974933698 Winsorized Mean ( 2 / 36 ) 0.660548623853211 0.00310578357506648 212.683404328671 Winsorized Mean ( 3 / 36 ) 0.660462201834862 0.00308254159148443 214.258975015747 Winsorized Mean ( 4 / 36 ) 0.660445321100917 0.00301691371409386 218.914222841566 Winsorized Mean ( 5 / 36 ) 0.660443486238532 0.00300822376163583 219.545997429191 Winsorized Mean ( 6 / 36 ) 0.660474311926605 0.00299878881816067 220.247023707296 Winsorized Mean ( 7 / 36 ) 0.660398532110092 0.00298315808181685 221.375640846993 Winsorized Mean ( 8 / 36 ) 0.660433027522936 0.00295172044634144 223.745113918739 Winsorized Mean ( 9 / 36 ) 0.660470183486239 0.00293408998900318 225.102224526735 Winsorized Mean ( 10 / 36 ) 0.660619724770642 0.00291004208645379 227.013804317752 Winsorized Mean ( 11 / 36 ) 0.660533944954128 0.00289594868284510 228.088967483082 Winsorized Mean ( 12 / 36 ) 0.660528440366973 0.00287612133629995 229.659448657588 Winsorized Mean ( 13 / 36 ) 0.660504587155963 0.00285466084818141 231.37760395486 Winsorized Mean ( 14 / 36 ) 0.660495596330275 0.00281756870039291 234.420405166401 Winsorized Mean ( 15 / 36 ) 0.660563027522936 0.00279448085825478 236.381303372203 Winsorized Mean ( 16 / 36 ) 0.660548348623853 0.00272716605677380 242.210534625556 Winsorized Mean ( 17 / 36 ) 0.660484403669725 0.00271862539354568 242.947927006710 Winsorized Mean ( 18 / 36 ) 0.660742018348624 0.00267458725203278 247.044480544217 Winsorized Mean ( 19 / 36 ) 0.660890183486239 0.00262324464222597 251.936160603548 Winsorized Mean ( 20 / 36 ) 0.660792935779817 0.00255784785826559 258.339421418084 Winsorized Mean ( 21 / 36 ) 0.660754403669725 0.00254778629245767 259.344516306484 Winsorized Mean ( 22 / 36 ) 0.66086743119266 0.00251635675770279 262.628671061719 Winsorized Mean ( 23 / 36 ) 0.661380183486239 0.00244003653745994 271.053393394974 Winsorized Mean ( 24 / 36 ) 0.66134495412844 0.00242544937047206 272.669041118647 Winsorized Mean ( 25 / 36 ) 0.661535321100917 0.00236385191609444 279.854806723217 Winsorized Mean ( 26 / 36 ) 0.661692752293578 0.00232895869535756 284.115280194778 Winsorized Mean ( 27 / 36 ) 0.661499541284404 0.00230236594537091 287.312945456999 Winsorized Mean ( 28 / 36 ) 0.661496972477064 0.00226250851022212 292.37325273624 Winsorized Mean ( 29 / 36 ) 0.661481009174312 0.00222137762471000 297.779630899391 Winsorized Mean ( 30 / 36 ) 0.662067247706422 0.00206713666875995 320.282281143796 Winsorized Mean ( 31 / 36 ) 0.662098532110092 0.00201942010001923 327.865673964416 Winsorized Mean ( 32 / 36 ) 0.662450825688073 0.00195408803357394 339.007667160461 Winsorized Mean ( 33 / 36 ) 0.662647614678899 0.00192711973789493 343.853888084161 Winsorized Mean ( 34 / 36 ) 0.662550917431193 0.00191291713881554 346.356307854211 Winsorized Mean ( 35 / 36 ) 0.662688990825688 0.00181296544726097 365.527645232775 Winsorized Mean ( 36 / 36 ) 0.663831743119266 0.00167371088253475 396.622708286347 Trimmed Mean ( 1 / 36 ) 0.660665794392523 0.00308985093003460 213.818015610586 Trimmed Mean ( 2 / 36 ) 0.660691238095238 0.00303765490476216 217.500426746786 Trimmed Mean ( 3 / 36 ) 0.660766699029126 0.00299702460607236 220.474232240312 Trimmed Mean ( 4 / 36 ) 0.660876237623762 0.00296065576042075 223.219546986389 Trimmed Mean ( 5 / 36 ) 0.660994848484848 0.00294019373781844 224.813365181606 Trimmed Mean ( 6 / 36 ) 0.661118762886598 0.00291877925181532 226.505229018405 Trimmed Mean ( 7 / 36 ) 0.661242 0.00289612325191066 228.319702748755 Trimmed Mean ( 8 / 36 ) 0.661383225806452 0.00287298997427236 230.207286391230 Trimmed Mean ( 9 / 36 ) 0.661525494505494 0.00285195883784981 231.954783402218 Trimmed Mean ( 10 / 36 ) 0.661669101123596 0.00283033703440167 233.777494722805 Trimmed Mean ( 11 / 36 ) 0.661800574712644 0.00280889744820528 235.608663867560 Trimmed Mean ( 12 / 36 ) 0.661948235294118 0.00278566727909438 237.626453188378 Trimmed Mean ( 13 / 36 ) 0.662103614457831 0.00276113230731928 239.794236843599 Trimmed Mean ( 14 / 36 ) 0.662269135802469 0.0027351265244705 242.134734856802 Trimmed Mean ( 15 / 36 ) 0.662443924050633 0.00270947250703859 244.491841983912 Trimmed Mean ( 16 / 36 ) 0.662621428571429 0.00268205145182476 247.057687174721 Trimmed Mean ( 17 / 36 ) 0.662809733333333 0.00265841289083132 249.325353341205 Trimmed Mean ( 18 / 36 ) 0.66301397260274 0.00263068766828306 252.030668861371 Trimmed Mean ( 19 / 36 ) 0.663207746478873 0.00260330905504974 254.755671514461 Trimmed Mean ( 20 / 36 ) 0.663400434782609 0.00257697349395069 257.433938043953 Trimmed Mean ( 21 / 36 ) 0.663612537313433 0.00255316570236277 259.917535590937 Trimmed Mean ( 22 / 36 ) 0.663840769230769 0.00252456961590726 262.952055292087 Trimmed Mean ( 23 / 36 ) 0.664074603174603 0.00249337326361601 266.335816167183 Trimmed Mean ( 24 / 36 ) 0.66428393442623 0.00246586905150361 269.391407472011 Trimmed Mean ( 25 / 36 ) 0.664510169491525 0.00243286121777222 273.139365549187 Trimmed Mean ( 26 / 36 ) 0.664737719298246 0.00240037266083283 276.931049142848 Trimmed Mean ( 27 / 36 ) 0.664969818181818 0.00236424866505822 281.260523907473 Trimmed Mean ( 28 / 36 ) 0.665234150943396 0.00232146862507565 286.557459255655 Trimmed Mean ( 29 / 36 ) 0.665519411764706 0.00227281146465427 292.817693906670 Trimmed Mean ( 30 / 36 ) 0.66582918367347 0.00221674325675956 300.363689679958 Trimmed Mean ( 31 / 36 ) 0.66612 0.0021732037251676 306.515211752008 Trimmed Mean ( 32 / 36 ) 0.666434222222222 0.00212372206348149 313.804821111909 Trimmed Mean ( 33 / 36 ) 0.66674976744186 0.00207102690350359 321.941625342437 Trimmed Mean ( 34 / 36 ) 0.667080243902439 0.00200549131769301 332.626842119569 Trimmed Mean ( 35 / 36 ) 0.667452564102564 0.00191801216815380 347.991829866765 Trimmed Mean ( 36 / 36 ) 0.667853513513514 0.00182277571130574 366.393687040682 Median 0.67124 Midrange 0.66829 Midmean - Weighted Average at Xnp 0.664568148148148 Midmean - Weighted Average at X(n+1)p 0.664969818181818 Midmean - Empirical Distribution Function 0.664969818181818 Midmean - Empirical Distribution Function - Averaging 0.664969818181818 Midmean - Empirical Distribution Function - Interpolation 0.664969818181818 Midmean - Closest Observation 0.664330178571429 Midmean - True Basic - Statistics Graphics Toolkit 0.664969818181818 Midmean - MS Excel (old versions) 0.664969818181818 Number of observations 109

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Apr/20/t120872585941rrvemw7gy5bl2/15cq31208725799.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Apr/20/t120872585941rrvemw7gy5bl2/15cq31208725799.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Apr/20/t120872585941rrvemw7gy5bl2/2oon91208725799.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Apr/20/t120872585941rrvemw7gy5bl2/2oon91208725799.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.

FreeStatistics.org is powered by