centrummaten

*Unverified author*

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

Title produced by software: Central Tendency

Date of computation: Tue, 20 Oct 2009 12:22:13 -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/20/t12560629689x2f0jmxfb1il8v.htm/, Retrieved Tue, 20 Oct 2009 20:22:50 +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/20/t12560629689x2f0jmxfb1il8v.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:

KDGP1W52

Dataseries X:

» Textbox « » Textfile « » CSV «

102,5 77,7 82,8 77,3 103,1 99,7 99,5 107,2 96,7 97,1 105,2 151,2 102,7 75,4 87,2 83,7 105,8 111,5 99,7 111,2 101,5 110,9 116,3 164,9 118,1 83,7 84 107,2 113,7 120,7 111,2 112,4 112,5 130,4 130,7 174,3 132,2 91,8 104,2 104,8 131,4 141,2 132,7 135,7 136,9 151,2 144 201,5 149,6 108,7 122,8 126,7 139,9 162,5 142,7 151,6 148,1 159 157,8 226,7 153,7 122,3 117,6 166 154,5 183,9 164,4 173,3 160,2 166,4 170,3 238,4 166,8 122,5 141,8 140,5 173,8 188,8 168 187,4 177,7 183,8 196,1 264,6 193,7 141,3 170,1 163,7 190,1 230,7 195,9 210,3 204,7 210,3 221,2 288,2 203,2 162,4 149,2 195,3 213,7 227,9 212,1 226,8 212,6 220,9 228,1 311,6

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 1 seconds R Server 'Gwilym Jenkins' @ 72.249.127.135 Central Tendency - Ungrouped Data Measure Value S.E. Value/S.E. Arithmetic Mean 151.298148148148 4.66243651576662 32.4504468074824 Geometric Mean 143.963102172557 Harmonic Mean 137.015424389386 Quadratic Mean 158.799021594150 Winsorized Mean ( 1 / 36 ) 151.099074074074 4.59472350305467 32.8853464139072 Winsorized Mean ( 2 / 36 ) 150.669444444444 4.48062450415913 33.6268848917346 Winsorized Mean ( 3 / 36 ) 150.083333333333 4.30286949342718 34.8798246292601 Winsorized Mean ( 4 / 36 ) 149.831481481481 4.24525586784047 35.2938635846464 Winsorized Mean ( 5 / 36 ) 149.711111111111 4.22410223488745 35.4421135631203 Winsorized Mean ( 6 / 36 ) 149.716666666667 4.21974673974568 35.4800124037041 Winsorized Mean ( 7 / 36 ) 149.852777777778 4.17780638778288 35.8687703231032 Winsorized Mean ( 8 / 36 ) 150.186111111111 4.13013255342364 36.363508717563 Winsorized Mean ( 9 / 36 ) 150.136111111111 3.99988889996569 37.5350703146777 Winsorized Mean ( 10 / 36 ) 150.145370370370 3.9906687161565 37.6241129118276 Winsorized Mean ( 11 / 36 ) 149.656481481482 3.84263179280801 38.9463496766938 Winsorized Mean ( 12 / 36 ) 149.556481481481 3.82097907011466 39.1408795330024 Winsorized Mean ( 13 / 36 ) 149.496296296296 3.81171971818221 39.2201702510252 Winsorized Mean ( 14 / 36 ) 149.496296296296 3.7479113661789 39.8878953342784 Winsorized Mean ( 15 / 36 ) 149.635185185185 3.73140139589924 40.1016050831819 Winsorized Mean ( 16 / 36 ) 148.835185185185 3.604720597068 41.288965726288 Winsorized Mean ( 17 / 36 ) 148.662037037037 3.56320537340238 41.721433781709 Winsorized Mean ( 18 / 36 ) 148.562037037037 3.50110888768019 42.4328525056167 Winsorized Mean ( 19 / 36 ) 147.717592592593 3.35739313480772 43.9977049637508 Winsorized Mean ( 20 / 36 ) 147.754629629630 3.34357678004802 44.1905897036131 Winsorized Mean ( 21 / 36 ) 147.754629629630 3.31406486558387 44.5841091295593 Winsorized Mean ( 22 / 36 ) 147.713888888889 3.23702390203657 45.6326222354907 Winsorized Mean ( 23 / 36 ) 146.947222222222 3.13681907101345 46.8459349728278 Winsorized Mean ( 24 / 36 ) 146.991666666667 3.06057770746420 48.0274251191795 Winsorized Mean ( 25 / 36 ) 147.176851851852 2.9603683730678 49.7157222698383 Winsorized Mean ( 26 / 36 ) 146.406481481482 2.84667109063963 51.4307683676181 Winsorized Mean ( 27 / 36 ) 146.381481481482 2.84359516912861 51.4776094257955 Winsorized Mean ( 28 / 36 ) 144.877777777778 2.64537820455976 54.7663761378454 Winsorized Mean ( 29 / 36 ) 144.206481481481 2.51276398007673 57.3895847858652 Winsorized Mean ( 30 / 36 ) 144.095370370370 2.49397348536212 57.7774267513707 Winsorized Mean ( 31 / 36 ) 144.296296296296 2.43740783423163 59.2007190055597 Winsorized Mean ( 32 / 36 ) 144.177777777778 2.24989070667724 64.0821251227386 Winsorized Mean ( 33 / 36 ) 144.513888888889 2.197514431171 65.7624299704285 Winsorized Mean ( 34 / 36 ) 144.010185185185 2.10832874244380 68.3053749095413 Winsorized Mean ( 35 / 36 ) 144.463888888889 1.97117004607035 73.288394969722 Winsorized Mean ( 36 / 36 ) 144.863888888889 1.89734673750515 76.3507723840569 Trimmed Mean ( 1 / 36 ) 150.501886792453 4.44274284954593 33.8758942142768 Trimmed Mean ( 2 / 36 ) 149.881730769231 4.27014681009089 35.0999011123087 Trimmed Mean ( 3 / 36 ) 149.464705882353 4.14426358829898 36.0654438835298 Trimmed Mean ( 4 / 36 ) 149.242 4.07725154505044 36.603579237384 Trimmed Mean ( 5 / 36 ) 149.079591836735 4.02029957422231 37.0817122168248 Trimmed Mean ( 6 / 36 ) 148.9375 3.96147850577968 37.5964427883944 Trimmed Mean ( 7 / 36 ) 148.788297872340 3.89564394767571 38.1935053282046 Trimmed Mean ( 8 / 36 ) 148.609782608696 3.82967330961057 38.8048197833897 Trimmed Mean ( 9 / 36 ) 148.373333333333 3.76355836085752 39.4236834152684 Trimmed Mean ( 10 / 36 ) 148.132954545455 3.71175507132207 39.9091404737252 Trimmed Mean ( 11 / 36 ) 147.880232558140 3.65347081938415 40.4766425869708 Trimmed Mean ( 12 / 36 ) 147.672619047619 3.61072434903305 40.8983363925761 Trimmed Mean ( 13 / 36 ) 147.465853658537 3.56417959007296 41.3744172906612 Trimmed Mean ( 14 / 36 ) 147.255 3.51112873589107 41.9395046654788 Trimmed Mean ( 15 / 36 ) 147.033333333333 3.45854796143613 42.5130242439313 Trimmed Mean ( 16 / 36 ) 146.786842105263 3.39893138114065 43.186174019201 Trimmed Mean ( 17 / 36 ) 146.6 3.34796793596641 43.7877550812574 Trimmed Mean ( 18 / 36 ) 146.418055555556 3.29354856550213 44.4560183776226 Trimmed Mean ( 19 / 36 ) 146.234285714286 3.23776492043143 45.1651955308726 Trimmed Mean ( 20 / 36 ) 146.110294117647 3.19229492402249 45.7696727887343 Trimmed Mean ( 21 / 36 ) 145.975757575758 3.13916463329021 46.5014660358090 Trimmed Mean ( 22 / 36 ) 145.8328125 3.07910348112204 47.3621017916741 Trimmed Mean ( 23 / 36 ) 145.683870967742 3.0177407695908 48.2758069996504 Trimmed Mean ( 24 / 36 ) 145.585 2.95863079589878 49.2068831980685 Trimmed Mean ( 25 / 36 ) 145.475862068966 2.89766193830132 50.2045667046471 Trimmed Mean ( 26 / 36 ) 145.344642857143 2.8378562418891 51.2163515232857 Trimmed Mean ( 27 / 36 ) 145.262962962963 2.78208215302740 52.2137575286522 Trimmed Mean ( 28 / 36 ) 145.176923076923 2.71205150094451 53.5302972773058 Trimmed Mean ( 29 / 36 ) 145.2 2.65838219945277 54.6196856230415 Trimmed Mean ( 30 / 36 ) 145.277083333333 2.61196143721488 55.6199189097682 Trimmed Mean ( 31 / 36 ) 145.369565217391 2.55404551608123 56.9173745346704 Trimmed Mean ( 32 / 36 ) 145.454545454545 2.48882588309809 58.4430379169327 Trimmed Mean ( 33 / 36 ) 145.557142857143 2.43996473493952 59.6554289383002 Trimmed Mean ( 34 / 36 ) 145.6425 2.38418369489971 61.0869457380994 Trimmed Mean ( 35 / 36 ) 145.778947368421 2.32623774512985 62.6672607619836 Trimmed Mean ( 36 / 36 ) 145.891666666667 2.27775779124023 64.0505620166178 Median 146.05 Midrange 193.5 Midmean - Weighted Average at Xnp 144.643636363636 Midmean - Weighted Average at X(n+1)p 144.643636363636 Midmean - Empirical Distribution Function 144.643636363636 Midmean - Empirical Distribution Function - Averaging 144.643636363636 Midmean - Empirical Distribution Function - Interpolation 144.643636363636 Midmean - Closest Observation 144.643636363636 Midmean - True Basic - Statistics Graphics Toolkit 144.643636363636 Midmean - MS Excel (old versions) 145.344642857143 Number of observations 108

Charts produced by software:

http://www.freestatistics.org/blog/date/2009/Oct/20/t12560629689x2f0jmxfb1il8v/1zrvj1256062931.png (open in new window) http://www.freestatistics.org/blog/date/2009/Oct/20/t12560629689x2f0jmxfb1il8v/1zrvj1256062931.ps (open in new window) http://www.freestatistics.org/blog/date/2009/Oct/20/t12560629689x2f0jmxfb1il8v/2ekcn1256062931.png (open in new window) http://www.freestatistics.org/blog/date/2009/Oct/20/t12560629689x2f0jmxfb1il8v/2ekcn1256062931.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

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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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