*Unverified author*

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

Title produced by software: Central Tendency

Date of computation: Wed, 03 Jun 2009 06:53:24 -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/Jun/03/t1244033646jogqyfumlg8k3rz.htm/, Retrieved Wed, 03 Jun 2009 14:54:08 +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/Jun/03/t1244033646jogqyfumlg8k3rz.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:

Dataseries X:

» Textbox « » Textfile « » CSV «

0 1 0 0 1 3 9 2 3 5 3 5 2 2 0 1 0 1 3 3 2 1 1 5 0 3 1 0 1 4 0 0 1 6 14 1 1 0 0 1 1 1 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 0 2 0 1 0 1 0 0 1 2 0 0 1 2 0 3 1 1 0 2 0 4 0 2 1 1 1 1 0 1 1 0 2 1 3 1 2 4 0 0 0 1 0 1 0 2 2 4 2 3 3 0 0 2 7 8 2 4 1 1 2 4

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 'Gwilym Jenkins' @ 72.249.127.135 Central Tendency - Ungrouped Data Measure Value S.E. Value/S.E. Arithmetic Mean 1.55833333333333 0.187791168258300 8.29822481955011 Geometric Mean 0 Harmonic Mean 0 Quadratic Mean 2.57390753524675 Winsorized Mean ( 1 / 40 ) 1.51666666666667 0.168193288390383 9.01740301994945 Winsorized Mean ( 2 / 40 ) 1.5 0.162266854942361 9.24403200230151 Winsorized Mean ( 3 / 40 ) 1.475 0.154286330271620 9.56014701628635 Winsorized Mean ( 4 / 40 ) 1.44166666666667 0.144844083724889 9.95323129251802 Winsorized Mean ( 5 / 40 ) 1.4 0.134622618083738 10.3994411929292 Winsorized Mean ( 6 / 40 ) 1.4 0.134622618083738 10.3994411929292 Winsorized Mean ( 7 / 40 ) 1.4 0.134622618083738 10.3994411929292 Winsorized Mean ( 8 / 40 ) 1.33333333333333 0.120882222313023 11.0300200295845 Winsorized Mean ( 9 / 40 ) 1.33333333333333 0.120882222313023 11.0300200295845 Winsorized Mean ( 10 / 40 ) 1.33333333333333 0.120882222313023 11.0300200295845 Winsorized Mean ( 11 / 40 ) 1.33333333333333 0.120882222313023 11.0300200295845 Winsorized Mean ( 12 / 40 ) 1.33333333333333 0.120882222313023 11.0300200295845 Winsorized Mean ( 13 / 40 ) 1.33333333333333 0.120882222313023 11.0300200295845 Winsorized Mean ( 14 / 40 ) 1.21666666666667 0.101241130837699 12.0175135994592 Winsorized Mean ( 15 / 40 ) 1.21666666666667 0.101241130837699 12.0175135994592 Winsorized Mean ( 16 / 40 ) 1.21666666666667 0.101241130837699 12.0175135994592 Winsorized Mean ( 17 / 40 ) 1.21666666666667 0.101241130837699 12.0175135994592 Winsorized Mean ( 18 / 40 ) 1.21666666666667 0.101241130837699 12.0175135994592 Winsorized Mean ( 19 / 40 ) 1.21666666666667 0.101241130837699 12.0175135994592 Winsorized Mean ( 20 / 40 ) 1.21666666666667 0.101241130837699 12.0175135994592 Winsorized Mean ( 21 / 40 ) 1.21666666666667 0.101241130837699 12.0175135994592 Winsorized Mean ( 22 / 40 ) 1.21666666666667 0.101241130837699 12.0175135994592 Winsorized Mean ( 23 / 40 ) 1.21666666666667 0.101241130837699 12.0175135994592 Winsorized Mean ( 24 / 40 ) 1.01666666666667 0.0748325238737702 13.5858930587669 Winsorized Mean ( 25 / 40 ) 1.01666666666667 0.0748325238737702 13.5858930587669 Winsorized Mean ( 26 / 40 ) 1.01666666666667 0.0748325238737702 13.5858930587669 Winsorized Mean ( 27 / 40 ) 1.01666666666667 0.0748325238737702 13.5858930587669 Winsorized Mean ( 28 / 40 ) 1.01666666666667 0.0748325238737702 13.5858930587669 Winsorized Mean ( 29 / 40 ) 1.01666666666667 0.0748325238737702 13.5858930587669 Winsorized Mean ( 30 / 40 ) 1.01666666666667 0.0748325238737702 13.5858930587669 Winsorized Mean ( 31 / 40 ) 1.01666666666667 0.0748325238737702 13.5858930587669 Winsorized Mean ( 32 / 40 ) 1.01666666666667 0.0748325238737702 13.5858930587669 Winsorized Mean ( 33 / 40 ) 1.01666666666667 0.0748325238737702 13.5858930587669 Winsorized Mean ( 34 / 40 ) 1.01666666666667 0.0748325238737702 13.5858930587669 Winsorized Mean ( 35 / 40 ) 1.01666666666667 0.0748325238737702 13.5858930587669 Winsorized Mean ( 36 / 40 ) 1.01666666666667 0.0748325238737702 13.5858930587669 Winsorized Mean ( 37 / 40 ) 1.01666666666667 0.0748325238737702 13.5858930587669 Winsorized Mean ( 38 / 40 ) 1.01666666666667 0.0748325238737702 13.5858930587669 Winsorized Mean ( 39 / 40 ) 1.34166666666667 0.04347611684317 30.8598551132434 Winsorized Mean ( 40 / 40 ) 1.34166666666667 0.04347611684317 30.8598551132434 Trimmed Mean ( 1 / 40 ) 1.46610169491525 0.15816298546437 9.26956260095083 Trimmed Mean ( 2 / 40 ) 1.41379310344828 0.146456887914421 9.65330564906166 Trimmed Mean ( 3 / 40 ) 1.36842105263158 0.136643712251700 10.0145190004128 Trimmed Mean ( 4 / 40 ) 1.33035714285714 0.128967532090512 10.3154423543088 Trimmed Mean ( 5 / 40 ) 1.3 0.123576127209155 10.5198312114096 Trimmed Mean ( 6 / 40 ) 1.27777777777778 0.120453548490480 10.6080542565234 Trimmed Mean ( 7 / 40 ) 1.25471698113208 0.116909377175859 10.7323895776529 Trimmed Mean ( 8 / 40 ) 1.23076923076923 0.112867745335135 10.9045257094021 Trimmed Mean ( 9 / 40 ) 1.21568627450980 0.111141559811333 10.9381789905907 Trimmed Mean ( 10 / 40 ) 1.2 0.109175051725163 10.9915221567367 Trimmed Mean ( 11 / 40 ) 1.18367346938776 0.106931001912940 11.0695069550687 Trimmed Mean ( 12 / 40 ) 1.16666666666667 0.104363848460552 11.1788390700028 Trimmed Mean ( 13 / 40 ) 1.14893617021277 0.101416919833808 11.3288411055623 Trimmed Mean ( 14 / 40 ) 1.13043478260870 0.0980183384564197 11.532890685668 Trimmed Mean ( 15 / 40 ) 1.12222222222222 0.0971860999419004 11.5471474098982 Trimmed Mean ( 16 / 40 ) 1.11363636363636 0.0962079043662418 11.5753104796566 Trimmed Mean ( 17 / 40 ) 1.10465116279070 0.095061460092524 11.6203891852233 Trimmed Mean ( 18 / 40 ) 1.09523809523810 0.0937199714678554 11.6862828496885 Trimmed Mean ( 19 / 40 ) 1.08536585365854 0.0921508842055247 11.7781382459428 Trimmed Mean ( 20 / 40 ) 1.075 0.0903141493323181 11.9028968101604 Trimmed Mean ( 21 / 40 ) 1.06410256410256 0.0881597549198442 12.0701624575755 Trimmed Mean ( 22 / 40 ) 1.05263157894737 0.0856241006449995 12.2936366165365 Trimmed Mean ( 23 / 40 ) 1.04054054054054 0.0826244569395604 12.5936142769652 Trimmed Mean ( 24 / 40 ) 1.02777777777778 0.0790500678841031 13.0016052520616 Trimmed Mean ( 25 / 40 ) 1.02857142857143 0.0787359467139334 13.0635557391400 Trimmed Mean ( 26 / 40 ) 1.02941176470588 0.0783123914614191 13.1449409920399 Trimmed Mean ( 27 / 40 ) 1.03030303030303 0.0777591073363854 13.2499338739313 Trimmed Mean ( 28 / 40 ) 1.03125 0.077051151583331 13.3839660901719 Trimmed Mean ( 29 / 40 ) 1.03225806451613 0.0761575294654455 13.5542483029795 Trimmed Mean ( 30 / 40 ) 1.03333333333333 0.0750392238926453 13.7705759698644 Trimmed Mean ( 31 / 40 ) 1.03448275862069 0.0736463535077227 14.0466256555691 Trimmed Mean ( 32 / 40 ) 1.03571428571429 0.0719139353685051 14.4021361146073 Trimmed Mean ( 33 / 40 ) 1.03703703703704 0.0697553023813712 14.8667843394510 Trimmed Mean ( 34 / 40 ) 1.03846153846154 0.067051332520046 15.4875600444044 Trimmed Mean ( 35 / 40 ) 1.04 0.0636315927180574 16.3440824844365 Trimmed Mean ( 36 / 40 ) 1.04166666666667 0.0592381697598869 17.5843830234612 Trimmed Mean ( 37 / 40 ) 1.04347826086957 0.0534466345350312 19.5237412036791 Trimmed Mean ( 38 / 40 ) 1.04545454545455 0.0454545454545455 23 Trimmed Mean ( 39 / 40 ) 1.04761904761905 0.0332585855128371 31.499206339208 Trimmed Mean ( 40 / 40 ) 1.025 0.025 41 Median 1 Midrange 7 Midmean - Weighted Average at Xnp 0.770833333333333 Midmean - Weighted Average at X(n+1)p 0.770833333333333 Midmean - Empirical Distribution Function 0.770833333333333 Midmean - Empirical Distribution Function - Averaging 0.770833333333333 Midmean - Empirical Distribution Function - Interpolation 0.770833333333333 Midmean - Closest Observation 0.770833333333333 Midmean - True Basic - Statistics Graphics Toolkit 0.770833333333333 Midmean - MS Excel (old versions) 0.770833333333333 Number of observations 120

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/03/t1244033646jogqyfumlg8k3rz/1eulh1244033600.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/03/t1244033646jogqyfumlg8k3rz/1eulh1244033600.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/03/t1244033646jogqyfumlg8k3rz/2dhq71244033600.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/03/t1244033646jogqyfumlg8k3rz/2dhq71244033600.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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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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