*Unverified author*

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

Title produced by software: Central Tendency

Date of computation: Tue, 19 Oct 2010 15:10:25 +0000

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2010/Oct/19/t1287501004gpjnom70jqtp211.htm/, Retrieved Tue, 19 Oct 2010 17:10:06 +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/2010/Oct/19/t1287501004gpjnom70jqtp211.htm/}, year = {2010}, } @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 = {2010}, 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 «

98,6 100,1 98,8 98,3 102,8 103,6 105,2 100,1 98,2 98,4 97,4 98,4 100,3 101,1 104,1 107,3 110,1 112,6 114,3 115,3 109,9 108,2 103,2 101,8 105,6 108,2 109,8 114,6 117,2 116,5 116,1 112,1 106,8 106,9 104,5 103 105,9 107,7 107,1 112,5 114,5 114,6 113,1 112,8 111,9 112 112,4 110 112,3 109,6 111,9 110,8 110,4 110,8 114 108,4 110,5 105,1 102,3 104,3 103,4 102,4 104,5 107,3 110,1 111,8 111,8 105,7 106 106,4 107,1 111,5 109,6 109,9 109,3 111,4 112,9 115,5 118,4 116,2 113,3 113,8 114,1 117,1 115,5 115,2 114,2 115,3 118,8 118 118,1 111,8 112 114,3 115 118,5 117,6 119,1 120,6 123,6 122,7 123,8 123,1 124,5 120,7 118,7 119 122,3 118,6 118,1 118,2 120,8 119,7 119,7 117,1 114,5 116,5 116,4 114,9 115,5

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 'George Udny Yule' @ 72.249.76.132 Central Tendency - Ungrouped Data Measure Value S.E. Value/S.E. Arithmetic Mean 111.301666666667 0.602235545054722 184.814177078428 Geometric Mean 111.105314313338 Harmonic Mean 110.906541467894 Quadratic Mean 111.495384807324 Winsorized Mean ( 1 / 40 ) 111.3025 0.59992934049389 185.526015294352 Winsorized Mean ( 2 / 40 ) 111.300833333333 0.599045103628382 185.797083824224 Winsorized Mean ( 3 / 40 ) 111.290833333333 0.596471881691774 186.581860351370 Winsorized Mean ( 4 / 40 ) 111.2775 0.594285888934875 187.245738241303 Winsorized Mean ( 5 / 40 ) 111.269166666667 0.590120336008729 188.553350693240 Winsorized Mean ( 6 / 40 ) 111.204166666667 0.577178489004861 192.668591752958 Winsorized Mean ( 7 / 40 ) 111.274166666667 0.563184840911649 197.580187859003 Winsorized Mean ( 8 / 40 ) 111.2675 0.56225108093378 197.896462582532 Winsorized Mean ( 9 / 40 ) 111.215 0.550668870086001 201.963477584326 Winsorized Mean ( 10 / 40 ) 111.281666666667 0.539830847214300 206.141733546565 Winsorized Mean ( 11 / 40 ) 111.290833333333 0.522790128037874 212.878605322997 Winsorized Mean ( 12 / 40 ) 111.330833333333 0.514029770352448 216.584407663779 Winsorized Mean ( 13 / 40 ) 111.32 0.509739319328485 218.386135381217 Winsorized Mean ( 14 / 40 ) 111.355 0.501525474049373 222.032590091401 Winsorized Mean ( 15 / 40 ) 111.3675 0.496428649517355 224.337374783416 Winsorized Mean ( 16 / 40 ) 111.380833333333 0.491044869836091 226.824146173265 Winsorized Mean ( 17 / 40 ) 111.395 0.485378436779753 229.501336604591 Winsorized Mean ( 18 / 40 ) 111.395 0.477629607558835 233.224654077330 Winsorized Mean ( 19 / 40 ) 111.458333333333 0.465037547553873 239.675987282342 Winsorized Mean ( 20 / 40 ) 111.491666666667 0.460634660422791 242.039247685649 Winsorized Mean ( 21 / 40 ) 111.509166666667 0.453961701751733 245.635625728731 Winsorized Mean ( 22 / 40 ) 111.435833333333 0.445289374696448 250.254867206968 Winsorized Mean ( 23 / 40 ) 111.474166666667 0.421615699524936 264.397570565499 Winsorized Mean ( 24 / 40 ) 111.474166666667 0.416804732027508 267.449378812018 Winsorized Mean ( 25 / 40 ) 111.5575 0.406399546919893 274.502028472953 Winsorized Mean ( 26 / 40 ) 111.449166666667 0.389174224220188 286.373453663289 Winsorized Mean ( 27 / 40 ) 111.494166666667 0.383623618927545 290.634260159369 Winsorized Mean ( 28 / 40 ) 111.494166666667 0.378218764659083 294.787506820728 Winsorized Mean ( 29 / 40 ) 111.5425 0.361282074555268 308.740753709707 Winsorized Mean ( 30 / 40 ) 111.6175 0.346748931402205 321.89717081069 Winsorized Mean ( 31 / 40 ) 111.488333333333 0.327305832991089 340.624339977371 Winsorized Mean ( 32 / 40 ) 111.541666666667 0.321063933643225 347.412633368576 Winsorized Mean ( 33 / 40 ) 111.541666666667 0.321063933643225 347.412633368576 Winsorized Mean ( 34 / 40 ) 111.541666666667 0.308662478569938 361.370993920121 Winsorized Mean ( 35 / 40 ) 111.541666666667 0.308662478569938 361.370993920121 Winsorized Mean ( 36 / 40 ) 111.631666666667 0.291862039406781 382.480938232192 Winsorized Mean ( 37 / 40 ) 111.724166666667 0.268286386536378 416.436212470727 Winsorized Mean ( 38 / 40 ) 111.6925 0.265051558062526 421.399145194429 Winsorized Mean ( 39 / 40 ) 111.66 0.248046711061338 450.157147910693 Winsorized Mean ( 40 / 40 ) 111.96 0.215876819321687 518.629097611282 Trimmed Mean ( 1 / 40 ) 111.307627118644 0.590359261244286 188.542188504071 Trimmed Mean ( 2 / 40 ) 111.312931034483 0.579759204231528 191.998557715057 Trimmed Mean ( 3 / 40 ) 111.319298245614 0.568511946439836 195.808195311855 Trimmed Mean ( 4 / 40 ) 111.329464285714 0.557059003678464 199.852194382579 Trimmed Mean ( 5 / 40 ) 111.343636363636 0.545001591190227 204.299653732154 Trimmed Mean ( 6 / 40 ) 111.360185185185 0.532670830433157 209.060040127651 Trimmed Mean ( 7 / 40 ) 111.389622641509 0.521928708121803 213.419229308832 Trimmed Mean ( 8 / 40 ) 111.408653846154 0.51287950770787 217.221885787667 Trimmed Mean ( 9 / 40 ) 111.429411764706 0.502887388546099 221.579252736602 Trimmed Mean ( 10 / 40 ) 111.458 0.49369597645891 225.762423261872 Trimmed Mean ( 11 / 40 ) 111.479591836735 0.485181114245169 229.769025552801 Trimmed Mean ( 12 / 40 ) 111.501041666667 0.478244906227555 233.146323598506 Trimmed Mean ( 13 / 40 ) 111.519148936170 0.471685783030331 236.426775934858 Trimmed Mean ( 14 / 40 ) 111.539130434783 0.464812885927622 239.96565889559 Trimmed Mean ( 15 / 40 ) 111.556666666667 0.458121469589536 243.508925190994 Trimmed Mean ( 16 / 40 ) 111.573863636364 0.451146496994863 247.311825270881 Trimmed Mean ( 17 / 40 ) 111.590697674419 0.44385646090265 251.411678107562 Trimmed Mean ( 18 / 40 ) 111.607142857143 0.436214830572742 255.853618526919 Trimmed Mean ( 19 / 40 ) 111.624390243902 0.42841191506776 260.553888250861 Trimmed Mean ( 20 / 40 ) 111.6375 0.421060952772122 265.13382270433 Trimmed Mean ( 21 / 40 ) 111.648717948718 0.413088170728336 270.278177542254 Trimmed Mean ( 22 / 40 ) 111.659210526316 0.404670876151892 275.925986046015 Trimmed Mean ( 23 / 40 ) 111.675675675676 0.395938332714688 282.053204876601 Trimmed Mean ( 24 / 40 ) 111.690277777778 0.388881867531071 287.208756959732 Trimmed Mean ( 25 / 40 ) 111.705714285714 0.381149431438733 293.075904282623 Trimmed Mean ( 26 / 40 ) 111.716176470588 0.373417705362646 299.172146543225 Trimmed Mean ( 27 / 40 ) 111.734848484848 0.366483271094065 304.883898660055 Trimmed Mean ( 28 / 40 ) 111.7515625 0.358921113908648 311.354105873088 Trimmed Mean ( 29 / 40 ) 111.769354838710 0.350534748322442 318.853852217521 Trimmed Mean ( 30 / 40 ) 111.785 0.342900761450583 325.99810956124 Trimmed Mean ( 31 / 40 ) 111.796551724138 0.335786185653534 332.939699429715 Trimmed Mean ( 32 / 40 ) 111.817857142857 0.329818005136256 339.028965676578 Trimmed Mean ( 33 / 40 ) 111.837037037037 0.323333185245987 345.887901830903 Trimmed Mean ( 34 / 40 ) 111.857692307692 0.315109047105073 354.980897360251 Trimmed Mean ( 35 / 40 ) 111.88 0.306847033619060 364.611639488408 Trimmed Mean ( 36 / 40 ) 111.904166666667 0.296237612084014 377.751379642266 Trimmed Mean ( 37 / 40 ) 111.923913043478 0.286089489438591 391.219940526695 Trimmed Mean ( 38 / 40 ) 111.938636363636 0.277869726063662 402.845743396999 Trimmed Mean ( 39 / 40 ) 111.957142857143 0.267611773019368 418.356567777159 Trimmed Mean ( 40 / 40 ) 111.98 0.257781461806861 434.398964204414 Median 111.95 Midrange 110.95 Midmean - Weighted Average at Xnp 111.696721311475 Midmean - Weighted Average at X(n+1)p 111.785 Midmean - Empirical Distribution Function 111.696721311475 Midmean - Empirical Distribution Function - Averaging 111.785 Midmean - Empirical Distribution Function - Interpolation 111.785 Midmean - Closest Observation 111.696721311475 Midmean - True Basic - Statistics Graphics Toolkit 111.785 Midmean - MS Excel (old versions) 111.769354838710 Number of observations 120

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Oct/19/t1287501004gpjnom70jqtp211/1xi0q1287501024.png (open in new window) http://www.freestatistics.org/blog/date/2010/Oct/19/t1287501004gpjnom70jqtp211/1xi0q1287501024.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Oct/19/t1287501004gpjnom70jqtp211/27szb1287501024.png (open in new window) http://www.freestatistics.org/blog/date/2010/Oct/19/t1287501004gpjnom70jqtp211/27szb1287501024.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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