opgave 5 oef 2

*Unverified author*

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

Title produced by software: Central Tendency

Date of computation: Wed, 20 Oct 2010 14:11:05 +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/20/t1287583799vu5zbmho4zeq002.htm/, Retrieved Wed, 20 Oct 2010 16:10:01 +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/20/t1287583799vu5zbmho4zeq002.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 «

102,8 106,3 103,7 106,9 104,3 105,4 96,2 95,7 95,9 93,6 94,7 94,5 96,6 96,7 98,9 102 105,2 106,4 99,3 96,4 93,1 95,6 93,3 96,7 105,6 105,2 107 104,9 104,5 105,2 99,7 100,2 98,5 98,4 97,1 98,4 100,6 111,3 119 117,8 108,8 109,3 103,5 103,7 110 105,5 110,4 106,7 110,2 105,2 108 108,1 107,2 106 99,4 100,2 100,3 100,8 99,5 100,2 103 111 120,5 109,5 106,6 105,5 103,9 104,9 104,8 99,6 97 95,4 99,3 103,9 107,4 107,4 111 113,2 108,5 113,3 113,8 105,3 107,5 109,4 118,9 119 115 124,1 120,5 117,7 117,1 118,1 119,6 118,8 124,9 124 124,9 121,7 121,6 125,1 127,9 129 130,1 130,3 127,9 124,1 125,7 129,2 129,2 132,6 131,5 131 125,8 127,2 127,3 127,5 122 118,4 118,3 115,5

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 109.831666666667 0.993294029921965 110.573167016110 Geometric Mean 109.309589714992 Harmonic Mean 108.801127624735 Quadratic Mean 110.364869108486 Winsorized Mean ( 1 / 40 ) 109.824166666667 0.991334298631558 110.784189368075 Winsorized Mean ( 2 / 40 ) 109.820833333333 0.989124259578654 111.028348834670 Winsorized Mean ( 3 / 40 ) 109.825833333333 0.982993695202869 111.725877662590 Winsorized Mean ( 4 / 40 ) 109.825833333333 0.980962695157355 111.957196614614 Winsorized Mean ( 5 / 40 ) 109.8175 0.970850115867012 113.114782812719 Winsorized Mean ( 6 / 40 ) 109.8275 0.969609614546931 113.269813285957 Winsorized Mean ( 7 / 40 ) 109.821666666667 0.966940352930374 113.576464498400 Winsorized Mean ( 8 / 40 ) 109.761666666667 0.95333204785324 115.134770632996 Winsorized Mean ( 9 / 40 ) 109.784166666667 0.950606467066555 115.488554380916 Winsorized Mean ( 10 / 40 ) 109.7675 0.94331138127599 116.364015296328 Winsorized Mean ( 11 / 40 ) 109.7675 0.938251220964543 116.991587697756 Winsorized Mean ( 12 / 40 ) 109.7675 0.935506545406604 117.334828429545 Winsorized Mean ( 13 / 40 ) 109.615833333333 0.912319968682462 120.150645712202 Winsorized Mean ( 14 / 40 ) 109.639166666667 0.90644926734836 120.954553791405 Winsorized Mean ( 15 / 40 ) 109.576666666667 0.893927328754583 122.578942540361 Winsorized Mean ( 16 / 40 ) 109.723333333333 0.870379141872615 126.063835924726 Winsorized Mean ( 17 / 40 ) 109.723333333333 0.870379141872615 126.063835924726 Winsorized Mean ( 18 / 40 ) 109.618333333333 0.851365671183126 128.755876638764 Winsorized Mean ( 19 / 40 ) 109.681666666667 0.844492773139131 129.878751074400 Winsorized Mean ( 20 / 40 ) 109.731666666667 0.835024600296247 131.411298095573 Winsorized Mean ( 21 / 40 ) 109.381666666667 0.786249102846775 139.118335741978 Winsorized Mean ( 22 / 40 ) 109.345 0.776891249793433 140.746854890017 Winsorized Mean ( 23 / 40 ) 109.345 0.772275050420121 141.588155593679 Winsorized Mean ( 24 / 40 ) 109.145 0.741283475113394 147.237870078385 Winsorized Mean ( 25 / 40 ) 109.165833333333 0.739035157047354 147.713992077834 Winsorized Mean ( 26 / 40 ) 109.079166666667 0.702609079057377 155.248729226511 Winsorized Mean ( 27 / 40 ) 108.944166666667 0.685796063464155 158.857964445520 Winsorized Mean ( 28 / 40 ) 108.944166666667 0.685796063464155 158.857964445520 Winsorized Mean ( 29 / 40 ) 108.944166666667 0.680235990350183 160.156428375074 Winsorized Mean ( 30 / 40 ) 108.994166666667 0.669201723357976 162.871915690454 Winsorized Mean ( 31 / 40 ) 108.9425 0.651094384140137 167.322131251177 Winsorized Mean ( 32 / 40 ) 109.235833333333 0.615158420343503 177.573499314756 Winsorized Mean ( 33 / 40 ) 109.400833333333 0.587051570124006 186.356427443374 Winsorized Mean ( 34 / 40 ) 109.3725 0.571155350910721 191.493434887028 Winsorized Mean ( 35 / 40 ) 109.489166666667 0.55406796576859 197.609631725931 Winsorized Mean ( 36 / 40 ) 109.369166666667 0.526307623023159 207.804641016674 Winsorized Mean ( 37 / 40 ) 108.875833333333 0.466356933777702 233.460307862027 Winsorized Mean ( 38 / 40 ) 108.780833333333 0.441642427060647 246.309744417729 Winsorized Mean ( 39 / 40 ) 108.390833333333 0.396154476832551 273.607493218229 Winsorized Mean ( 40 / 40 ) 108.3575 0.364502774212987 297.274829345152 Trimmed Mean ( 1 / 40 ) 109.780508474576 0.981151690087067 111.889435225693 Trimmed Mean ( 2 / 40 ) 109.735344827586 0.969817564499278 113.150502573382 Trimmed Mean ( 3 / 40 ) 109.690350877193 0.958465148355477 114.443755274147 Trimmed Mean ( 4 / 40 ) 109.641964285714 0.948240291236435 115.626772347702 Trimmed Mean ( 5 / 40 ) 109.591818181818 0.937419783006318 116.907942597878 Trimmed Mean ( 6 / 40 ) 109.541666666667 0.927919811477087 118.050789854670 Trimmed Mean ( 7 / 40 ) 109.487735849057 0.917484845511563 119.334653193110 Trimmed Mean ( 8 / 40 ) 109.432692307692 0.906260322037163 120.751940305299 Trimmed Mean ( 9 / 40 ) 109.384313725490 0.896152982000396 122.059866922857 Trimmed Mean ( 10 / 40 ) 109.331 0.885146446822916 123.517413861204 Trimmed Mean ( 11 / 40 ) 109.277551020408 0.873848652645508 125.053177903953 Trimmed Mean ( 12 / 40 ) 109.221875 0.861777542738763 126.740219584846 Trimmed Mean ( 13 / 40 ) 109.163829787234 0.848426822898347 128.666169952424 Trimmed Mean ( 14 / 40 ) 109.118478260870 0.836662780963033 130.421097655700 Trimmed Mean ( 15 / 40 ) 109.068888888889 0.823985995003046 132.367406182050 Trimmed Mean ( 16 / 40 ) 109.022727272727 0.811198281696655 134.397137830102 Trimmed Mean ( 17 / 40 ) 108.961627906977 0.799514504880792 136.284741854962 Trimmed Mean ( 18 / 40 ) 108.897619047619 0.785956733400154 138.554216052725 Trimmed Mean ( 19 / 40 ) 108.839024390244 0.772854639748739 140.827289884199 Trimmed Mean ( 20 / 40 ) 108.7725 0.758418939620236 143.420073415447 Trimmed Mean ( 21 / 40 ) 108.698717948718 0.742733683972372 146.349519746248 Trimmed Mean ( 22 / 40 ) 108.647368421053 0.731229375019882 148.581788605113 Trimmed Mean ( 23 / 40 ) 108.595945945946 0.718879684954936 151.062755310374 Trimmed Mean ( 24 / 40 ) 108.541666666667 0.70483949160088 153.994871116173 Trimmed Mean ( 25 / 40 ) 108.498571428571 0.692543823630407 156.666723067152 Trimmed Mean ( 26 / 40 ) 108.451470588235 0.678101895137464 159.933885107710 Trimmed Mean ( 27 / 40 ) 108.407575757576 0.665928416202605 162.791635136641 Trimmed Mean ( 28 / 40 ) 108.3703125 0.653666701905535 165.788332469873 Trimmed Mean ( 29 / 40 ) 108.330645161290 0.638727204381092 169.603931722713 Trimmed Mean ( 30 / 40 ) 108.288333333333 0.621334865483914 174.283368516581 Trimmed Mean ( 31 / 40 ) 108.239655172414 0.601696229355715 179.890865010596 Trimmed Mean ( 32 / 40 ) 108.191071428571 0.580580077061951 186.349955334459 Trimmed Mean ( 33 / 40 ) 108.118518518519 0.559955786377757 193.084027612101 Trimmed Mean ( 34 / 40 ) 108.028846153846 0.538504832885637 200.608870258344 Trimmed Mean ( 35 / 40 ) 107.934 0.514219122672863 209.89884514401 Trimmed Mean ( 36 / 40 ) 107.822916666667 0.485701944905381 221.993998166245 Trimmed Mean ( 37 / 40 ) 107.710869565217 0.455012111755446 236.720884526934 Trimmed Mean ( 38 / 40 ) 107.625 0.43101391107868 249.701917347984 Trimmed Mean ( 39 / 40 ) 107.538095238095 0.405321059431852 265.315834782515 Trimmed Mean ( 40 / 40 ) 107.4725 0.384207267446849 279.725317832172 Median 106.95 Midrange 112.85 Midmean - Weighted Average at Xnp 108.157377049180 Midmean - Weighted Average at X(n+1)p 108.288333333333 Midmean - Empirical Distribution Function 108.157377049180 Midmean - Empirical Distribution Function - Averaging 108.288333333333 Midmean - Empirical Distribution Function - Interpolation 108.288333333333 Midmean - Closest Observation 108.157377049180 Midmean - True Basic - Statistics Graphics Toolkit 108.288333333333 Midmean - MS Excel (old versions) 108.330645161290 Number of observations 120

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Oct/20/t1287583799vu5zbmho4zeq002/1gvp61287583863.png (open in new window) http://www.freestatistics.org/blog/date/2010/Oct/20/t1287583799vu5zbmho4zeq002/1gvp61287583863.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Oct/20/t1287583799vu5zbmho4zeq002/2rm6r1287583863.png (open in new window) http://www.freestatistics.org/blog/date/2010/Oct/20/t1287583799vu5zbmho4zeq002/2rm6r1287583863.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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