Centrummaten eigen reeks

*Unverified author*

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

Title produced by software: Central Tendency

Date of computation: Wed, 17 Mar 2010 07:01:34 -0600

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2010/Mar/17/t1268831032639tgks8y5iielj.htm/, Retrieved Wed, 17 Mar 2010 14:03:54 +0100

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/Mar/17/t1268831032639tgks8y5iielj.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 «

81.28 69.39 67.63 51.25 103.97 133.83 162.37 172.91 163.01 151.50 111.73 88.58 74.29 63.98 61.18 76.48 107.98 124.97 145.57 140.20 143.84 138.80 104.06 74.70 60.18 55.16 35.62 56.18 85.44 114.08 133.64 67.14 95.58 89.37 75.24 69.18 54.49 57.50 62.16 76.67 110.04 127.38 156.47 167.56 153.54 124.08 100.97 79.17 68.13 61.77 54.31 60.30 84.18 104.05 114.66 105.55 96.61 70.94 63.91 58.61 44.53 49.58 57.39 76.76 104.57 125.41 143.11 136.35 135.15 131.70 96.87 70.63 66.29 63.49 62.97 66.43 101.49 127.69 133.21 158.72 148.61 134.31 100.99 75.16 59.74 52.87 52.07 57.38 79.43 101.40 120.19 134.38 135.97 113.83 84.38 70.28 65.96 56.36 49.57 68.33 90.32 117.06 134.69 131.67 129.25 118.77 88.44 76.79 75.28 73.89 76.24 88.58 105.83 115.84 127.76 131.75 119.63 93.38 75.55 51.79

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 95.8285 3.08209344133049 31.0920164570456 Geometric Mean 89.942250300139 Harmonic Mean 84.2851805274835 Quadratic Mean 101.555492761347 Winsorized Mean ( 1 / 40 ) 95.8581666666667 3.06169317041969 31.3088743159481 Winsorized Mean ( 2 / 40 ) 95.8663333333333 3.03588103893082 31.5777634577854 Winsorized Mean ( 3 / 40 ) 95.8505833333333 3.03288768457135 31.6037365382623 Winsorized Mean ( 4 / 40 ) 95.7845833333333 3.00392650348123 31.8864603452611 Winsorized Mean ( 5 / 40 ) 95.7133333333333 2.98486225942668 32.0662479586972 Winsorized Mean ( 6 / 40 ) 95.5808333333333 2.95854122341314 32.3067438022939 Winsorized Mean ( 7 / 40 ) 95.5085 2.93346747922670 32.5582269707579 Winsorized Mean ( 8 / 40 ) 95.4118333333333 2.89152087230036 32.9971103606207 Winsorized Mean ( 9 / 40 ) 95.1973333333333 2.85537630581431 33.3396803564861 Winsorized Mean ( 10 / 40 ) 95.109 2.82759055114597 33.6360580783006 Winsorized Mean ( 11 / 40 ) 95.1355833333333 2.80693640824684 33.8930312257246 Winsorized Mean ( 12 / 40 ) 94.8625833333333 2.76387281185472 34.3223403502692 Winsorized Mean ( 13 / 40 ) 94.8214166666667 2.73031854806197 34.7290673221894 Winsorized Mean ( 14 / 40 ) 94.53675 2.69218117853800 35.1153000970532 Winsorized Mean ( 15 / 40 ) 94.503 2.68440489834587 35.2044507362629 Winsorized Mean ( 16 / 40 ) 94.5416666666667 2.65328340887395 35.6319518489696 Winsorized Mean ( 17 / 40 ) 94.6365833333333 2.62687268000801 36.0263304931265 Winsorized Mean ( 18 / 40 ) 94.6560833333333 2.61358202177308 36.2169935914686 Winsorized Mean ( 19 / 40 ) 94.664 2.61006272234324 36.2688602038702 Winsorized Mean ( 20 / 40 ) 94.7306666666667 2.58375405646056 36.6639643699047 Winsorized Mean ( 21 / 40 ) 94.8006666666667 2.56831441724821 36.9116281207656 Winsorized Mean ( 22 / 40 ) 94.7933333333333 2.55060894122464 37.1649811937927 Winsorized Mean ( 23 / 40 ) 94.66875 2.49882782761835 37.885263223689 Winsorized Mean ( 24 / 40 ) 94.76275 2.48654108232634 38.1102691902209 Winsorized Mean ( 25 / 40 ) 94.844 2.47654440228125 38.2969107731867 Winsorized Mean ( 26 / 40 ) 94.3348333333333 2.41026090264398 39.1388472633194 Winsorized Mean ( 27 / 40 ) 94.4450833333333 2.32311410516141 40.65451762507 Winsorized Mean ( 28 / 40 ) 94.50575 2.31323216182224 40.8544164134193 Winsorized Mean ( 29 / 40 ) 94.4646666666667 2.30074708647627 41.0582576511462 Winsorized Mean ( 30 / 40 ) 94.1496666666667 2.22390023156675 42.3353823747469 Winsorized Mean ( 31 / 40 ) 94.1625833333333 2.19761051638691 42.8477123817854 Winsorized Mean ( 32 / 40 ) 94.0585833333333 2.1562455969048 43.6214610563613 Winsorized Mean ( 33 / 40 ) 93.0438333333333 2.02782670981341 45.8835229278022 Winsorized Mean ( 34 / 40 ) 93.126 1.98546452382059 46.9038851526792 Winsorized Mean ( 35 / 40 ) 92.9364166666667 1.95123174771091 47.629614870553 Winsorized Mean ( 36 / 40 ) 92.6904166666666 1.86755724077220 49.6319013110092 Winsorized Mean ( 37 / 40 ) 92.4221666666667 1.8156611106355 50.9027627046095 Winsorized Mean ( 38 / 40 ) 92.1466666666667 1.76548231534303 52.1934804250717 Winsorized Mean ( 39 / 40 ) 92.9169166666667 1.65033089711417 56.3019918182134 Winsorized Mean ( 40 / 40 ) 92.9669166666667 1.6284706905123 57.0884801355683 Trimmed Mean ( 1 / 40 ) 95.6855084745763 3.02197478300652 31.6632385593172 Trimmed Mean ( 2 / 40 ) 95.5068965517241 2.97785983998468 32.0723276728214 Trimmed Mean ( 3 / 40 ) 95.3177192982456 2.94364990905314 32.3807933155018 Trimmed Mean ( 4 / 40 ) 95.1274107142857 2.90662672271014 32.7277699509997 Trimmed Mean ( 5 / 40 ) 94.9481818181818 2.87433078313997 33.0331437060485 Trimmed Mean ( 6 / 40 ) 94.7781481481481 2.84307509837940 33.3364912527893 Trimmed Mean ( 7 / 40 ) 94.6266981132076 2.81391507588595 33.6281286255288 Trimmed Mean ( 8 / 40 ) 94.4813461538461 2.78606540111673 33.9121063403521 Trimmed Mean ( 9 / 40 ) 94.3445098039216 2.76221812914215 34.1553437827959 Trimmed Mean ( 10 / 40 ) 94.2308 2.74117460880543 34.376066266375 Trimmed Mean ( 11 / 40 ) 94.1232653061224 2.72137368382684 34.5866743202150 Trimmed Mean ( 12 / 40 ) 94.0082291666667 2.70151807548395 34.7982973054238 Trimmed Mean ( 13 / 40 ) 93.917340425532 2.68467391214273 34.9827738857765 Trimmed Mean ( 14 / 40 ) 93.8266304347826 2.66942730694988 35.1485991735022 Trimmed Mean ( 15 / 40 ) 93.759 2.65637700689239 35.2958182354114 Trimmed Mean ( 16 / 40 ) 93.6913636363636 2.64161069388380 35.4675137609377 Trimmed Mean ( 17 / 40 ) 93.6172093023256 2.6277065814662 35.6269645791614 Trimmed Mean ( 18 / 40 ) 93.5315476190476 2.61398601317077 35.7811966658512 Trimmed Mean ( 19 / 40 ) 93.4401219512195 2.59877241243015 35.9554847913143 Trimmed Mean ( 20 / 40 ) 93.3435 2.58060467904204 36.1711736625427 Trimmed Mean ( 21 / 40 ) 93.2367948717949 2.56171361393368 36.3962600521233 Trimmed Mean ( 22 / 40 ) 93.1192105263158 2.54054853700588 36.6531909034337 Trimmed Mean ( 23 / 40 ) 92.9958108108108 2.51699643384933 36.9471364997483 Trimmed Mean ( 24 / 40 ) 92.8745833333333 2.49485541037583 37.2264392345457 Trimmed Mean ( 25 / 40 ) 92.7397142857143 2.46912611401946 37.5597316634201 Trimmed Mean ( 26 / 40 ) 92.5911764705882 2.43881581651680 37.9656289923648 Trimmed Mean ( 27 / 40 ) 92.4692424242424 2.41087424113226 38.3550667416043 Trimmed Mean ( 28 / 40 ) 92.33203125 2.38762554913481 38.6710685364619 Trimmed Mean ( 29 / 40 ) 92.1817741935484 2.35952081427299 39.0680063663482 Trimmed Mean ( 30 / 40 ) 92.0243333333333 2.32598426243111 39.563609616666 Trimmed Mean ( 31 / 40 ) 91.8777586206897 2.29528034449757 40.0289920318215 Trimmed Mean ( 32 / 40 ) 91.7198214285714 2.26008503878441 40.5824647544693 Trimmed Mean ( 33 / 40 ) 91.5574074074074 2.22176410139222 41.209328816698 Trimmed Mean ( 34 / 40 ) 91.4534615384615 2.19415848089013 41.6804266122839 Trimmed Mean ( 35 / 40 ) 91.3354 2.16435743794404 42.1997764319193 Trimmed Mean ( 36 / 40 ) 91.2210416666667 2.13070261610130 42.8126576544878 Trimmed Mean ( 37 / 40 ) 91.1145652173913 2.10075895433174 43.372213184913 Trimmed Mean ( 38 / 40 ) 91.0181818181818 2.06960361415867 43.9785576307966 Trimmed Mean ( 39 / 40 ) 90.9333333333333 2.03647844192971 44.6522445124279 Trimmed Mean ( 40 / 40 ) 90.78075 2.01188460530521 45.1222449640586 Median 88.975 Midrange 104.265 Midmean - Weighted Average at Xnp 91.6047540983607 Midmean - Weighted Average at X(n+1)p 92.0243333333333 Midmean - Empirical Distribution Function 91.6047540983607 Midmean - Empirical Distribution Function - Averaging 92.0243333333333 Midmean - Empirical Distribution Function - Interpolation 92.0243333333333 Midmean - Closest Observation 91.6047540983607 Midmean - True Basic - Statistics Graphics Toolkit 92.0243333333333 Midmean - MS Excel (old versions) 92.1817741935484 Number of observations 120

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Mar/17/t1268831032639tgks8y5iielj/1zwnm1268830892.png (open in new window) http://www.freestatistics.org/blog/date/2010/Mar/17/t1268831032639tgks8y5iielj/1zwnm1268830892.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Mar/17/t1268831032639tgks8y5iielj/234ce1268830892.png (open in new window) http://www.freestatistics.org/blog/date/2010/Mar/17/t1268831032639tgks8y5iielj/234ce1268830892.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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