*The author of this computation has been verified*

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

Title produced by software: Central Tendency

Date of computation: Fri, 24 Dec 2010 09:49:44 +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/Dec/24/t1293184059sxxyyw06czsu6if.htm/, Retrieved Fri, 24 Dec 2010 10:47:42 +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/Dec/24/t1293184059sxxyyw06czsu6if.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:

Dataseries X:

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1579 2146 2462 3695 4831 5134 6250 5760 6249 2917 1741 2359 1511 2059 2635 2867 4403 5720 4502 5749 5627 2846 1762 2429 1169 2154 2249 2687 4359 5382 4459 6398 4596 3024 1887 2070 1351 2218 2461 3028 4784 4975 4607 6249 4809 3157 1910 2228 1594 2467 2222 3607 4685 4962 5770 5480 5000 3228 1993 2288 1580 2111 2192 3601 4665 4876 5813 5589 5331 3075 2002 2306 1507 1992 2487 3490 4647 5594 5611 5788 6204 3013 1931 2549 1504 2090 2702 2939 4500 6208 6415 5657 5964 3163 1997 2422 1376 2202 2683 3303 5202 5231 4880 7998 4977 3531 2025 2205 1442 2238 2179 3218 5139 4990 4914 6084 5672 3548 1793 2086

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 3626.425 148.163166010500 24.4758876152998 Geometric Mean 3261.36289613366 Harmonic Mean 2921.46980992151 Quadratic Mean 3970.30034233348 Winsorized Mean ( 1 / 40 ) 3614.75 145.248490472686 24.8866613913607 Winsorized Mean ( 2 / 40 ) 3614.88333333333 145.148423110826 24.9047372052623 Winsorized Mean ( 3 / 40 ) 3612.83333333333 144.355089218843 25.0274053577444 Winsorized Mean ( 4 / 40 ) 3614.86666666667 144.092175959473 25.0871821637517 Winsorized Mean ( 5 / 40 ) 3614.99166666667 144.076797572878 25.0907274978686 Winsorized Mean ( 6 / 40 ) 3613.14166666667 143.739245266102 25.1367791724364 Winsorized Mean ( 7 / 40 ) 3616.875 143.222935741727 25.2534622424042 Winsorized Mean ( 8 / 40 ) 3608.94166666667 142.021886158000 25.4111655907154 Winsorized Mean ( 9 / 40 ) 3600.99166666667 140.601211835903 25.6113842807373 Winsorized Mean ( 10 / 40 ) 3600.65833333333 137.429455545444 26.2000480103968 Winsorized Mean ( 11 / 40 ) 3600.29166666667 136.902522313005 26.2982128147733 Winsorized Mean ( 12 / 40 ) 3601.59166666667 136.313634432472 26.4213604285553 Winsorized Mean ( 13 / 40 ) 3610.69166666667 135.054905732601 26.7349908326587 Winsorized Mean ( 14 / 40 ) 3612.09166666667 134.597011860061 26.8363436658024 Winsorized Mean ( 15 / 40 ) 3611.09166666667 133.837258504956 26.981213654589 Winsorized Mean ( 16 / 40 ) 3612.825 132.146271485718 27.3395908895581 Winsorized Mean ( 17 / 40 ) 3610.84166666667 131.853979796637 27.3851549436414 Winsorized Mean ( 18 / 40 ) 3606.94166666667 131.207594881541 27.4903420790782 Winsorized Mean ( 19 / 40 ) 3605.2 130.79890085542 27.5629227495195 Winsorized Mean ( 20 / 40 ) 3606.2 130.041101345750 27.7312323771537 Winsorized Mean ( 21 / 40 ) 3611.275 129.324614892745 27.9241117632169 Winsorized Mean ( 22 / 40 ) 3593.30833333333 126.585126413447 28.3864971750080 Winsorized Mean ( 23 / 40 ) 3577.59166666667 123.949524094391 28.8632949001259 Winsorized Mean ( 24 / 40 ) 3568.19166666667 122.628537317716 29.0975636235626 Winsorized Mean ( 25 / 40 ) 3551.73333333333 119.698958136227 29.6722159376791 Winsorized Mean ( 26 / 40 ) 3553.03333333333 118.197422996391 30.0601590395233 Winsorized Mean ( 27 / 40 ) 3540.65833333333 116.368215394232 30.426335244021 Winsorized Mean ( 28 / 40 ) 3545.325 115.651917965945 30.6551336316269 Winsorized Mean ( 29 / 40 ) 3516.08333333333 111.661080956916 31.4888885473893 Winsorized Mean ( 30 / 40 ) 3516.08333333333 111.133406207390 31.6384015691181 Winsorized Mean ( 31 / 40 ) 3513.5 110.682683571447 31.7438996474277 Winsorized Mean ( 32 / 40 ) 3516.43333333333 110.279717396692 31.8864920616745 Winsorized Mean ( 33 / 40 ) 3513.95833333333 109.774090275324 32.0108171656899 Winsorized Mean ( 34 / 40 ) 3502.05833333333 108.105681056674 32.3947668531628 Winsorized Mean ( 35 / 40 ) 3495.05833333333 106.732035923680 32.7461038580069 Winsorized Mean ( 36 / 40 ) 3497.15833333333 106.275044170407 32.9066749454914 Winsorized Mean ( 37 / 40 ) 3495.30833333333 103.584524002680 33.7435381104121 Winsorized Mean ( 38 / 40 ) 3494.04166666667 102.273360419599 34.1637514630553 Winsorized Mean ( 39 / 40 ) 3503.14166666667 99.7247523532118 35.1281059516599 Winsorized Mean ( 40 / 40 ) 3491.14166666667 94.1710191819021 37.0723572601792 Trimmed Mean ( 1 / 40 ) 3610.20338983051 144.506465029647 24.9829887478725 Trimmed Mean ( 2 / 40 ) 3605.5 143.663012791664 25.0969259932520 Trimmed Mean ( 3 / 40 ) 3600.56140350877 142.763542724884 25.2204542895614 Trimmed Mean ( 4 / 40 ) 3596.17857142857 142.054839464995 25.3154245569700 Trimmed Mean ( 5 / 40 ) 3591.08181818182 141.319581240551 25.4110703319249 Trimmed Mean ( 6 / 40 ) 3585.76851851852 140.477108580165 25.5256429660371 Trimmed Mean ( 7 / 40 ) 3580.60377358491 139.586223134638 25.6515556705853 Trimmed Mean ( 8 / 40 ) 3574.625 138.664300776514 25.7789855065959 Trimmed Mean ( 9 / 40 ) 3569.57843137255 137.823578025427 25.8996209684383 Trimmed Mean ( 10 / 40 ) 3565.39 137.088064223423 26.0080264477965 Trimmed Mean ( 11 / 40 ) 3561.07142857143 136.712506894367 26.0478833244053 Trimmed Mean ( 12 / 40 ) 3556.61458333333 136.317606251273 26.090647284236 Trimmed Mean ( 13 / 40 ) 3551.82978723404 135.902696123410 26.135094361989 Trimmed Mean ( 14 / 40 ) 3545.92391304348 135.543120320596 26.1608549711443 Trimmed Mean ( 15 / 40 ) 3539.62222222222 135.135986051225 26.1930395126616 Trimmed Mean ( 16 / 40 ) 3533.125 134.709655086743 26.227704300222 Trimmed Mean ( 17 / 40 ) 3526.17441860465 134.366355260361 26.2429862875419 Trimmed Mean ( 18 / 40 ) 3519.05952380952 133.942473320687 26.2729172947564 Trimmed Mean ( 19 / 40 ) 3511.91463414634 133.467357213288 26.3129105683431 Trimmed Mean ( 20 / 40 ) 3504.55 132.900434917519 26.3697406421205 Trimmed Mean ( 21 / 40 ) 3496.73076923077 132.26397896213 26.4375138013348 Trimmed Mean ( 22 / 40 ) 3488.11842105263 131.534283393176 26.5187016728264 Trimmed Mean ( 23 / 40 ) 3480.36486486487 130.950816972914 26.5776491152763 Trimmed Mean ( 24 / 40 ) 3473.31944444444 130.508576676876 26.6137255717987 Trimmed Mean ( 25 / 40 ) 3466.54285714286 130.059961781791 26.6534205427407 Trimmed Mean ( 26 / 40 ) 3460.52941176471 129.791022805065 26.6623171385444 Trimmed Mean ( 27 / 40 ) 3454.06060606061 129.537084858921 26.6646467289459 Trimmed Mean ( 28 / 40 ) 3448.046875 129.343284452576 26.6581051315752 Trimmed Mean ( 29 / 40 ) 3441.32258064516 129.063635000457 26.6637661385639 Trimmed Mean ( 30 / 40 ) 3436.16666666667 129.10654770047 26.6149682403301 Trimmed Mean ( 31 / 40 ) 3430.65517241379 129.060973016764 26.5816620797378 Trimmed Mean ( 32 / 40 ) 3424.92857142857 128.896308515 26.5711920759158 Trimmed Mean ( 33 / 40 ) 3418.57407407407 128.571054844595 26.5889867529371 Trimmed Mean ( 34 / 40 ) 3411.90384615385 128.064355226775 26.6421038087615 Trimmed Mean ( 35 / 40 ) 3405.54 127.510102712991 26.7080013860975 Trimmed Mean ( 36 / 40 ) 3399.14583333333 126.839269728958 26.7988442427724 Trimmed Mean ( 37 / 40 ) 3392.04347826087 125.85691959205 26.9515850956449 Trimmed Mean ( 38 / 40 ) 3384.43181818182 124.860744409227 27.1056514535061 Trimmed Mean ( 39 / 40 ) 3376.19047619048 123.587034969912 27.3183224843321 Trimmed Mean ( 40 / 40 ) 3366.425 122.162637955225 27.5569114775816 Median 3160 Midrange 4583.5 Midmean - Weighted Average at Xnp 3415.77049180328 Midmean - Weighted Average at X(n+1)p 3436.16666666667 Midmean - Empirical Distribution Function 3415.77049180328 Midmean - Empirical Distribution Function - Averaging 3436.16666666667 Midmean - Empirical Distribution Function - Interpolation 3436.16666666667 Midmean - Closest Observation 3415.77049180328 Midmean - True Basic - Statistics Graphics Toolkit 3436.16666666667 Midmean - MS Excel (old versions) 3441.32258064516 Number of observations 120

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Dec/24/t1293184059sxxyyw06czsu6if/17zq71293184182.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/24/t1293184059sxxyyw06czsu6if/17zq71293184182.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/24/t1293184059sxxyyw06czsu6if/27zq71293184182.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/24/t1293184059sxxyyw06czsu6if/27zq71293184182.ps (open in new window)

Parameters (Session):

Parameters (R input):

R code (references can be found in the software module):

geomean <- function(x) { return(exp(mean(log(x)))) } harmean <- function(x) { return(1/mean(1/x)) } quamean <- function(x) { return(sqrt(mean(x*x))) } winmean <- function(x) { x <-sort(x[!is.na(x)]) n<-length(x) denom <- 3 nodenom <- n/denom if (nodenom>40) denom <- n/40 sqrtn = sqrt(n) roundnodenom = floor(nodenom) win <- array(NA,dim=c(roundnodenom,2)) for (j in 1:roundnodenom) { win[j,1] <- (j*x[j+1]+sum(x[(j+1):(n-j)])+j*x[n-j])/n win[j,2] <- sd(c(rep(x[j+1],j),x[(j+1):(n-j)],rep(x[n-j],j)))/sqrtn } return(win) } trimean <- function(x) { x <-sort(x[!is.na(x)]) n<-length(x) denom <- 3 nodenom <- n/denom if (nodenom>40) denom <- n/40 sqrtn = sqrt(n) roundnodenom = floor(nodenom) tri <- array(NA,dim=c(roundnodenom,2)) for (j in 1:roundnodenom) { tri[j,1] <- mean(x,trim=j/n) tri[j,2] <- sd(x[(j+1):(n-j)]) / sqrt(n-j*2) } return(tri) } midrange <- function(x) { return((max(x)+min(x))/2) } q1 <- function(data,n,p,i,f) { np <- n*p; i <<- floor(np) f <<- np - i qvalue <- (1-f)*data[i] + f*data[i+1] } q2 <- function(data,n,p,i,f) { np <- (n+1)*p i <<- floor(np) f <<- np - i qvalue <- (1-f)*data[i] + f*data[i+1] } q3 <- function(data,n,p,i,f) { np <- n*p i <<- floor(np) f <<- np - i if (f==0) { qvalue <- data[i] } else { qvalue <- data[i+1] } } q4 <- function(data,n,p,i,f) { np <- n*p i <<- floor(np) f <<- np - i if (f==0) { qvalue <- (data[i]+data[i+1])/2 } else { qvalue <- data[i+1] } } q5 <- function(data,n,p,i,f) { np <- (n-1)*p i <<- floor(np) f <<- np - i if (f==0) { qvalue <- data[i+1] } else { qvalue <- data[i+1] + f*(data[i+2]-data[i+1]) } } q6 <- function(data,n,p,i,f) { np <- n*p+0.5 i <<- floor(np) f <<- np - i qvalue <- data[i] } q7 <- function(data,n,p,i,f) { np <- (n+1)*p i <<- floor(np) f <<- np - i if (f==0) { qvalue <- data[i] } else { qvalue <- f*data[i] + (1-f)*data[i+1] } } q8 <- function(data,n,p,i,f) { np <- (n+1)*p i <<- floor(np) f <<- np - i if (f==0) { qvalue <- data[i] } else { if (f == 0.5) { qvalue <- (data[i]+data[i+1])/2 } else { if (f < 0.5) { qvalue <- data[i] } else { qvalue <- data[i+1] } } } } midmean <- function(x,def) { x <-sort(x[!is.na(x)]) n<-length(x) if (def==1) { qvalue1 <- q1(x,n,0.25,i,f) qvalue3 <- q1(x,n,0.75,i,f) } if (def==2) { qvalue1 <- q2(x,n,0.25,i,f) qvalue3 <- q2(x,n,0.75,i,f) } if (def==3) { qvalue1 <- q3(x,n,0.25,i,f) qvalue3 <- q3(x,n,0.75,i,f) } if (def==4) { qvalue1 <- q4(x,n,0.25,i,f) qvalue3 <- q4(x,n,0.75,i,f) } if (def==5) { qvalue1 <- q5(x,n,0.25,i,f) qvalue3 <- q5(x,n,0.75,i,f) } if (def==6) { qvalue1 <- q6(x,n,0.25,i,f) qvalue3 <- q6(x,n,0.75,i,f) } if (def==7) { qvalue1 <- q7(x,n,0.25,i,f) qvalue3 <- q7(x,n,0.75,i,f) } if (def==8) { qvalue1 <- q8(x,n,0.25,i,f) qvalue3 <- q8(x,n,0.75,i,f) } midm <- 0 myn <- 0 roundno4 <- round(n/4) round3no4 <- round(3*n/4) for (i in 1:n) { if ((x[i]>=qvalue1) & (x[i]<=qvalue3)){ midm = midm + x[i] myn = myn + 1 } } midm = midm / myn return(midm) } (arm <- mean(x)) sqrtn <- sqrt(length(x)) (armse <- sd(x) / sqrtn) (armose <- arm / armse) (geo <- geomean(x)) (har <- harmean(x)) (qua <- quamean(x)) (win <- winmean(x)) (tri <- trimean(x)) (midr <- midrange(x)) midm <- array(NA,dim=8) for (j in 1:8) midm[j] <- midmean(x,j) midm bitmap(file='test1.png') lb <- win[,1] - 2*win[,2] ub <- win[,1] + 2*win[,2] if ((ylimmin == '') | (ylimmax == '')) plot(win[,1],type='b',main=main, xlab='j', pch=19, ylab='Winsorized Mean(j/n)', ylim=c(min(lb),max(ub))) else plot(win[,1],type='l',main=main, xlab='j', pch=19, ylab='Winsorized Mean(j/n)', ylim=c(ylimmin,ylimmax)) lines(ub,lty=3) lines(lb,lty=3) grid() dev.off() bitmap(file='test2.png') lb <- tri[,1] - 2*tri[,2] ub <- tri[,1] + 2*tri[,2] if ((ylimmin == '') | (ylimmax == '')) plot(tri[,1],type='b',main=main, xlab='j', pch=19, ylab='Trimmed Mean(j/n)', ylim=c(min(lb),max(ub))) else plot(tri[,1],type='l',main=main, xlab='j', pch=19, ylab='Trimmed Mean(j/n)', ylim=c(ylimmin,ylimmax)) lines(ub,lty=3) lines(lb,lty=3) grid() dev.off() load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Central Tendency - Ungrouped Data',4,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Measure',header=TRUE) a<-table.element(a,'Value',header=TRUE) a<-table.element(a,'S.E.',header=TRUE) a<-table.element(a,'Value/S.E.',header=TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,hyperlink('http://www.xycoon.com/arithmetic_mean.htm', 'Arithmetic Mean', 'click to view the definition of the Arithmetic Mean'),header=TRUE) a<-table.element(a,arm) a<-table.element(a,hyperlink('http://www.xycoon.com/arithmetic_mean_standard_error.htm', armse, 'click to view the definition of the Standard Error of the Arithmetic Mean')) a<-table.element(a,armose) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,hyperlink('http://www.xycoon.com/geometric_mean.htm', 'Geometric Mean', 'click to view the definition of the Geometric Mean'),header=TRUE) a<-table.element(a,geo) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,hyperlink('http://www.xycoon.com/harmonic_mean.htm', 'Harmonic Mean', 'click to view the definition of the Harmonic Mean'),header=TRUE) a<-table.element(a,har) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,hyperlink('http://www.xycoon.com/quadratic_mean.htm', 'Quadratic Mean', 'click to view the definition of the Quadratic Mean'),header=TRUE) a<-table.element(a,qua) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) for (j in 1:length(win[,1])) { a<-table.row.start(a) mylabel <- paste('Winsorized Mean (',j) mylabel <- paste(mylabel,'/') mylabel <- paste(mylabel,length(win[,1])) mylabel <- paste(mylabel,')') a<-table.element(a,hyperlink('http://www.xycoon.com/winsorized_mean.htm', mylabel, 'click to view the definition of the Winsorized Mean'),header=TRUE) a<-table.element(a,win[j,1]) a<-table.element(a,win[j,2]) a<-table.element(a,win[j,1]/win[j,2]) a<-table.row.end(a) } for (j in 1:length(tri[,1])) { a<-table.row.start(a) mylabel <- paste('Trimmed Mean (',j) mylabel <- paste(mylabel,'/') mylabel <- paste(mylabel,length(tri[,1])) mylabel <- paste(mylabel,')') a<-table.element(a,hyperlink('http://www.xycoon.com/arithmetic_mean.htm', mylabel, 'click to view the definition of the Trimmed Mean'),header=TRUE) a<-table.element(a,tri[j,1]) a<-table.element(a,tri[j,2]) a<-table.element(a,tri[j,1]/tri[j,2]) a<-table.row.end(a) } a<-table.row.start(a) a<-table.element(a,hyperlink('http://www.xycoon.com/median_1.htm', 'Median', 'click to view the definition of the Median'),header=TRUE) a<-table.element(a,median(x)) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,hyperlink('http://www.xycoon.com/midrange.htm', 'Midrange', 'click to view the definition of the Midrange'),header=TRUE) a<-table.element(a,midr) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) a<-table.row.start(a) mymid <- hyperlink('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean') mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/method_1.htm','Weighted Average at Xnp',''),sep=' - ') a<-table.element(a,mylabel,header=TRUE) a<-table.element(a,midm[1]) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) a<-table.row.start(a) mymid <- hyperlink('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean') mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/method_2.htm','Weighted Average at X(n+1)p',''),sep=' - ') a<-table.element(a,mylabel,header=TRUE) a<-table.element(a,midm[2]) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) a<-table.row.start(a) mymid <- hyperlink('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean') mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/method_3.htm','Empirical Distribution Function',''),sep=' - ') a<-table.element(a,mylabel,header=TRUE) a<-table.element(a,midm[3]) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) a<-table.row.start(a) mymid <- hyperlink('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean') mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/method_4.htm','Empirical Distribution Function - Averaging',''),sep=' - ') a<-table.element(a,mylabel,header=TRUE) a<-table.element(a,midm[4]) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) a<-table.row.start(a) mymid <- hyperlink('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean') mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/method_5.htm','Empirical Distribution Function - Interpolation',''),sep=' - ') a<-table.element(a,mylabel,header=TRUE) a<-table.element(a,midm[5]) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) a<-table.row.start(a) mymid <- hyperlink('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean') mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/method_6.htm','Closest Observation',''),sep=' - ') a<-table.element(a,mylabel,header=TRUE) a<-table.element(a,midm[6]) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) a<-table.row.start(a) mymid <- hyperlink('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean') mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/method_7.htm','True Basic - Statistics Graphics Toolkit',''),sep=' - ') a<-table.element(a,mylabel,header=TRUE) a<-table.element(a,midm[7]) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) a<-table.row.start(a) mymid <- hyperlink('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean') mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/method_8.htm','MS Excel (old versions)',''),sep=' - ') a<-table.element(a,mylabel,header=TRUE) a<-table.element(a,midm[8]) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Number of observations',header=TRUE) a<-table.element(a,length(x)) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) a<-table.end(a) table.save(a,file='mytable.tab')

Copyright

This work is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 3.0 License.

Software written by Ed van Stee & Patrick Wessa

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We 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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