*Unverified author*

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

Title produced by software: Central Tendency

Date of computation: Fri, 06 May 2011 11:35:25 +0000

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2011/May/06/t1304681499tlfum57ade5gja1.htm/, Retrieved Fri, 06 May 2011 13:31:41 +0200

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords:

KDGP1W52

Dataseries X:

» Textbox « » Textfile « » CSV «

116 111 104 100 93 91 119 139 134 124 113 109 109 106 101 98 93 91 122 139 140 132 117 114 113 110 107 103 98 98 137 148 147 139 130 128 127 123 118 114 108 111 151 159 158 148 138 137 136 133 126 120 114 116 153 162 161 149 139 135 130 127 122 117 112 113 149 157 157 147 137 132 125 123 117 114 111 112 144 150 149 134 123 116 117 111 105 102 95 93 124 130 124 115 106 105 105 101 95 93 84 87 116 120 117 109 105 107 109 109 108 107 99 103 131 137 135 124 118 121 121 118 113 107 100 102 130 136 133 120 112 109 110

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' @ www.wessa.org Central Tendency - Ungrouped Data Measure Value S.E. Value/S.E. Arithmetic Mean 120.338345864662 1.54066497917008 78.1080556069271 Geometric Mean 119.060117496799 Harmonic Mean 117.806473981964 Quadratic Mean 121.633215437825 Winsorized Mean ( 1 / 44 ) 120.353383458647 1.53526909897892 78.392370131524 Winsorized Mean ( 2 / 44 ) 120.383458646617 1.5200011468751 79.199584088543 Winsorized Mean ( 3 / 44 ) 120.360902255639 1.5157086756558 79.4089947420552 Winsorized Mean ( 4 / 44 ) 120.390977443609 1.50153087318997 80.1788225558364 Winsorized Mean ( 5 / 44 ) 120.390977443609 1.50153087318997 80.1788225558364 Winsorized Mean ( 6 / 44 ) 120.210526315789 1.46959976570419 81.7981392765042 Winsorized Mean ( 7 / 44 ) 120.105263157895 1.45221851471422 82.7046769759232 Winsorized Mean ( 8 / 44 ) 120.165413533835 1.42605304997256 84.2643361242042 Winsorized Mean ( 9 / 44 ) 120.097744360902 1.41545615907413 84.8473784164815 Winsorized Mean ( 10 / 44 ) 120.323308270677 1.38653604848077 86.7797908337942 Winsorized Mean ( 11 / 44 ) 120.323308270677 1.38653604848077 86.7797908337942 Winsorized Mean ( 12 / 44 ) 120.233082706767 1.37255290718824 87.5981407179939 Winsorized Mean ( 13 / 44 ) 120.330827067669 1.36075087683004 88.4297259083808 Winsorized Mean ( 14 / 44 ) 120.330827067669 1.33232425665462 90.3164724853186 Winsorized Mean ( 15 / 44 ) 120.330827067669 1.33232425665462 90.3164724853186 Winsorized Mean ( 16 / 44 ) 120.09022556391 1.26525589583956 94.9137846018286 Winsorized Mean ( 17 / 44 ) 119.578947368421 1.19547689973821 100.026146381086 Winsorized Mean ( 18 / 44 ) 119.578947368421 1.16242975696839 102.869826457542 Winsorized Mean ( 19 / 44 ) 119.578947368421 1.16242975696839 102.869826457542 Winsorized Mean ( 20 / 44 ) 119.729323308271 1.14549489641231 104.521917717192 Winsorized Mean ( 21 / 44 ) 119.729323308271 1.14549489641231 104.521917717192 Winsorized Mean ( 22 / 44 ) 119.729323308271 1.1065438353093 108.201157051138 Winsorized Mean ( 23 / 44 ) 119.729323308271 1.06675821723926 112.236607483677 Winsorized Mean ( 24 / 44 ) 119.729323308271 1.06675821723926 112.236607483677 Winsorized Mean ( 25 / 44 ) 119.729323308271 1.06675821723926 112.236607483677 Winsorized Mean ( 26 / 44 ) 119.729323308271 1.06675821723926 112.236607483677 Winsorized Mean ( 27 / 44 ) 119.729323308271 1.02108818308844 117.256594769446 Winsorized Mean ( 28 / 44 ) 119.729323308271 1.02108818308844 117.256594769446 Winsorized Mean ( 29 / 44 ) 119.729323308271 0.973043358012367 123.04623665778 Winsorized Mean ( 30 / 44 ) 119.729323308271 0.973043358012367 123.04623665778 Winsorized Mean ( 31 / 44 ) 119.496240601504 0.94564175559925 126.365232810368 Winsorized Mean ( 32 / 44 ) 119.496240601504 0.94564175559925 126.365232810368 Winsorized Mean ( 33 / 44 ) 119.496240601504 0.892465108018556 133.89457977445 Winsorized Mean ( 34 / 44 ) 119.496240601504 0.892465108018556 133.89457977445 Winsorized Mean ( 35 / 44 ) 119.496240601504 0.837138094418279 142.74376163056 Winsorized Mean ( 36 / 44 ) 119.496240601504 0.837138094418279 142.74376163056 Winsorized Mean ( 37 / 44 ) 119.218045112782 0.80598823591871 147.915366254559 Winsorized Mean ( 38 / 44 ) 118.932330827068 0.774699280820048 153.52064184334 Winsorized Mean ( 39 / 44 ) 118.932330827068 0.774699280820048 153.52064184334 Winsorized Mean ( 40 / 44 ) 118.932330827068 0.774699280820048 153.52064184334 Winsorized Mean ( 41 / 44 ) 119.240601503759 0.745240107580854 160.002930989356 Winsorized Mean ( 42 / 44 ) 118.609022556391 0.677472904209662 175.075669918873 Winsorized Mean ( 43 / 44 ) 118.609022556391 0.612938139772862 193.508960953783 Winsorized Mean ( 44 / 44 ) 118.609022556391 0.612938139772862 193.508960953783 Trimmed Mean ( 1 / 44 ) 120.297709923664 1.50581938906057 79.8885382919086 Trimmed Mean ( 2 / 44 ) 120.240310077519 1.47347243828333 81.6033655964446 Trimmed Mean ( 3 / 44 ) 120.165354330709 1.44670620811012 83.0613386858168 Trimmed Mean ( 4 / 44 ) 120.096 1.41896936701119 84.6360765722247 Trimmed Mean ( 5 / 44 ) 120.016260162602 1.39284666178622 86.1661685060793 Trimmed Mean ( 6 / 44 ) 119.933884297521 1.36397649986169 87.9295825915493 Trimmed Mean ( 7 / 44 ) 119.882352941176 1.3394827347396 89.4989907910104 Trimmed Mean ( 8 / 44 ) 119.846153846154 1.31595747974926 91.0714485007445 Trimmed Mean ( 9 / 44 ) 119.8 1.29472319887635 92.5294303090964 Trimmed Mean ( 10 / 44 ) 119.761061946903 1.27297311290886 94.0798047754816 Trimmed Mean ( 11 / 44 ) 119.693693693694 1.2533194446226 95.5013458119102 Trimmed Mean ( 12 / 44 ) 119.623853211009 1.23137079652576 97.1468980330874 Trimmed Mean ( 13 / 44 ) 119.560747663551 1.2089259497807 98.8983218411684 Trimmed Mean ( 14 / 44 ) 119.485714285714 1.18538986691202 100.798663478521 Trimmed Mean ( 15 / 44 ) 119.407766990291 1.16286838337856 102.683819335915 Trimmed Mean ( 16 / 44 ) 119.326732673267 1.13748975936124 104.903566551909 Trimmed Mean ( 17 / 44 ) 119.262626262626 1.11783445879052 106.690776371008 Trimmed Mean ( 18 / 44 ) 119.237113402062 1.10448293751048 107.957406450138 Trimmed Mean ( 19 / 44 ) 119.210526315789 1.09318306480595 109.049005746307 Trimmed Mean ( 20 / 44 ) 119.182795698925 1.08022583441294 110.331369517464 Trimmed Mean ( 21 / 44 ) 119.142857142857 1.06728135088487 111.632098737674 Trimmed Mean ( 22 / 44 ) 119.101123595506 1.05238735162007 113.172325201513 Trimmed Mean ( 23 / 44 ) 119.057471264368 1.03975460291328 114.505356293477 Trimmed Mean ( 24 / 44 ) 119.011764705882 1.0296030234491 115.589952627762 Trimmed Mean ( 25 / 44 ) 118.963855421687 1.0176875054225 116.896252324821 Trimmed Mean ( 26 / 44 ) 118.913580246914 1.00372724070014 118.472006562228 Trimmed Mean ( 27 / 44 ) 118.860759493671 0.987381302315383 120.379795743494 Trimmed Mean ( 28 / 44 ) 118.805194805195 0.973686429767291 122.015867915083 Trimmed Mean ( 29 / 44 ) 118.746666666667 0.957491718183708 124.018479127862 Trimmed Mean ( 30 / 44 ) 118.684931506849 0.944195741516884 125.699498830802 Trimmed Mean ( 31 / 44 ) 118.619718309859 0.928287013563447 127.783451213553 Trimmed Mean ( 32 / 44 ) 118.565217391304 0.912982582307338 129.865804330746 Trimmed Mean ( 33 / 44 ) 118.507462686567 0.894572087372654 132.47391055384 Trimmed Mean ( 34 / 44 ) 118.446153846154 0.879529695466333 134.669874657675 Trimmed Mean ( 35 / 44 ) 118.380952380952 0.8611869098614 137.462554325175 Trimmed Mean ( 36 / 44 ) 118.311475409836 0.846574900454819 139.75311026381 Trimmed Mean ( 37 / 44 ) 118.237288135593 0.828460361780105 142.719306306385 Trimmed Mean ( 38 / 44 ) 118.175438596491 0.811154537431032 145.687946184409 Trimmed Mean ( 39 / 44 ) 118.127272727273 0.79478711778416 148.627563386542 Trimmed Mean ( 40 / 44 ) 118.075471698113 0.774151090196653 152.522515557162 Trimmed Mean ( 41 / 44 ) 118.019607843137 0.748064271160577 157.766668444193 Trimmed Mean ( 42 / 44 ) 117.938775510204 0.719864029149739 163.834794814663 Trimmed Mean ( 43 / 44 ) 117.893617021277 0.698375306670328 168.811262218538 Trimmed Mean ( 44 / 44 ) 117.844444444444 0.68309719168537 172.514901069485 Median 117 Midrange 123 Midmean - Weighted Average at Xnp 118.507462686567 Midmean - Weighted Average at X(n+1)p 118.507462686567 Midmean - Empirical Distribution Function 118.507462686567 Midmean - Empirical Distribution Function - Averaging 118.507462686567 Midmean - Empirical Distribution Function - Interpolation 118.507462686567 Midmean - Closest Observation 117.859154929577 Midmean - True Basic - Statistics Graphics Toolkit 118.507462686567 Midmean - MS Excel (old versions) 118.507462686567 Number of observations 133

Charts produced by software:

http://www.freestatistics.org/blog/date/2011/May/06/t1304681499tlfum57ade5gja1/1mvuz1304681723.png (open in new window) http://www.freestatistics.org/blog/date/2011/May/06/t1304681499tlfum57ade5gja1/1mvuz1304681723.ps (open in new window) http://www.freestatistics.org/blog/date/2011/May/06/t1304681499tlfum57ade5gja1/2sckb1304681723.png (open in new window) http://www.freestatistics.org/blog/date/2011/May/06/t1304681499tlfum57ade5gja1/2sckb1304681723.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.

FreeStatistics.org is powered by