Robuustheid consumptieprijsindex koffie

*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 12:36:50 +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/t1287578193d5h0ibrjiqsqx7w.htm/, Retrieved Wed, 20 Oct 2010 14:36:35 +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/t1287578193d5h0ibrjiqsqx7w.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 - Natasha Van Linden

Dataseries X:

» Textbox « » Textfile « » CSV «

97 100,7 101,4 101,5 101,8 101,5 102,2 101,8 98,5 98,4 97,5 97,7 98,3 99,6 99,4 96,7 96,9 96,1 97,9 99,2 97,8 94,9 93,3 91,5 89,1 92,3 91,8 92,1 94,4 92,8 92,6 92,3 92,1 89,8 87,4 87,7 86,3 89,1 90,4 87,1 86,7 84,4 88,4 88,9 88,5 87,2 86,2 83,4 87,5 85,7 87,4 86,8 87,9 85,9 87,7 87 86,8 86,2 86,1 87,5 85,7 88,9 89,8 91,4 95,2 94,1 96,8 96,1 96,6 94,2 93,9 96,5 93,4 95 95,2 94 97 96,9 96,3 96,3 97,3 95,7 96,4 95,1 94,6 95,9 96,2 94,3 98,3 95,9 92,1 94,6 94,7 96,7 97,5 96,2 97,1 95,9 94,5 99,4 101,3 101,4 100,9 101,4 103,1 102,4 101,1 102 103,9 101,7 101,2 101,9 101,1 103,1 103,3 101,4 102,8 103 102,6 102,2

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 7 seconds R Server 'Gwilym Jenkins' @ 72.249.127.135 Central Tendency - Ungrouped Data Measure Value S.E. Value/S.E. Arithmetic Mean 94.905 0.496676418793961 191.080140729149 Geometric Mean 94.7484804967084 Harmonic Mean 94.590231663272 Quadratic Mean 95.059533100754 Winsorized Mean ( 1 / 40 ) 94.9083333333333 0.494383841584446 191.972967864731 Winsorized Mean ( 2 / 40 ) 94.9266666666667 0.490263367930585 193.623821146080 Winsorized Mean ( 3 / 40 ) 94.9266666666667 0.490263367930585 193.623821146080 Winsorized Mean ( 4 / 40 ) 94.93 0.48875391779183 194.228622102693 Winsorized Mean ( 5 / 40 ) 94.93 0.486326480235398 195.198089879973 Winsorized Mean ( 6 / 40 ) 94.925 0.484220546667658 196.036704045835 Winsorized Mean ( 7 / 40 ) 94.9133333333333 0.482683229361275 196.636898818569 Winsorized Mean ( 8 / 40 ) 94.9066666666667 0.479954965985785 197.740774432319 Winsorized Mean ( 9 / 40 ) 94.9366666666667 0.47551083151388 199.651954014207 Winsorized Mean ( 10 / 40 ) 94.9283333333333 0.472183057089544 201.041379837844 Winsorized Mean ( 11 / 40 ) 94.9191666666667 0.471035416834267 201.511740464441 Winsorized Mean ( 12 / 40 ) 94.9291666666667 0.46691879318618 203.309800444923 Winsorized Mean ( 13 / 40 ) 94.94 0.465378975713788 204.005777988537 Winsorized Mean ( 14 / 40 ) 94.94 0.462293030380489 205.367578052951 Winsorized Mean ( 15 / 40 ) 94.94 0.455748222790864 208.316775035602 Winsorized Mean ( 16 / 40 ) 94.94 0.455748222790864 208.316775035602 Winsorized Mean ( 17 / 40 ) 94.94 0.452076441814543 210.008731308648 Winsorized Mean ( 18 / 40 ) 94.94 0.452076441814543 210.008731308648 Winsorized Mean ( 19 / 40 ) 94.9716666666667 0.447725630227544 212.120236713721 Winsorized Mean ( 20 / 40 ) 94.9716666666667 0.447725630227544 212.120236713721 Winsorized Mean ( 21 / 40 ) 94.9891666666667 0.440863991033632 215.461386274617 Winsorized Mean ( 22 / 40 ) 95.0625 0.426439008055122 222.921679781490 Winsorized Mean ( 23 / 40 ) 95.0625 0.421614979781875 225.472301883537 Winsorized Mean ( 24 / 40 ) 95.1425 0.41127945221604 231.332976853954 Winsorized Mean ( 25 / 40 ) 95.1008333333333 0.406244148129942 234.097731059289 Winsorized Mean ( 26 / 40 ) 95.1008333333333 0.395525562201495 240.441686762297 Winsorized Mean ( 27 / 40 ) 94.8533333333333 0.367318493704025 258.231847726577 Winsorized Mean ( 28 / 40 ) 94.97 0.341073852045301 278.444094821394 Winsorized Mean ( 29 / 40 ) 94.97 0.341073852045301 278.444094821394 Winsorized Mean ( 30 / 40 ) 95.07 0.31675127868569 300.140856240512 Winsorized Mean ( 31 / 40 ) 95.1475 0.265871439889695 357.870330259899 Winsorized Mean ( 32 / 40 ) 95.1475 0.259904535641568 366.086339221171 Winsorized Mean ( 33 / 40 ) 95.2025 0.247376889846752 384.847994729731 Winsorized Mean ( 34 / 40 ) 95.2875 0.237672427456593 400.919454644788 Winsorized Mean ( 35 / 40 ) 95.1708333333333 0.225519617341351 422.006894368223 Winsorized Mean ( 36 / 40 ) 95.1408333333333 0.222487515255226 427.623245395108 Winsorized Mean ( 37 / 40 ) 95.1716666666667 0.212350403211683 448.182180147753 Winsorized Mean ( 38 / 40 ) 95.1083333333333 0.206092712993949 461.483241943278 Winsorized Mean ( 39 / 40 ) 95.2058333333333 0.195033918738383 488.150132803524 Winsorized Mean ( 40 / 40 ) 95.2058333333333 0.181030723955557 525.909808308044 Trimmed Mean ( 1 / 40 ) 94.9262711864407 0.489596871196927 193.886596853392 Trimmed Mean ( 2 / 40 ) 94.944827586207 0.484265692168126 196.059372203564 Trimmed Mean ( 3 / 40 ) 94.9543859649123 0.480679570484597 197.541963077782 Trimmed Mean ( 4 / 40 ) 94.9642857142857 0.4766437675223 199.23534552425 Trimmed Mean ( 5 / 40 ) 94.9736363636364 0.472573345376333 200.971208581399 Trimmed Mean ( 6 / 40 ) 94.9833333333333 0.468612432219123 202.690596328266 Trimmed Mean ( 7 / 40 ) 94.9943396226415 0.464604924842713 204.462618761092 Trimmed Mean ( 8 / 40 ) 95.0076923076923 0.460368663167153 206.373065564622 Trimmed Mean ( 9 / 40 ) 95.0225490196078 0.456059755522403 208.355479449754 Trimmed Mean ( 10 / 40 ) 95.034 0.451923431433675 210.287835039922 Trimmed Mean ( 11 / 40 ) 95.0469387755102 0.447728925800641 212.286795197663 Trimmed Mean ( 12 / 40 ) 95.0614583333333 0.443098563823476 214.537951811562 Trimmed Mean ( 13 / 40 ) 95.0755319148936 0.438401158498265 216.868797155037 Trimmed Mean ( 14 / 40 ) 95.0891304347826 0.43323044728328 219.488567876685 Trimmed Mean ( 15 / 40 ) 95.1033333333333 0.427717718760076 222.350698046907 Trimmed Mean ( 16 / 40 ) 95.1181818181818 0.422259884760951 225.259810962223 Trimmed Mean ( 17 / 40 ) 95.1337209302326 0.415956072292406 228.710979998282 Trimmed Mean ( 18 / 40 ) 95.15 0.409162487870292 232.548199849062 Trimmed Mean ( 19 / 40 ) 95.1670731707317 0.401292907769503 237.151146527101 Trimmed Mean ( 20 / 40 ) 95.1825 0.392770003076171 242.336480012556 Trimmed Mean ( 21 / 40 ) 95.198717948718 0.382846888750041 248.660027666759 Trimmed Mean ( 22 / 40 ) 95.2144736842105 0.372236973885734 255.789941257793 Trimmed Mean ( 23 / 40 ) 95.2256756756757 0.361903217146941 263.124700648936 Trimmed Mean ( 24 / 40 ) 95.2375 0.350432537894277 271.771281777301 Trimmed Mean ( 25 / 40 ) 95.2442857142857 0.338438967370372 281.422338728669 Trimmed Mean ( 26 / 40 ) 95.2544117647059 0.324919344510166 293.163252278215 Trimmed Mean ( 27 / 40 ) 95.2651515151515 0.310443643930866 306.867778991689 Trimmed Mean ( 28 / 40 ) 95.29375 0.297391728664026 320.431743102232 Trimmed Mean ( 29 / 40 ) 95.316129032258 0.286079219209648 333.18089057845 Trimmed Mean ( 30 / 40 ) 95.34 0.272249470176343 350.193518974512 Trimmed Mean ( 31 / 40 ) 95.3586206896552 0.259752715048267 367.113085504941 Trimmed Mean ( 32 / 40 ) 95.3732142857143 0.253232236097395 376.623512691461 Trimmed Mean ( 33 / 40 ) 95.3888888888889 0.246096949112439 387.606954222365 Trimmed Mean ( 34 / 40 ) 95.401923076923 0.239382223764453 398.533865951536 Trimmed Mean ( 35 / 40 ) 95.41 0.232699333028345 410.0140673303 Trimmed Mean ( 36 / 40 ) 95.4270833333333 0.22626201592898 421.754764897376 Trimmed Mean ( 37 / 40 ) 95.4478260869565 0.218442867323230 436.946407344684 Trimmed Mean ( 38 / 40 ) 95.4681818181818 0.210425239627350 453.691686354974 Trimmed Mean ( 39 / 40 ) 95.495238095238 0.201012315538838 475.071578769944 Trimmed Mean ( 40 / 40 ) 95.5175 0.191414689439795 499.008201928215 Median 95.9 Midrange 93.65 Midmean - Weighted Average at Xnp 95.1612903225806 Midmean - Weighted Average at X(n+1)p 95.34 Midmean - Empirical Distribution Function 95.1612903225806 Midmean - Empirical Distribution Function - Averaging 95.34 Midmean - Empirical Distribution Function - Interpolation 95.34 Midmean - Closest Observation 95.1612903225806 Midmean - True Basic - Statistics Graphics Toolkit 95.34 Midmean - MS Excel (old versions) 95.29375 Number of observations 120

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Oct/20/t1287578193d5h0ibrjiqsqx7w/1j7z31287578203.png (open in new window) http://www.freestatistics.org/blog/date/2010/Oct/20/t1287578193d5h0ibrjiqsqx7w/1j7z31287578203.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Oct/20/t1287578193d5h0ibrjiqsqx7w/2byy61287578203.png (open in new window) http://www.freestatistics.org/blog/date/2010/Oct/20/t1287578193d5h0ibrjiqsqx7w/2byy61287578203.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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