ct residuals: goudprijs

*Unverified author*

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

Title produced by software: Central Tendency

Date of computation: Wed, 30 Dec 2009 07:34:46 -0700

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2009/Dec/30/t1262183769sdybvjhyjl2o37l.htm/, Retrieved Wed, 30 Dec 2009 15:36:11 +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/2009/Dec/30/t1262183769sdybvjhyjl2o37l.htm/}, year = {2009}, } @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 = {2009}, 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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10.0699947754242 65.7731821094984 -150.198460641018 -247.385699879324 -617.482560413075 51.0478428322415 150.198460641018 84.4252785302456 543.855864020419 224.806846318910 -171.795624916197 -268.982864154503 268.980915214612 48.2372215011231 -15.8551476059929 -9.99671370398755 395.817726508698 647.094559970665 -166.144852394007 167.617926105329 -48.5310341586937 -213.622033975345 -627.664384516658 72.1940493853472 218.805950614653 -100.619843111337 -115.427984589998 278.048375417337 248.424972151986 -199.151424986032 -540.902975307326 -485.050018565342 165.142113813998 -36.6168306733252 221.913381911367 443.190215373332 423.377418308653 -416.046458411329 319.620664685339 -97.8606247660136 -149.337258631349 -258.90379688133 446.007394166028 322.720154100021 -609.526104714676 100.143756962003 29.7130337919953 57.8513135939775 -11.4823848833566 234.481837167355 10.6151875253181 -238.047006127332 -200.47499071 etc...

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 112.820711157852 56.065539959031 2.01230044765990 Geometric Mean NaN Harmonic Mean -4566.78513243971 Quadratic Mean 598.74572037294 Winsorized Mean ( 1 / 37 ) 108.801595407204 51.9641635808565 2.09378132754717 Winsorized Mean ( 2 / 37 ) 114.668471576057 49.1771636852914 2.33174227594491 Winsorized Mean ( 3 / 37 ) 108.947097216762 44.34210214291 2.45696735047961 Winsorized Mean ( 4 / 37 ) 108.206559185743 43.7304060886818 2.47440096866031 Winsorized Mean ( 5 / 37 ) 114.911844702410 42.5400047729598 2.70126543980674 Winsorized Mean ( 6 / 37 ) 107.538336055819 40.7291956327939 2.64032555480257 Winsorized Mean ( 7 / 37 ) 107.840522166523 40.5651530222711 2.65845224612654 Winsorized Mean ( 8 / 37 ) 107.156290715015 40.2550998949498 2.66193081111836 Winsorized Mean ( 9 / 37 ) 106.848899178588 39.2950307393693 2.71914532621900 Winsorized Mean ( 10 / 37 ) 108.036935479067 38.5769262077787 2.80055841922632 Winsorized Mean ( 11 / 37 ) 104.753830255595 37.9478297501529 2.76046959589758 Winsorized Mean ( 12 / 37 ) 101.606251950650 35.8207676199762 2.83651799505231 Winsorized Mean ( 13 / 37 ) 96.7501035437604 34.8715375292001 2.77447197338934 Winsorized Mean ( 14 / 37 ) 101.373231406938 33.7196076820721 3.00635856629006 Winsorized Mean ( 15 / 37 ) 103.280492221902 33.2299173704649 3.10805744927006 Winsorized Mean ( 16 / 37 ) 100.869353568490 32.6972648307764 3.08494774992758 Winsorized Mean ( 17 / 37 ) 117.970770614391 30.3823741724682 3.88286872989976 Winsorized Mean ( 18 / 37 ) 115.746902176661 29.5283053278683 3.9198626840065 Winsorized Mean ( 19 / 37 ) 112.467068268806 28.2493905596781 3.98122104727230 Winsorized Mean ( 20 / 37 ) 112.110973981849 27.7272284853929 4.0433530542337 Winsorized Mean ( 21 / 37 ) 109.795293404033 26.8505385220567 4.08912816828013 Winsorized Mean ( 22 / 37 ) 109.646187697524 26.3588655454018 4.15974608272362 Winsorized Mean ( 23 / 37 ) 100.342932259775 24.7782367302757 4.04963974442821 Winsorized Mean ( 24 / 37 ) 104.026817408596 24.3172712222019 4.27789847216159 Winsorized Mean ( 25 / 37 ) 106.666059997339 23.9274777760771 4.45788983676266 Winsorized Mean ( 26 / 37 ) 106.730839724393 23.8598762871912 4.47323525234245 Winsorized Mean ( 27 / 37 ) 108.565624239161 22.4788154138899 4.82968618408945 Winsorized Mean ( 28 / 37 ) 105.819948435498 21.7896320165772 4.8564357743624 Winsorized Mean ( 29 / 37 ) 107.105906627864 20.9595060296699 5.11013506121025 Winsorized Mean ( 30 / 37 ) 102.072414343080 20.2798467400579 5.03319456263253 Winsorized Mean ( 31 / 37 ) 89.2951837920356 18.2357704650615 4.89670474648269 Winsorized Mean ( 32 / 37 ) 95.9108420057002 17.2814675801419 5.54992459760254 Winsorized Mean ( 33 / 37 ) 92.5023707169386 15.8844239844750 5.82346396742795 Winsorized Mean ( 34 / 37 ) 88.4882368111733 15.2761434416563 5.79257697789588 Winsorized Mean ( 35 / 37 ) 85.8072478154415 14.9356093081284 5.74514544704532 Winsorized Mean ( 36 / 37 ) 94.3515206956668 13.3682196353053 7.05789725705028 Winsorized Mean ( 37 / 37 ) 95.1611227503332 12.4263664184736 7.65800070154557 Trimmed Mean ( 1 / 37 ) 109.373727601330 48.3653616302987 2.26140617819370 Trimmed Mean ( 2 / 37 ) 109.967247914863 44.1458192764267 2.49100027403011 Trimmed Mean ( 3 / 37 ) 107.482315408232 41.0370101551870 2.61915561103923 Trimmed Mean ( 4 / 37 ) 106.956131651770 39.6502599688522 2.6974887866004 Trimmed Mean ( 5 / 37 ) 106.612573591693 38.2910565436071 2.78426826562696 Trimmed Mean ( 6 / 37 ) 104.751524918380 37.0936550588929 2.82397420130393 Trimmed Mean ( 7 / 37 ) 104.751524918380 36.1932844185256 2.89422545097242 Trimmed Mean ( 8 / 37 ) 103.615695229832 35.2091544957256 2.94286235252854 Trimmed Mean ( 9 / 37 ) 103.087461225994 34.1543366677352 3.01828321916667 Trimmed Mean ( 10 / 37 ) 102.577669269049 33.1398748317831 3.09529440861591 Trimmed Mean ( 11 / 37 ) 101.896794494541 32.1129961027905 3.17307030986395 Trimmed Mean ( 12 / 37 ) 101.565414171159 31.0478571593473 3.27125358925395 Trimmed Mean ( 13 / 37 ) 101.560970059861 30.1905064878737 3.36400351880994 Trimmed Mean ( 14 / 37 ) 101.560970059861 29.3582361277466 3.45936893544757 Trimmed Mean ( 15 / 37 ) 102.122698429518 28.5814327981697 3.57304335127865 Trimmed Mean ( 16 / 37 ) 102.014246859092 27.7570869156416 3.67525047455916 Trimmed Mean ( 17 / 37 ) 102.117398770826 26.8803949818315 3.79895454809528 Trimmed Mean ( 18 / 37 ) 100.737222869151 26.2089523550197 3.84361883316017 Trimmed Mean ( 19 / 37 ) 99.4692819230831 25.5501989044216 3.89309227279125 Trimmed Mean ( 20 / 37 ) 98.3997828242134 24.9662376937533 3.94131402701631 Trimmed Mean ( 21 / 37 ) 97.2969261441427 24.3512578701272 3.99556058512695 Trimmed Mean ( 22 / 37 ) 96.3109142281173 23.7519631705419 4.05486121448545 Trimmed Mean ( 23 / 37 ) 95.2757985951774 23.1088396854117 4.12291572801571 Trimmed Mean ( 24 / 37 ) 94.8876330763572 22.5830543517876 4.20171831490305 Trimmed Mean ( 25 / 37 ) 94.1947031167408 22.0145562938223 4.27874638305445 Trimmed Mean ( 26 / 37 ) 93.2561806667432 21.3811050648185 4.36161650130009 Trimmed Mean ( 27 / 37 ) 92.246945069308 20.6136958470665 4.47503183095793 Trimmed Mean ( 28 / 37 ) 92.246945069308 19.9064407923760 4.63402503900333 Trimmed Mean ( 29 / 37 ) 89.9206967081162 19.1526771806758 4.6949413839044 Trimmed Mean ( 30 / 37 ) 88.630934503186 18.3608148249619 4.82717871445935 Trimmed Mean ( 31 / 37 ) 88.630934503186 17.4988239362767 5.06496521285901 Trimmed Mean ( 32 / 37 ) 87.488036161315 16.8308437270153 5.19807786111681 Trimmed Mean ( 33 / 37 ) 86.8387782108104 16.1646528892575 5.3721399899976 Trimmed Mean ( 34 / 37 ) 86.3957487758701 15.6011150296340 5.53779320335521 Trimmed Mean ( 35 / 37 ) 86.2291302881236 14.9934990418803 5.75110119707653 Trimmed Mean ( 36 / 37 ) 86.2634372144736 14.2607518795385 6.04901045492876 Trimmed Mean ( 37 / 37 ) 85.5894302577074 13.670681720262 6.26080191237655 Median 72.1940493853472 Midrange 300.6813149883 Midmean - Weighted Average at Xnp 86.3339009043196 Midmean - Weighted Average at X(n+1)p 92.246945069308 Midmean - Empirical Distribution Function 92.246945069308 Midmean - Empirical Distribution Function - Averaging 92.246945069308 Midmean - Empirical Distribution Function - Interpolation 91.0271650101472 Midmean - Closest Observation 86.3339009043196 Midmean - True Basic - Statistics Graphics Toolkit 92.246945069308 Midmean - MS Excel (old versions) 92.246945069308 Number of observations 111

Charts produced by software:

http://www.freestatistics.org/blog/date/2009/Dec/30/t1262183769sdybvjhyjl2o37l/1hsph1262183684.png (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/30/t1262183769sdybvjhyjl2o37l/1hsph1262183684.ps (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/30/t1262183769sdybvjhyjl2o37l/2ko2c1262183684.png (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/30/t1262183769sdybvjhyjl2o37l/2ko2c1262183684.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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