Centrummaten - Gem. prijs gebakken tong of forel - Niels Braspennincx

*Unverified author*

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

Title produced by software: Central Tendency

Date of computation: Mon, 17 Aug 2009 12:34:42 -0600

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2009/Aug/17/t1250534391w4xen9z5a831j8g.htm/, Retrieved Mon, 17 Aug 2009 20:39:51 +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/2009/Aug/17/t1250534391w4xen9z5a831j8g.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:

» Textbox « » Textfile « » CSV «

15.22 15.27 15.31 15.33 15.42 15.49 15.65 15.67 15.69 15.83 15.92 15.99 15.94 15.96 16.03 16.09 16.04 16.23 16.2 16.2 16.26 16.28 16.27 16.29 16.3 16.37 16.39 16.42 16.43 16.37 16.37 16.39 16.48 16.51 16.5 16.54 16.52 16.56 16.61 16.75 16.75 16.79 16.82 16.84 17.14 17.25 17.28 17.3 17.34 17.44 17.48 17.55 17.59 17.66 17.67 17.64 17.68 17.72 17.78 17.83 17.88 18.11 18.16 18.27 18.29 18.35 18.35 18.38 18.41 18.41 18.42 18.43 18.48 18.54 18.65 18.66 18.69 18.72 18.72 18.73 18.84 18.83 18.91 18.91 18.94 18.97 19 19.08 19.18 19.24 19.23 19.25 19.3 19.33 19.35 19.35 19.31 19.47 19.7 19.76 19.9 19.97 20.1 20.26 20.44 20.43 20.57 20.6 20.69 20.93 20.98 21.11 21.14 21.16 21.32 21.32 21.48 21.58 21.74 21.75 21.81 21.89 22.21 22.37 22.47 22.51 22.55 22.61 22.58 22.85 22.93 22.98

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 3 seconds R Server 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 Central Tendency - Ungrouped Data Measure Value S.E. Value/S.E. Arithmetic Mean 18.4202272727273 0.184113510391391 100.048210658573 Geometric Mean 18.3028857377794 Harmonic Mean 18.1890227317201 Quadratic Mean 18.5403716946494 Winsorized Mean ( 1 / 44 ) 18.4202272727273 0.183992384669431 100.114074317923 Winsorized Mean ( 2 / 44 ) 18.4196212121212 0.183688636591517 100.276323859284 Winsorized Mean ( 3 / 44 ) 18.4146212121212 0.182649569398026 100.819406652925 Winsorized Mean ( 4 / 44 ) 18.4164393939394 0.182143505096791 101.109503652919 Winsorized Mean ( 5 / 44 ) 18.4179545454545 0.181616031286397 101.411502139977 Winsorized Mean ( 6 / 44 ) 18.4234090909091 0.180426693397414 102.110218526973 Winsorized Mean ( 7 / 44 ) 18.4223484848485 0.179937045942538 102.382188105564 Winsorized Mean ( 8 / 44 ) 18.4175 0.178763855460125 103.026979098178 Winsorized Mean ( 9 / 44 ) 18.4161363636364 0.175852921260590 104.724654169072 Winsorized Mean ( 10 / 44 ) 18.3987121212121 0.171208857484466 107.463552946619 Winsorized Mean ( 11 / 44 ) 18.3937121212121 0.169994672914013 108.2016971821 Winsorized Mean ( 12 / 44 ) 18.3900757575758 0.168962301318528 108.841295449135 Winsorized Mean ( 13 / 44 ) 18.3920454545455 0.168489902701831 109.158146331730 Winsorized Mean ( 14 / 44 ) 18.3793181818182 0.165489173627181 111.060547218779 Winsorized Mean ( 15 / 44 ) 18.3690909090909 0.163702726410141 112.2100487384 Winsorized Mean ( 16 / 44 ) 18.3557575757576 0.160270421242325 114.529914088166 Winsorized Mean ( 17 / 44 ) 18.3699242424242 0.158766880149439 115.703755248787 Winsorized Mean ( 18 / 44 ) 18.3481060606061 0.155715318390321 117.831092343877 Winsorized Mean ( 19 / 44 ) 18.3495454545455 0.154865976084649 118.486616095169 Winsorized Mean ( 20 / 44 ) 18.3495454545455 0.153768712148966 119.332113783779 Winsorized Mean ( 21 / 44 ) 18.3304545454545 0.150798892832581 121.555630821542 Winsorized Mean ( 22 / 44 ) 18.3237878787879 0.149511717036317 122.557537576383 Winsorized Mean ( 23 / 44 ) 18.2837121212121 0.143874761016453 127.080747116732 Winsorized Mean ( 24 / 44 ) 18.2691666666667 0.141609377661306 129.010994669872 Winsorized Mean ( 25 / 44 ) 18.2767424242424 0.139500550576184 131.015557635818 Winsorized Mean ( 26 / 44 ) 18.2511363636364 0.136324248783804 133.880336964708 Winsorized Mean ( 27 / 44 ) 18.2490909090909 0.136073768558710 134.111747637953 Winsorized Mean ( 28 / 44 ) 18.2172727272727 0.131276015383627 138.770762305944 Winsorized Mean ( 29 / 44 ) 18.1821212121212 0.127163808411015 142.981886429145 Winsorized Mean ( 30 / 44 ) 18.1593939393939 0.123068738448273 147.554888173542 Winsorized Mean ( 31 / 44 ) 18.1453030303030 0.120981673575497 149.983898337955 Winsorized Mean ( 32 / 44 ) 18.1234848484848 0.115962016524923 156.288113915212 Winsorized Mean ( 33 / 44 ) 18.1134848484848 0.113814885602421 159.148645211128 Winsorized Mean ( 34 / 44 ) 18.0568181818182 0.107401721354749 168.124104102357 Winsorized Mean ( 35 / 44 ) 18.0276515151515 0.103965768882526 173.399876795232 Winsorized Mean ( 36 / 44 ) 18.0331060606061 0.103363128343232 174.463624985543 Winsorized Mean ( 37 / 44 ) 18.0331060606061 0.102201486269499 176.446612655454 Winsorized Mean ( 38 / 44 ) 18.0417424242424 0.100066106776126 180.298234891925 Winsorized Mean ( 39 / 44 ) 18.0801515151515 0.0953154413842743 189.687539107745 Winsorized Mean ( 40 / 44 ) 18.065 0.093845018930526 192.498229590359 Winsorized Mean ( 41 / 44 ) 18.0743181818182 0.0922205435420395 195.990150216138 Winsorized Mean ( 42 / 44 ) 18.0806818181818 0.0909008041851197 198.905631036668 Winsorized Mean ( 43 / 44 ) 18.0709090909091 0.0886467161222983 203.853113588305 Winsorized Mean ( 44 / 44 ) 18.1375757575758 0.0750672550029444 241.617676800149 Trimmed Mean ( 1 / 44 ) 18.4097692307692 0.181938362815156 101.186846720573 Trimmed Mean ( 2 / 44 ) 18.398984375 0.179677328618102 102.400144283681 Trimmed Mean ( 3 / 44 ) 18.3881746031746 0.177359768913713 103.677258466212 Trimmed Mean ( 4 / 44 ) 18.3787903225806 0.175217170435417 104.891491381291 Trimmed Mean ( 5 / 44 ) 18.3686065573770 0.173004574470980 106.174109057783 Trimmed Mean ( 6 / 44 ) 18.35775 0.170690370425582 107.550003870919 Trimmed Mean ( 7 / 44 ) 18.3455084745763 0.168387448647189 108.948194309983 Trimmed Mean ( 8 / 44 ) 18.3330172413793 0.165926602685267 110.488715761593 Trimmed Mean ( 9 / 44 ) 18.3207894736842 0.163406769011023 112.117690011044 Trimmed Mean ( 10 / 44 ) 18.3083035714286 0.161093626520966 113.650080185176 Trimmed Mean ( 11 / 44 ) 18.2974545454545 0.159251608579285 114.896513188719 Trimmed Mean ( 12 / 44 ) 18.2867592592593 0.157365425906538 116.205698640057 Trimmed Mean ( 13 / 44 ) 18.2760377358491 0.155391669839862 117.612725023699 Trimmed Mean ( 14 / 44 ) 18.2647115384615 0.153230397867628 119.197703540782 Trimmed Mean ( 15 / 44 ) 18.2541176470588 0.151199330953750 120.728825530601 Trimmed Mean ( 16 / 44 ) 18.244 0.14913812999425 122.329547787031 Trimmed Mean ( 17 / 44 ) 18.2345918367347 0.147240353215871 123.842353257606 Trimmed Mean ( 18 / 44 ) 18.2236458333333 0.145252587001124 125.461764293343 Trimmed Mean ( 19 / 44 ) 18.2139361702128 0.143369605213384 127.041824123768 Trimmed Mean ( 20 / 44 ) 18.2036956521739 0.141312758395734 128.818486446893 Trimmed Mean ( 21 / 44 ) 18.193 0.139083898552113 130.805939360287 Trimmed Mean ( 22 / 44 ) 18.1831818181818 0.136894534286879 132.826207510059 Trimmed Mean ( 23 / 44 ) 18.1733720930233 0.134530099812434 135.087776775317 Trimmed Mean ( 24 / 44 ) 18.1658333333333 0.132506206171386 137.094207571209 Trimmed Mean ( 25 / 44 ) 18.1589024390244 0.130435539150412 139.217444550020 Trimmed Mean ( 26 / 44 ) 18.151125 0.128270382167731 141.506750765465 Trimmed Mean ( 27 / 44 ) 18.1446153846154 0.126144536014407 143.839883659670 Trimmed Mean ( 28 / 44 ) 18.1378947368421 0.123682150038828 146.649251578728 Trimmed Mean ( 29 / 44 ) 18.1328378378378 0.121414976241678 149.345973611561 Trimmed Mean ( 30 / 44 ) 18.1297222222222 0.119275160274298 151.999143665196 Trimmed Mean ( 31 / 44 ) 18.1278571428571 0.117263641462268 154.590603846207 Trimmed Mean ( 32 / 44 ) 18.1267647058824 0.115133323712092 157.441513207861 Trimmed Mean ( 33 / 44 ) 18.1269696969697 0.113241695373013 160.073280758119 Trimmed Mean ( 34 / 44 ) 18.1278125 0.111238622735074 162.963295070394 Trimmed Mean ( 35 / 44 ) 18.1322580645161 0.109650765106602 165.363716768306 Trimmed Mean ( 36 / 44 ) 18.1388333333333 0.108126336356764 167.755922789099 Trimmed Mean ( 37 / 44 ) 18.1455172413793 0.106306628954060 170.690364466555 Trimmed Mean ( 38 / 44 ) 18.1526785714286 0.104200260198415 174.209532076626 Trimmed Mean ( 39 / 44 ) 18.1598148148148 0.101903096821984 178.206702064595 Trimmed Mean ( 40 / 44 ) 18.165 0.0998314945302875 181.956606835020 Trimmed Mean ( 41 / 44 ) 18.1716 0.0974136394087457 186.540612898696 Trimmed Mean ( 42 / 44 ) 18.178125 0.0946173968951416 192.122438330719 Trimmed Mean ( 43 / 44 ) 18.1847826086957 0.0912705481492376 199.240422868519 Trimmed Mean ( 44 / 44 ) 18.1927272727273 0.0873683628573195 208.230149653115 Median 18.35 Midrange 19.1 Midmean - Weighted Average at Xnp 18.1023880597015 Midmean - Weighted Average at X(n+1)p 18.1269696969697 Midmean - Empirical Distribution Function 18.1023880597015 Midmean - Empirical Distribution Function - Averaging 18.1269696969697 Midmean - Empirical Distribution Function - Interpolation 18.1269696969697 Midmean - Closest Observation 18.1023880597015 Midmean - True Basic - Statistics Graphics Toolkit 18.1269696969697 Midmean - MS Excel (old versions) 18.1267647058823 Number of observations 132

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Aug/17/t1250534391w4xen9z5a831j8g/1kyhk1250534077.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Aug/17/t1250534391w4xen9z5a831j8g/1kyhk1250534077.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Aug/17/t1250534391w4xen9z5a831j8g/2dinw1250534077.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Aug/17/t1250534391w4xen9z5a831j8g/2dinw1250534077.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