Home » date » 2007 » Dec » 21 » attachments

Paper - Centr. Tend. - Regress.

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

Title produced by software: Central Tendency

Date of computation: Fri, 21 Dec 2007 09:04:13 -0700

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2007/Dec/21/t1198252054jxbhovk9xvu6xag.htm/, Retrieved Fri, 21 Dec 2007 16:47:36 +0100

User-defined keywords:

Dataseries X:

» Textbox « » Textfile « » CSV «

622.755354196211 419.557064448606 337.667064448595 587.237064448597 -78.5029355514001 568.837064448604 111.996766841012 336.956766841012 -410.723233158992 506.376766841009 -207.193233158988 342.366766841013 395.671231421387 256.272941673806 221.182941673811 -171.54705832619 -252.987058326191 -506.447058326191 -1043.78735593379 -941.627355933786 -841.907355933784 -600.707355933784 -876.677355933786 -265.917355933785 -632.912891353406 -85.1111811009849 -339.801181100985 -361.331181100985 -139.271181100985 302.068818899015 -360.67147870858 645.48852129142 410.608521291422 -300.891478708579 1072.53852129142 -225.101478708580 109.802985871800 706.304696124221 382.814696124222 358.684696124221 1231.64469612422 593.68469612422 1026.44439851663 641.904398516626 79.9243985166273 249.724398516626 720.354398516625 -9.28560148337375 -389.081136902994 -315.179426650573 -800.369426650573 -673.499426650573 -920.739426650575 -1487.59942665057 370.863251817773 198.223251817774 -9.05674818222588 870.343251817775 572.773251817774 -117.366748182226 593.537716398154 -31.160573349427 87.7494266505743 798.919426650575 -181.820573349426 199.819426650573 314.47912904298 58.83912904298 -547.640870957020 49.7591290429804 -771.71087095702 -701.150870957021 -141.946406376641 -1102.04469612422 -506.434696124219 209.935303875781 -826.90469612422 -268.264696124222 -677.204993731815 -493.544993731816 -136.324993731815 -191.124993731815 -1176.29499373181 438.965006268185 -431.030529151435 -146.428818899016 86.0811811009855 -81.7488188990137 -65.288818899014 493.651181100984 -478.489116506611 -296.029116506610 53.1908834933911 305.190883493390 -424.979116506609 84.5808834933917 -889.51465192623 -80.7129416738088 432.597058326191 -769.932941673809 828.527058326191 1028.86705832619 638.626760718596 307.086760718597 1529.50676071860 -202.193239281403 800.236760718596 299.296760718597 -377.998774701024 378.502935551396 98.5129355513976 103.282935551397 405.342935551397 -924.617064448604 97.7426379438026 -457.297362056198 -127.577362056198 -686.477362056198 290.952637943803 153.612637943802 1140.71710252418

Text written by user:

Output produced by software:

Summary of compuational transaction Raw Input view raw input (R code) Raw Output view raw output of R engine Computing time 2 seconds R Server 'Gwilym Jenkins' @ 72.249.127.135 Central Tendency - Ungrouped Data Measure Value S.E. Value/S.E. Arithmetic Mean 6.79676700596141e-14 51.4038116616343 1.32223015886471e-15 Geometric Mean NaN Harmonic Mean -611.289101333921 Quadratic Mean 563.100543776485 Winsorized Mean ( 1 / 40 ) 0.111093953094117 50.2851531315402 0.00220927940307763 Winsorized Mean ( 2 / 40 ) -0.164563831905055 49.755227392081 -0.00330746819039254 Winsorized Mean ( 3 / 40 ) -0.410545014772738 49.1790186519547 -0.00834797086290416 Winsorized Mean ( 4 / 40 ) 1.52296034174872 48.3466703605139 0.0315008320199143 Winsorized Mean ( 5 / 40 ) 2.12575503908846 48.2155158224542 0.0440886092957340 Winsorized Mean ( 6 / 40 ) -5.42251812954753 46.8958439787222 -0.115628969850886 Winsorized Mean ( 7 / 40 ) -6.03524483509029 46.2348717823591 -0.130534477601667 Winsorized Mean ( 8 / 40 ) -7.05693089229036 45.8221821129901 -0.154006871058412 Winsorized Mean ( 9 / 40 ) -4.56871607090334 45.4045078558647 -0.100622521565625 Winsorized Mean ( 10 / 40 ) -9.8218043621749 44.2887281034489 -0.221767586985865 Winsorized Mean ( 11 / 40 ) -8.68675280933464 43.7466491673476 -0.198569558461598 Winsorized Mean ( 12 / 40 ) -11.8759381785162 42.5211194835424 -0.279295049677908 Winsorized Mean ( 13 / 40 ) -12.0699920247194 42.4431587778793 -0.284380153887370 Winsorized Mean ( 14 / 40 ) -4.49096672833417 41.2414884693981 -0.108894389970104 Winsorized Mean ( 15 / 40 ) -4.63946643348649 40.7324547537251 -0.113900978017098 Winsorized Mean ( 16 / 40 ) -7.25742210259167 40.0745897365988 -0.181097851538670 Winsorized Mean ( 17 / 40 ) -6.75745528409587 39.999585454884 -0.168938132914345 Winsorized Mean ( 18 / 40 ) -1.65707594312909 39.0559994314315 -0.0424282048149434 Winsorized Mean ( 19 / 40 ) 1.12881441213687 38.097781298384 0.0296294002870123 Winsorized Mean ( 20 / 40 ) 9.24952476049952 36.8864655874909 0.250756601728636 Winsorized Mean ( 21 / 40 ) 5.5586472025484 34.6574225864933 0.160388360925452 Winsorized Mean ( 22 / 40 ) 3.24715201381149 34.3803121046942 0.0944480086138638 Winsorized Mean ( 23 / 40 ) -4.69763200378448 32.8740874791258 -0.142897715617729 Winsorized Mean ( 24 / 40 ) -2.97440636083351 32.364368498813 -0.091903735459649 Winsorized Mean ( 25 / 40 ) -1.29015830859631 31.531501963147 -0.0409164875845179 Winsorized Mean ( 26 / 40 ) 2.43112709170991 30.6450023120081 0.0793319271755214 Winsorized Mean ( 27 / 40 ) 2.60647689691344 30.3560069658702 0.0858636282381918 Winsorized Mean ( 28 / 40 ) 3.6672786993349 29.7240343711572 0.123377555467149 Winsorized Mean ( 29 / 40 ) 5.77290901178247 28.7887422363947 0.200526614340392 Winsorized Mean ( 30 / 40 ) 7.45157057272726 28.3594824484112 0.262754110068209 Winsorized Mean ( 31 / 40 ) 9.76450615833797 27.6658032535527 0.352944972132124 Winsorized Mean ( 32 / 40 ) 6.71819784729082 27.2980671577850 0.246105257506295 Winsorized Mean ( 33 / 40 ) 7.95975284485092 26.1879381730255 0.303947290247147 Winsorized Mean ( 34 / 40 ) 13.5576848280889 25.2894893471346 0.536099588330557 Winsorized Mean ( 35 / 40 ) 17.4851043463070 24.8227587235222 0.704398110663583 Winsorized Mean ( 36 / 40 ) 12.2441959045031 23.9576146207926 0.511077421450651 Winsorized Mean ( 37 / 40 ) 18.4736663685212 22.8197393414466 0.809547650483814 Winsorized Mean ( 38 / 40 ) 18.6154481261967 22.6798851996252 0.82079110905307 Winsorized Mean ( 39 / 40 ) 21.7767794279780 22.1404416478052 0.98357475313221 Winsorized Mean ( 40 / 40 ) 30.0787699857278 21.1019577883936 1.42540186495263 Trimmed Mean ( 1 / 40 ) -0.352162471159846 49.0724324811779 -0.00717638098121426 Trimmed Mean ( 2 / 40 ) -0.83125672188403 47.7259980443493 -0.0174172726804285 Trimmed Mean ( 3 / 40 ) -1.18199515530775 46.5418036441373 -0.0253964191922039 Trimmed Mean ( 4 / 40 ) -1.45735051520373 45.4627304726741 -0.0320559390087599 Trimmed Mean ( 5 / 40 ) -2.26955234784167 44.5310602695066 -0.050965603201588 Trimmed Mean ( 6 / 40 ) -3.24539123558213 43.527300576408 -0.0745599013172239 Trimmed Mean ( 7 / 40 ) -2.83506046584721 42.719415667803 -0.0663646826982223 Trimmed Mean ( 8 / 40 ) -2.30822739281536 41.9545070095494 -0.0550173880553518 Trimmed Mean ( 9 / 40 ) -1.61090564107206 41.1759871110444 -0.0391224535000881 Trimmed Mean ( 10 / 40 ) -1.21718170046746 40.3763977231560 -0.0301458715760917 Trimmed Mean ( 11 / 40 ) -0.165505597369886 39.6633760804966 -0.00417275617269678 Trimmed Mean ( 12 / 40 ) 0.800821406048797 38.9448299207307 0.0205629709432243 Trimmed Mean ( 13 / 40 ) 2.14633711634035 38.3169720423269 0.0560153112821492 Trimmed Mean ( 14 / 40 ) 3.56914590547867 37.6143336309147 0.094887920666106 Trimmed Mean ( 15 / 40 ) 4.33466680712023 36.9888821566552 0.117188369974580 Trimmed Mean ( 16 / 40 ) 5.14805266638122 36.3448200626962 0.141644742153094 Trimmed Mean ( 17 / 40 ) 6.22640212546578 35.6959419199732 0.174428850747930 Trimmed Mean ( 18 / 40 ) 7.31363170785814 34.9599694224874 0.209200174618968 Trimmed Mean ( 19 / 40 ) 8.04017496473194 34.242268255132 0.234802639382014 Trimmed Mean ( 20 / 40 ) 8.583563286281 33.5427179176138 0.255899456548619 Trimmed Mean ( 21 / 40 ) 8.53256243920477 32.8942233406819 0.259393947406326 Trimmed Mean ( 22 / 40 ) 8.75510031405661 32.4295644248927 0.269972800107555 Trimmed Mean ( 23 / 40 ) 9.15901652274126 31.917277021152 0.286961087459668 Trimmed Mean ( 24 / 40 ) 10.1576195434140 31.503235652411 0.322430992660167 Trimmed Mean ( 25 / 40 ) 11.0901166880232 31.0741471275496 0.356892069877308 Trimmed Mean ( 26 / 40 ) 11.9585301805397 30.6673462611315 0.389943429689453 Trimmed Mean ( 27 / 40 ) 12.6203073181679 30.2917012494346 0.416625900745785 Trimmed Mean ( 28 / 40 ) 13.3107195580379 29.8707759318549 0.445610103614449 Trimmed Mean ( 29 / 40 ) 13.9722027461915 29.4417387463632 0.474571249563766 Trimmed Mean ( 30 / 40 ) 14.5330362916203 29.0433407685075 0.500391342974528 Trimmed Mean ( 31 / 40 ) 14.5330362916203 28.6083721766867 0.50799941366337 Trimmed Mean ( 32 / 40 ) 15.3768242495031 28.1667643292375 0.545920861543255 Trimmed Mean ( 33 / 40 ) 15.9721048146552 27.6652312953618 0.577334945951925 Trimmed Mean ( 34 / 40 ) 16.5264184729436 27.2067403782344 0.607438386340647 Trimmed Mean ( 35 / 40 ) 16.7335792405488 26.7658507553298 0.625183910405564 Trimmed Mean ( 36 / 40 ) 16.6805561864399 26.272210800223 0.634912543648528 Trimmed Mean ( 37 / 40 ) 16.9978136297699 25.7805322238332 0.659327491077008 Trimmed Mean ( 38 / 40 ) 16.8905594667736 25.3402689419629 0.66655012641966 Trimmed Mean ( 39 / 40 ) 16.7628290336094 24.7726962291980 0.676665506189517 Trimmed Mean ( 40 / 40 ) 16.3834118993264 24.1204721300143 0.679232637363664 Median 49.7591290429804 Midrange 20.953667034015 Midmean - Weighted Average at Xnp 8.46687130395737 Midmean - Weighted Average at X(n+1)p 14.5330362916203 Midmean - Empirical Distribution Function 14.5330362916203 Midmean - Empirical Distribution Function - Averaging 14.5330362916203 Midmean - Empirical Distribution Function - Interpolation 14.5330362916203 Midmean - Closest Observation 8.02313027235234 Midmean - True Basic - Statistics Graphics Toolkit 14.5330362916203 Midmean - MS Excel (old versions) 14.5330362916203 Number of observations 121

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Dec/21/t1198252054jxbhovk9xvu6xag/1hexf1198253050.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Dec/21/t1198252054jxbhovk9xvu6xag/1hexf1198253050.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Dec/21/t1198252054jxbhovk9xvu6xag/2gisg1198253050.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Dec/21/t1198252054jxbhovk9xvu6xag/2gisg1198253050.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