Centrummaten hotelkamer

*Unverified author*

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

Title produced by software: Central Tendency

Date of computation: Wed, 12 Aug 2009 07:27:27 -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/12/t1250083691haa5dolr78rvggc.htm/, Retrieved Wed, 12 Aug 2009 15:28:14 +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/12/t1250083691haa5dolr78rvggc.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 «

613,20 614,70 618,40 628,20 629,00 629,70 630,40 630,40 639,30 639,40 640,90 640,80 642,10 645,30 647,60 648,40 648,80 648,90 648,90 648,90 650,30 650,30 650,00 650,00 650,50 658,40 666,00 675,50 680,70 690,60 690,60 691,10 692,90 693,80 692,80 697,50 699,00 702,10 704,80 715,50 721,80 726,40 727,70 727,40 731,30 734,40 733,40 733,40 738,10 742,60 747,20 751,10 752,60 758,90 759,10 764,30 765,60 767,60 767,60 765,60 768,20 770,90 775,10 777,60 778,60 778,90 779,40 779,90 781,70 789,10 788,70 788,80 790,80 794,10 795,10 797,30 803,80 805,60 804,60 804,50 805,80 806,80 805,20 814,90 816,60 819,50 823,00 824,00 831,40 831,70 831,10 832,10 833,30 838,80 838,00 837,30 994,20 994,20 994,20 994,20 994,20 1092,60 1100,00 1100,00 1092,60 1000,70 1000,70 1000,50 1000,50 1000,50 1000,50 1000,50 1000,50 1087,70 1113,20 1116,00 1085,20 1031,30 1028,70 1027,50 1027,50 1027,50 1027,50 1027,50 1027,50 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 8 seconds R Server 'George Udny Yule' @ 72.249.76.132 Central Tendency - Ungrouped Data Measure Value S.E. Value/S.E. Arithmetic Mean 818.079545454545 13.6336886269961 60.0042708790244 Geometric Mean 804.063424698361 Harmonic Mean 791.01766305261 Quadratic Mean 832.828968445393 Winsorized Mean ( 1 / 44 ) 818.08106060606 13.6305335461234 60.0182713198872 Winsorized Mean ( 2 / 44 ) 818.109848484848 13.6190842656150 60.0708412202416 Winsorized Mean ( 3 / 44 ) 817.598484848485 13.4629756336893 60.7294038921497 Winsorized Mean ( 4 / 44 ) 817.504545454545 13.4402295247530 60.8251923041148 Winsorized Mean ( 5 / 44 ) 817.425 13.4194814975455 60.9133072801295 Winsorized Mean ( 6 / 44 ) 816.856818181818 13.3169090313734 61.3398211444847 Winsorized Mean ( 7 / 44 ) 816.856818181818 13.3169090313734 61.3398211444847 Winsorized Mean ( 8 / 44 ) 816.947727272727 13.1881688783719 61.9455009112366 Winsorized Mean ( 9 / 44 ) 816.954545454545 13.1874679557705 61.9493103751631 Winsorized Mean ( 10 / 44 ) 816.689393939394 13.1177020183742 62.2585718745129 Winsorized Mean ( 11 / 44 ) 816.489393939394 13.0840900440318 62.4032233951055 Winsorized Mean ( 12 / 44 ) 816.062121212121 12.9893927049452 62.8252713386237 Winsorized Mean ( 13 / 44 ) 815.884848484848 12.8815588628849 63.3374312200382 Winsorized Mean ( 14 / 44 ) 815.651515151515 12.7842304460304 63.8013776890873 Winsorized Mean ( 15 / 44 ) 811.367424242424 12.1397682642373 66.8354952567458 Winsorized Mean ( 16 / 44 ) 811.100757575758 12.0913605949274 67.0810163345913 Winsorized Mean ( 17 / 44 ) 810.959090909091 12.0688417789735 67.1944421644467 Winsorized Mean ( 18 / 44 ) 810.959090909091 12.0688417789735 67.1944421644466 Winsorized Mean ( 19 / 44 ) 810.959090909091 12.0688417789735 67.1944421644467 Winsorized Mean ( 20 / 44 ) 811.125757575758 12.0517951042108 67.3033146151279 Winsorized Mean ( 21 / 44 ) 811.125757575758 12.0517951042108 67.3033146151279 Winsorized Mean ( 22 / 44 ) 811.175757575758 12.0466951439894 67.3359579436594 Winsorized Mean ( 23 / 44 ) 806.50606060606 11.4231917774106 70.6025142815974 Winsorized Mean ( 24 / 44 ) 806.542424242424 11.4193973082902 70.6291586559385 Winsorized Mean ( 25 / 44 ) 808.000757575758 11.2605479117980 71.7550126250245 Winsorized Mean ( 26 / 44 ) 809.497727272727 11.1108338900176 72.8566132196445 Winsorized Mean ( 27 / 44 ) 811.440909090909 10.922709873112 74.2893401470271 Winsorized Mean ( 28 / 44 ) 812.54393939394 10.8190027954014 75.1034041454646 Winsorized Mean ( 29 / 44 ) 814.71893939394 10.6207841581016 76.709866923759 Winsorized Mean ( 30 / 44 ) 814.71893939394 10.6207841581016 76.709866923759 Winsorized Mean ( 31 / 44 ) 813.356818181818 10.4134274136188 78.1065432038354 Winsorized Mean ( 32 / 44 ) 813.76893939394 10.3766223384566 78.4232973747194 Winsorized Mean ( 33 / 44 ) 813.79393939394 10.3743980122714 78.4425215257156 Winsorized Mean ( 34 / 44 ) 814.025757575758 10.3538131927500 78.6208658029257 Winsorized Mean ( 35 / 44 ) 815.006818181818 10.2674760996027 79.3775227987486 Winsorized Mean ( 36 / 44 ) 773.034090909091 5.05692049217224 152.866570100458 Winsorized Mean ( 37 / 44 ) 773.678787878788 4.93800532954676 156.678402765070 Winsorized Mean ( 38 / 44 ) 774.254545454545 4.8323044479448 160.224703098713 Winsorized Mean ( 39 / 44 ) 776.234090909091 4.37330500916095 177.493700824223 Winsorized Mean ( 40 / 44 ) 777.779545454545 4.13711398995714 188.000511308755 Winsorized Mean ( 41 / 44 ) 779.084090909091 3.97858290604282 195.819493851891 Winsorized Mean ( 42 / 44 ) 779.306818181818 3.93684987593108 197.951875926564 Winsorized Mean ( 43 / 44 ) 779.306818181818 3.91715005209514 198.947399976418 Winsorized Mean ( 44 / 44 ) 778.140151515152 3.56062426784759 218.540371850451 Trimmed Mean ( 1 / 44 ) 817.061538461538 13.5044884159234 60.5029611857142 Trimmed Mean ( 2 / 44 ) 816.01015625 13.3651076836469 61.0552623716189 Trimmed Mean ( 3 / 44 ) 814.910317460318 13.2174010763044 61.6543534357337 Trimmed Mean ( 4 / 44 ) 813.956451612903 13.1153366380636 62.0614227507222 Trimmed Mean ( 5 / 44 ) 812.996721311475 13.0083303135193 62.4981609258909 Trimmed Mean ( 6 / 44 ) 812.0225 12.8940487142091 62.9765342134282 Trimmed Mean ( 7 / 44 ) 811.121186440678 12.7891136577027 63.4227834821181 Trimmed Mean ( 8 / 44 ) 810.188793103448 12.6713654318063 63.938554804031 Trimmed Mean ( 9 / 44 ) 809.21052631579 12.5620612670271 64.4170179650218 Trimmed Mean ( 10 / 44 ) 808.196428571429 12.4390035536975 64.972762897169 Trimmed Mean ( 11 / 44 ) 807.177272727273 12.3113978300161 65.5634139901899 Trimmed Mean ( 12 / 44 ) 806.142592592593 12.1725725152982 66.2261483001602 Trimmed Mean ( 13 / 44 ) 805.11320754717 12.0295863239654 66.927755108521 Trimmed Mean ( 14 / 44 ) 804.061538461538 11.8826884475598 67.6666347022386 Trimmed Mean ( 15 / 44 ) 802.990196078431 11.7292541887419 68.4604650182418 Trimmed Mean ( 16 / 44 ) 802.253 11.6394659927318 68.9252411150962 Trimmed Mean ( 17 / 44 ) 801.508163265306 11.5418882080558 69.443417646853 Trimmed Mean ( 18 / 44 ) 800.74375 11.4321313315496 70.0432602440599 Trimmed Mean ( 19 / 44 ) 799.946808510638 11.3056941598017 70.7560984052541 Trimmed Mean ( 20 / 44 ) 799.115217391304 11.1601941271005 71.6040606722778 Trimmed Mean ( 21 / 44 ) 798.234444444444 10.9946489267053 72.6020857751617 Trimmed Mean ( 22 / 44 ) 797.313636363636 10.8039943344310 73.7980428055849 Trimmed Mean ( 23 / 44 ) 796.346511627907 10.5846680406736 75.2358513812426 Trimmed Mean ( 24 / 44 ) 795.652380952381 10.4120974914527 76.4161478132078 Trimmed Mean ( 25 / 44 ) 794.921951219512 10.2122123171569 77.8403274953476 Trimmed Mean ( 26 / 44 ) 794.05875 9.99785747518665 79.4228915515897 Trimmed Mean ( 27 / 44 ) 793.053846153846 9.76440263144363 81.2188800572428 Trimmed Mean ( 28 / 44 ) 791.871052631579 9.51152833583919 83.2538183845628 Trimmed Mean ( 29 / 44 ) 790.554054054054 9.22447129913534 85.701828150103 Trimmed Mean ( 30 / 44 ) 789.026388888889 8.90552856039253 88.5996135477119 Trimmed Mean ( 31 / 44 ) 787.411428571429 8.5226932588532 92.3899763438608 Trimmed Mean ( 32 / 44 ) 785.786764705882 8.09589743827352 97.0598714592232 Trimmed Mean ( 33 / 44 ) 784.037878787879 7.57760095288559 103.467823611022 Trimmed Mean ( 34 / 44 ) 782.178125 6.92999950924707 112.868424298775 Trimmed Mean ( 35 / 44 ) 780.183870967742 6.0977803668351 127.945551337179 Trimmed Mean ( 36 / 44 ) 777.995 4.9773165829824 156.308120455908 Trimmed Mean ( 37 / 44 ) 778.308620689655 4.84969690802572 160.486033550187 Trimmed Mean ( 38 / 44 ) 778.603571428571 4.71182469706602 165.244596623766 Trimmed Mean ( 39 / 44 ) 778.883333333333 4.55893601885781 170.847612274338 Trimmed Mean ( 40 / 44 ) 779.055769230769 4.44945419523075 175.090187480931 Trimmed Mean ( 41 / 44 ) 779.14 4.35238991350541 179.014292258682 Trimmed Mean ( 42 / 44 ) 779.14375 4.25615002069596 183.063037301631 Trimmed Mean ( 43 / 44 ) 779.132608695652 4.13882764136253 188.249590514273 Trimmed Mean ( 44 / 44 ) 779.120454545455 3.98947820633619 195.293823966261 Median 779.15 Midrange 884.25 Midmean - Weighted Average at Xnp 788.807246376811 Midmean - Weighted Average at X(n+1)p 790.219117647059 Midmean - Empirical Distribution Function 788.807246376811 Midmean - Empirical Distribution Function - Averaging 790.219117647059 Midmean - Empirical Distribution Function - Interpolation 790.219117647059 Midmean - Closest Observation 788.807246376811 Midmean - True Basic - Statistics Graphics Toolkit 790.219117647059 Midmean - MS Excel (old versions) 788.807246376811 Number of observations 132

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Aug/12/t1250083691haa5dolr78rvggc/1vkql1250083639.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Aug/12/t1250083691haa5dolr78rvggc/1vkql1250083639.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Aug/12/t1250083691haa5dolr78rvggc/2ij841250083639.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Aug/12/t1250083691haa5dolr78rvggc/2ij841250083639.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