Median ws3 part 1

*The author of this computation has been verified*

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

Title produced by software: Central Tendency

Date of computation: Wed, 21 Oct 2009 13:19:52 -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/Oct/21/t1256153296534bpt0146s67q0.htm/, Retrieved Wed, 21 Oct 2009 21:28:16 +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/Oct/21/t1256153296534bpt0146s67q0.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 «

2443.6 2460.2 2448.2 2470.4 2484.7 2466.8 2487.9 2508.4 2510.5 2497.4 2532.5 2556.8 2561 2547.3 2541.5 2558.5 2587.9 2580.5 2579.6 2589.3 2595 2595.6 2588.8 2591.7 2601.7 2585.4 2573.3 2597.4 2600.6 2570.6 2569.4 2584.9 2608.8 2617.2 2621 2540.5 2554.5 2601.9 2623 2640.7 2640.7 2619.8 2624.2 2638.2 2645.7 2679.6 2669 2664.6 2663.3 2667.4 2653.2 2630.8 2626.6 2641.9 2625.8 2606 2594.4 2583.6 2588.7 2600.3 2579.5 2576.6 2597.8 2595.6 2599 2621.7 2645.6 2644.2 2625.6 2624.6 2596.2 2599.5 2584.1 2570.8 2555 2574.5 2576.7 2579 2588.7 2601.1 2575.7 2559.5 2561.1 2528.3 2514.7 2558.5 2553.3 2577.1 2566 2549.5 2527.8 2540.9 2534.2 2538 2559 2554.9 2575.5 2546.5 2561.6 2546.6 2502.9 2463.1 2472.6 2463.5 2446.3 2456.2 2471.5 2447.5 2428.6 2420.2 2414.9 2420.2 2423.8 2407 2388.7 2409.6 2392 2380.2 2423.3 2451.6 2440.8 2432.9 2413.6 2391.6 2358.1 2345.4 2384.4 2384.4 2384.4 2418.7 2420 2493.1 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 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 2540.59925373134 7.00802764408751 362.527002283557 Geometric Mean 2539.29739991599 Harmonic Mean 2537.979335502 Quadratic Mean 2541.88444349944 Winsorized Mean ( 1 / 44 ) 2540.61492537313 6.9774105675782 364.120027160013 Winsorized Mean ( 2 / 44 ) 2540.92089552239 6.91283183215499 367.565848152607 Winsorized Mean ( 3 / 44 ) 2540.95223880597 6.88803621410263 368.893565571505 Winsorized Mean ( 4 / 44 ) 2540.91343283582 6.88282328805513 369.167320806489 Winsorized Mean ( 5 / 44 ) 2540.53656716418 6.83426837805777 371.734972439899 Winsorized Mean ( 6 / 44 ) 2540.39328358209 6.76100782397319 375.741805027108 Winsorized Mean ( 7 / 44 ) 2540.53955223881 6.73502270416071 377.213212758634 Winsorized Mean ( 8 / 44 ) 2540.47985074627 6.72130365103698 377.974271457638 Winsorized Mean ( 9 / 44 ) 2541.33283582090 6.54189315394372 388.470550652279 Winsorized Mean ( 10 / 44 ) 2541.43731343284 6.50180802971792 390.881628897169 Winsorized Mean ( 11 / 44 ) 2541.76567164179 6.45225518868792 393.934461255967 Winsorized Mean ( 12 / 44 ) 2541.65820895522 6.40932203365572 396.556483760502 Winsorized Mean ( 13 / 44 ) 2541.30895522388 6.27566944662891 404.946273355585 Winsorized Mean ( 14 / 44 ) 2541.00597014925 6.20947567077364 409.214256544896 Winsorized Mean ( 15 / 44 ) 2540.93880597015 6.19694465991086 410.03090158412 Winsorized Mean ( 16 / 44 ) 2540.91492537313 6.1944879139129 410.189665503456 Winsorized Mean ( 17 / 44 ) 2541.18134328358 6.1241976123706 414.941108064592 Winsorized Mean ( 18 / 44 ) 2541.19477611940 6.10898919472108 415.976308865517 Winsorized Mean ( 19 / 44 ) 2541.70522388060 5.99416601094097 424.029834883001 Winsorized Mean ( 20 / 44 ) 2542.15298507463 5.88407936355117 432.039207496409 Winsorized Mean ( 21 / 44 ) 2543.28134328358 5.70277985634204 445.972211333953 Winsorized Mean ( 22 / 44 ) 2543.54402985075 5.62084954658992 452.519500614257 Winsorized Mean ( 23 / 44 ) 2543.56119402985 5.51396762547658 461.294183570765 Winsorized Mean ( 24 / 44 ) 2542.27164179105 5.33928516963672 476.144570109938 Winsorized Mean ( 25 / 44 ) 2541.87985074627 5.2734967010311 482.010323482191 Winsorized Mean ( 26 / 44 ) 2541.74402985075 5.11415972411451 497.001299718076 Winsorized Mean ( 27 / 44 ) 2542.63059701493 4.98878455161662 509.669353468268 Winsorized Mean ( 28 / 44 ) 2543.34104477612 4.8695165994061 522.298464920791 Winsorized Mean ( 29 / 44 ) 2543.86044776119 4.7797074395834 532.220952833657 Winsorized Mean ( 30 / 44 ) 2543.88283582090 4.76234794471093 534.165681582786 Winsorized Mean ( 31 / 44 ) 2544.46119402985 4.64948111981095 547.257022549929 Winsorized Mean ( 32 / 44 ) 2545.20149253731 4.53149615418989 561.669127796562 Winsorized Mean ( 33 / 44 ) 2545.17686567164 4.47164057416381 569.181897216233 Winsorized Mean ( 34 / 44 ) 2545.35447761194 4.4281379870804 574.813721938725 Winsorized Mean ( 35 / 44 ) 2548.20149253731 4.01681713160873 634.383246497648 Winsorized Mean ( 36 / 44 ) 2548.9 3.90067671934163 653.450717246368 Winsorized Mean ( 37 / 44 ) 2550.25298507463 3.74303058498857 681.333728690976 Winsorized Mean ( 38 / 44 ) 2550.16791044776 3.71774877200026 685.94412017671 Winsorized Mean ( 39 / 44 ) 2549.99328358209 3.70195715960324 688.823012704822 Winsorized Mean ( 40 / 44 ) 2550.47089552239 3.48199318491757 732.474407638098 Winsorized Mean ( 41 / 44 ) 2551.41940298507 3.22522539772555 791.082510011347 Winsorized Mean ( 42 / 44 ) 2552.98656716418 3.01802087394395 845.914151623455 Winsorized Mean ( 43 / 44 ) 2553.62835820896 2.94056384653363 868.414525744511 Winsorized Mean ( 44 / 44 ) 2555.00746268657 2.78957926414583 915.911404822157 Trimmed Mean ( 1 / 44 ) 2541.025 6.87717424034305 369.486785007391 Trimmed Mean ( 2 / 44 ) 2541.44769230769 6.76715490206604 375.556305284482 Trimmed Mean ( 3 / 44 ) 2541.7234375 6.68329403431298 380.309982540112 Trimmed Mean ( 4 / 44 ) 2541.99682539683 6.60081081469835 385.103723884411 Trimmed Mean ( 5 / 44 ) 2542.28951612903 6.5114876416052 390.431443021569 Trimmed Mean ( 6 / 44 ) 2542.67459016393 6.42523102851416 395.732788265503 Trimmed Mean ( 7 / 44 ) 2543.09916666667 6.34602353446997 400.739006537434 Trimmed Mean ( 8 / 44 ) 2543.51440677966 6.26336384101936 406.093989003472 Trimmed Mean ( 9 / 44 ) 2543.95258620690 6.17394734986223 412.046368724486 Trimmed Mean ( 10 / 44 ) 2544.29473684211 6.10500465888143 416.755576613807 Trimmed Mean ( 11 / 44 ) 2544.63660714286 6.03425136232802 421.698808079008 Trimmed Mean ( 12 / 44 ) 2544.95454545455 5.96253561160903 426.824208898565 Trimmed Mean ( 13 / 44 ) 2545.29537037037 5.88811252708675 432.276957796134 Trimmed Mean ( 14 / 44 ) 2545.68301886792 5.82225220973012 437.233381029697 Trimmed Mean ( 15 / 44 ) 2546.11346153846 5.75619127303749 442.32606957741 Trimmed Mean ( 16 / 44 ) 2546.56666666667 5.6828725522592 448.112577441894 Trimmed Mean ( 17 / 44 ) 2547.04 5.60002074310732 454.826886692335 Trimmed Mean ( 18 / 44 ) 2547.51122448980 5.51490718961082 461.93183981208 Trimmed Mean ( 19 / 44 ) 2548.00104166667 5.41995915348265 470.114436200026 Trimmed Mean ( 20 / 44 ) 2548.47340425532 5.32630410197467 478.469376788024 Trimmed Mean ( 21 / 44 ) 2548.93369565217 5.23307073610994 487.081834775073 Trimmed Mean ( 22 / 44 ) 2549.33444444444 5.14904647030264 495.108066930032 Trimmed Mean ( 23 / 44 ) 2549.73522727273 5.06240136964766 503.66121551721 Trimmed Mean ( 24 / 44 ) 2550.15348837209 4.97520354715609 512.572694604586 Trimmed Mean ( 25 / 44 ) 2550.67738095238 4.89332074633741 521.256936378334 Trimmed Mean ( 26 / 44 ) 2551.25243902439 4.80502635857115 530.954931074102 Trimmed Mean ( 27 / 44 ) 2551.865 4.72045344180011 540.597430196634 Trimmed Mean ( 28 / 44 ) 2552.45256410256 4.63744288784152 550.400862249884 Trimmed Mean ( 29 / 44 ) 2552.45256410256 4.55496966632342 560.366533936283 Trimmed Mean ( 30 / 44 ) 2553.59864864865 4.46898750166665 571.404294081449 Trimmed Mean ( 31 / 44 ) 2554.20138888889 4.36864875142908 584.666228442685 Trimmed Mean ( 32 / 44 ) 2554.80285714286 4.2647066076085 599.057119799269 Trimmed Mean ( 33 / 44 ) 2555.39411764706 4.15739758832755 614.661952184143 Trimmed Mean ( 34 / 44 ) 2556.02272727273 4.03605937396669 633.2966119774 Trimmed Mean ( 35 / 44 ) 2556.6796875 3.89546196325674 656.322590649179 Trimmed Mean ( 36 / 44 ) 2557.20322580645 3.79345644941961 674.10902429042 Trimmed Mean ( 37 / 44 ) 2557.71833333333 3.68731946157043 693.652492004042 Trimmed Mean ( 38 / 44 ) 2558.18448275862 3.58413591517736 713.752085105297 Trimmed Mean ( 39 / 44 ) 2558.68928571429 3.45956858523116 739.59779165451 Trimmed Mean ( 40 / 44 ) 2559.24259259259 3.30541727792648 774.257038493498 Trimmed Mean ( 41 / 44 ) 2559.80769230769 3.15362063719341 811.704382612683 Trimmed Mean ( 42 / 44 ) 2560.356 3.01368871542324 849.575467730557 Trimmed Mean ( 43 / 44 ) 2560.84583333333 2.88150121915725 888.719330156071 Trimmed Mean ( 44 / 44 ) 2561.33478260870 2.7284619322721 938.746754101044 Median 2561.05 Midrange 2512.5 Midmean - Weighted Average at Xnp 2554.76119402985 Midmean - Weighted Average at X(n+1)p 2555.39411764706 Midmean - Empirical Distribution Function 2555.39411764706 Midmean - Empirical Distribution Function - Averaging 2555.39411764706 Midmean - Empirical Distribution Function - Interpolation 2556.02272727273 Midmean - Closest Observation 2555.39411764706 Midmean - True Basic - Statistics Graphics Toolkit 2555.39411764706 Midmean - MS Excel (old versions) 2555.39411764706 Number of observations 134

Charts produced by software:

http://www.freestatistics.org/blog/date/2009/Oct/21/t1256153296534bpt0146s67q0/1a4hx1256152787.png (open in new window) http://www.freestatistics.org/blog/date/2009/Oct/21/t1256153296534bpt0146s67q0/1a4hx1256152787.ps (open in new window) http://www.freestatistics.org/blog/date/2009/Oct/21/t1256153296534bpt0146s67q0/2ujrn1256152787.png (open in new window) http://www.freestatistics.org/blog/date/2009/Oct/21/t1256153296534bpt0146s67q0/2ujrn1256152787.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