*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: Mon, 22 Nov 2010 14:52:55 +0000

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2010/Nov/22/t1290437451795krc8143jhiwp.htm/, Retrieved Mon, 22 Nov 2010 15:50:53 +0100

BibTeX entries for LaTeX users:

@Manual{KEY, author = {{YOUR NAME}}, publisher = {Office for Research Development and Education}, title = {Statistical Computations at FreeStatistics.org, URL http://www.freestatistics.org/blog/date/2010/Nov/22/t1290437451795krc8143jhiwp.htm/}, year = {2010}, } @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 = {2010}, note = {{ISBN} 3-900051-07-0}, url = {http://www.R-project.org}, }

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords:

Dataseries X:

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14.84 14.84 15.57 14.84 14.84 15.57 15.57 15.57 15.57 15.57 15.57 14.84 15.57 15.57 15.57 15.57 15.57 15.57 15.57 14.84 14.84 14.84 14.84 15.57 15.57 15.57 15.57 15.57 15.57 15.57 14.84 14.84 14.84 14.84 14.84 15.57 15.57 15.57 15.57 15.57 15.57 15.57 14.84 14.84 14.84 14.84 14.84 14.84 15.57 15.57 14.84 15.57 15.57 15.57 15.57 15.57 15.57 15.57 15.57 15.57 15.57 14.84 14.84 14.84 14.84 15.57 15.57 15.57 15.57 15.57 15.57 15.57 15.57 15.57 15.57 15.57 14.84 14.84 14.84 14.84 14.84 15.57 15.57 15.57 14.84 14.84 14.84 15.57 14.84 14.84 14.84 15.57 15.57 15.57 15.57 15.57 15.57 15.57 15.57 15.57 15.57 15.57 15.57 14.84 14.84 14.84 14.84 14.84 15.57 15.57 14.84 14.84 14.84 14.84 14.84 14.84 14.84 14.84 15.57 15.57 15.57 15.57 15.57 14.84 14.84 15.57 15.57 15.54 15.54 15.54 15.54 16.28 16.28 16.28 15.54 15.54 16.28 16.28 16.28 15.54 15.54 15.54 15.54 15.54 16.28 16.28 15 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 'Gwilym Jenkins' @ 72.249.127.135 Central Tendency - Ungrouped Data Measure Value S.E. Value/S.E. Arithmetic Mean 15.4908457711443 0.0323558249536383 478.76528548849 Geometric Mean 15.4840910004680 Harmonic Mean 15.4773400911857 Quadratic Mean 15.497602478676 Winsorized Mean ( 1 / 67 ) 15.4908457711443 0.0323558249536383 478.76528548849 Winsorized Mean ( 2 / 67 ) 15.4908457711443 0.0323558249536383 478.76528548849 Winsorized Mean ( 3 / 67 ) 15.4908457711443 0.0323558249536383 478.76528548849 Winsorized Mean ( 4 / 67 ) 15.4908457711443 0.0323558249536383 478.76528548849 Winsorized Mean ( 5 / 67 ) 15.4908457711443 0.0323558249536383 478.76528548849 Winsorized Mean ( 6 / 67 ) 15.4908457711443 0.0323558249536383 478.76528548849 Winsorized Mean ( 7 / 67 ) 15.4908457711443 0.0323558249536383 478.76528548849 Winsorized Mean ( 8 / 67 ) 15.4896517412935 0.0322125541879360 480.857607593707 Winsorized Mean ( 9 / 67 ) 15.4896517412935 0.0322125541879360 480.857607593707 Winsorized Mean ( 10 / 67 ) 15.4896517412935 0.0322125541879360 480.857607593707 Winsorized Mean ( 11 / 67 ) 15.4896517412935 0.0322125541879360 480.857607593707 Winsorized Mean ( 12 / 67 ) 15.4896517412935 0.0322125541879360 480.857607593707 Winsorized Mean ( 13 / 67 ) 15.4896517412935 0.0322125541879360 480.857607593707 Winsorized Mean ( 14 / 67 ) 15.4896517412935 0.0322125541879360 480.857607593707 Winsorized Mean ( 15 / 67 ) 15.4896517412935 0.0322125541879360 480.857607593707 Winsorized Mean ( 16 / 67 ) 15.4896517412935 0.0322125541879360 480.857607593707 Winsorized Mean ( 17 / 67 ) 15.4896517412935 0.0322125541879360 480.857607593707 Winsorized Mean ( 18 / 67 ) 15.4896517412935 0.0322125541879360 480.857607593707 Winsorized Mean ( 19 / 67 ) 15.4896517412935 0.0322125541879360 480.857607593707 Winsorized Mean ( 20 / 67 ) 15.4896517412935 0.0322125541879360 480.857607593707 Winsorized Mean ( 21 / 67 ) 15.4896517412935 0.0322125541879360 480.857607593707 Winsorized Mean ( 22 / 67 ) 15.4896517412935 0.0322125541879360 480.857607593707 Winsorized Mean ( 23 / 67 ) 15.4896517412935 0.0322125541879360 480.857607593707 Winsorized Mean ( 24 / 67 ) 15.4896517412935 0.0322125541879360 480.857607593707 Winsorized Mean ( 25 / 67 ) 15.4896517412935 0.0322125541879360 480.857607593707 Winsorized Mean ( 26 / 67 ) 15.4896517412935 0.0322125541879360 480.857607593707 Winsorized Mean ( 27 / 67 ) 15.4896517412935 0.0322125541879360 480.857607593707 Winsorized Mean ( 28 / 67 ) 15.4896517412935 0.0322125541879360 480.857607593707 Winsorized Mean ( 29 / 67 ) 15.4896517412935 0.0322125541879360 480.857607593707 Winsorized Mean ( 30 / 67 ) 15.4896517412935 0.0322125541879360 480.857607593707 Winsorized Mean ( 31 / 67 ) 15.4896517412935 0.0322125541879360 480.857607593707 Winsorized Mean ( 32 / 67 ) 15.4896517412935 0.0322125541879360 480.857607593707 Winsorized Mean ( 33 / 67 ) 15.4896517412935 0.0322125541879360 480.857607593707 Winsorized Mean ( 34 / 67 ) 15.3746268656716 0.0220904951392144 695.98380519679 Winsorized Mean ( 35 / 67 ) 15.3746268656716 0.0220904951392144 695.98380519679 Winsorized Mean ( 36 / 67 ) 15.3746268656716 0.0220904951392144 695.98380519679 Winsorized Mean ( 37 / 67 ) 15.3746268656716 0.0220904951392144 695.98380519679 Winsorized Mean ( 38 / 67 ) 15.3746268656716 0.0220904951392144 695.98380519679 Winsorized Mean ( 39 / 67 ) 15.3746268656716 0.0220904951392144 695.98380519679 Winsorized Mean ( 40 / 67 ) 15.3746268656716 0.0220904951392144 695.98380519679 Winsorized Mean ( 41 / 67 ) 15.3746268656716 0.0220904951392144 695.98380519679 Winsorized Mean ( 42 / 67 ) 15.3746268656716 0.0220904951392144 695.98380519679 Winsorized Mean ( 43 / 67 ) 15.3746268656716 0.0220904951392144 695.98380519679 Winsorized Mean ( 44 / 67 ) 15.3746268656716 0.0220904951392144 695.98380519679 Winsorized Mean ( 45 / 67 ) 15.3746268656716 0.0220904951392144 695.98380519679 Winsorized Mean ( 46 / 67 ) 15.3746268656716 0.0220904951392144 695.98380519679 Winsorized Mean ( 47 / 67 ) 15.3746268656716 0.0220904951392144 695.98380519679 Winsorized Mean ( 48 / 67 ) 15.3746268656716 0.0220904951392144 695.98380519679 Winsorized Mean ( 49 / 67 ) 15.3746268656716 0.0220904951392144 695.98380519679 Winsorized Mean ( 50 / 67 ) 15.3746268656716 0.0220904951392144 695.98380519679 Winsorized Mean ( 51 / 67 ) 15.5446268656716 0.00203083821459640 7654.29109711772 Winsorized Mean ( 52 / 67 ) 15.5446268656716 0.00203083821459640 7654.29109711772 Winsorized Mean ( 53 / 67 ) 15.5446268656716 0.00203083821459640 7654.29109711772 Winsorized Mean ( 54 / 67 ) 15.5446268656716 0.00203083821459640 7654.29109711772 Winsorized Mean ( 55 / 67 ) 15.5446268656716 0.00203083821459640 7654.29109711772 Winsorized Mean ( 56 / 67 ) 15.5446268656716 0.00203083821459640 7654.29109711772 Winsorized Mean ( 57 / 67 ) 15.5446268656716 0.00203083821459640 7654.29109711772 Winsorized Mean ( 58 / 67 ) 15.5446268656716 0.00203083821459640 7654.29109711772 Winsorized Mean ( 59 / 67 ) 15.5446268656716 0.00203083821459640 7654.29109711772 Winsorized Mean ( 60 / 67 ) 15.5446268656716 0.00203083821459640 7654.29109711772 Winsorized Mean ( 61 / 67 ) 15.5446268656716 0.00203083821459640 7654.29109711772 Winsorized Mean ( 62 / 67 ) 15.5446268656716 0.00203083821459640 7654.29109711772 Winsorized Mean ( 63 / 67 ) 15.5446268656716 0.00203083821459640 7654.29109711772 Winsorized Mean ( 64 / 67 ) 15.5446268656716 0.00203083821459640 7654.29109711772 Winsorized Mean ( 65 / 67 ) 15.5446268656716 0.00203083821459640 7654.29109711772 Winsorized Mean ( 66 / 67 ) 15.5446268656716 0.00203083821459640 7654.29109711772 Winsorized Mean ( 67 / 67 ) 15.5446268656716 0.00203083821459640 7654.29109711772 Trimmed Mean ( 1 / 67 ) 15.4901507537688 0.0322729524786142 479.973152875723 Trimmed Mean ( 2 / 67 ) 15.4894416243655 0.0321830135828291 481.29245524197 Trimmed Mean ( 3 / 67 ) 15.4887179487179 0.0320855729860885 482.731536551754 Trimmed Mean ( 4 / 67 ) 15.4879792746114 0.0319801623448108 484.299582585594 Trimmed Mean ( 5 / 67 ) 15.4872251308901 0.0318662770338334 486.00673101683 Trimmed Mean ( 6 / 67 ) 15.4864550264550 0.0317433725292493 487.864199438334 Trimmed Mean ( 7 / 67 ) 15.4856684491979 0.0316108603303403 489.884434886279 Trimmed Mean ( 8 / 67 ) 15.4848648648649 0.0314681033468774 492.08128923987 Trimmed Mean ( 9 / 67 ) 15.4842076502732 0.0313368639543515 494.121162629072 Trimmed Mean ( 10 / 67 ) 15.4835359116022 0.0311952095575968 496.343385128234 Trimmed Mean ( 11 / 67 ) 15.4828491620112 0.0310424246804474 498.764169403407 Trimmed Mean ( 12 / 67 ) 15.4821468926554 0.0308777308692863 501.401704619924 Trimmed Mean ( 13 / 67 ) 15.4814285714286 0.0307002793893797 504.276471724363 Trimmed Mean ( 14 / 67 ) 15.4806936416185 0.0305091428182377 507.411621947127 Trimmed Mean ( 15 / 67 ) 15.4806936416185 0.0303033053240159 510.858253780975 Trimmed Mean ( 16 / 67 ) 15.4791715976331 0.0300816513664342 514.571870043848 Trimmed Mean ( 17 / 67 ) 15.4783832335329 0.0298429524925298 518.661256368901 Trimmed Mean ( 18 / 67 ) 15.4775757575758 0.0295858518147854 523.141123482573 Trimmed Mean ( 19 / 67 ) 15.4767484662577 0.0293088456477122 528.057251120901 Trimmed Mean ( 20 / 67 ) 15.475900621118 0.0290102616308246 533.462980033046 Trimmed Mean ( 21 / 67 ) 15.4750314465409 0.0286882324666792 539.420874552477 Trimmed Mean ( 22 / 67 ) 15.4741401273885 0.0283406641311325 546.004852101898 Trimmed Mean ( 23 / 67 ) 15.4732258064516 0.0279651970377700 553.302942423519 Trimmed Mean ( 24 / 67 ) 15.4722875816993 0.0275591581119210 561.42090839149 Trimmed Mean ( 25 / 67 ) 15.4713245033113 0.027119500978154 570.487064484488 Trimmed Mean ( 26 / 67 ) 15.4703355704698 0.0266427303723212 580.658789631477 Trimmed Mean ( 27 / 67 ) 15.4693197278912 0.026124805266792 592.131484614534 Trimmed Mean ( 28 / 67 ) 15.4682758620690 0.0255610127325141 605.151134813725 Trimmed Mean ( 29 / 67 ) 15.4672027972028 0.0249458007177614 620.032324165491 Trimmed Mean ( 30 / 67 ) 15.4672027972028 0.0242725517506253 637.230191374681 Trimmed Mean ( 31 / 67 ) 15.4649640287770 0.0235332693200763 657.153233511153 Trimmed Mean ( 32 / 67 ) 15.4637956204380 0.0227181309882575 680.680801974019 Trimmed Mean ( 33 / 67 ) 15.4625925925926 0.0218148303004823 708.811041828309 Trimmed Mean ( 34 / 67 ) 15.4613533834586 0.0208075685626252 743.063916234332 Trimmed Mean ( 35 / 67 ) 15.4652671755725 0.0205632171205608 752.08402872472 Trimmed Mean ( 36 / 67 ) 15.4693023255814 0.0202889692407029 762.448902261012 Trimmed Mean ( 37 / 67 ) 15.4734645669291 0.0199810489994785 774.407017736307 Trimmed Mean ( 38 / 67 ) 15.47776 0.0196350128350419 788.273485229275 Trimmed Mean ( 39 / 67 ) 15.4821951219512 0.0192455795151128 804.454607864297 Trimmed Mean ( 40 / 67 ) 15.4867768595041 0.0188063990618988 823.484432534451 Trimmed Mean ( 41 / 67 ) 15.4915126050420 0.0183097308026666 846.080850232153 Trimmed Mean ( 42 / 67 ) 15.4964102564103 0.0177459814500474 873.234895462422 Trimmed Mean ( 43 / 67 ) 15.5014782608696 0.0171030187129722 906.359194304812 Trimmed Mean ( 44 / 67 ) 15.5067256637168 0.0163651069930623 947.548077155293 Trimmed Mean ( 45 / 67 ) 15.5121621621622 0.0155111676264832 1000.06411739612 Trimmed Mean ( 46 / 67 ) 15.5177981651376 0.0145117371960978 1069.32739722645 Trimmed Mean ( 47 / 67 ) 15.5236448598131 0.0133231558104889 1165.16274977373 Trimmed Mean ( 48 / 67 ) 15.5297142857143 0.0118750030984050 1307.76507231398 Trimmed Mean ( 49 / 67 ) 15.5360194174757 0.0100373752391222 1547.81693892660 Trimmed Mean ( 50 / 67 ) 15.5425742574257 0.00750267736415639 2071.60370932109 Trimmed Mean ( 51 / 67 ) 15.5493939393939 0.00267769127172160 5807.01520881328 Trimmed Mean ( 52 / 67 ) 15.5495876288660 0.00269400794693575 5771.9160207202 Trimmed Mean ( 53 / 67 ) 15.5497894736842 0.00271026809237602 5737.36211462834 Trimmed Mean ( 54 / 67 ) 15.55 0.00272642257989322 5703.4445484269 Trimmed Mean ( 55 / 67 ) 15.55 0.00274241331996734 5670.18832893694 Trimmed Mean ( 56 / 67 ) 15.5504494382022 0.002758171591856 5637.9557690021 Trimmed Mean ( 57 / 67 ) 15.5506896551724 0.00277361602039819 5606.64833949866 Trimmed Mean ( 58 / 67 ) 15.5509411764706 0.00278865011274453 5576.51212871796 Trimmed Mean ( 59 / 67 ) 15.5512048192771 0.00280315924349400 5547.74219672703 Trimmed Mean ( 60 / 67 ) 15.5512048192771 0.00281700694367506 5520.47088637598 Trimmed Mean ( 61 / 67 ) 15.5517721518987 0.00283003030452572 5495.2670036885 Trimmed Mean ( 62 / 67 ) 15.5520779220779 0.00284203424647853 5472.16415190914 Trimmed Mean ( 63 / 67 ) 15.5524 0.00285278432034014 5451.65643582396 Trimmed Mean ( 64 / 67 ) 15.5527397260274 0.00286199759120225 5434.2253025776 Trimmed Mean ( 65 / 67 ) 15.5530985915493 0.00286933099063774 5420.46164848079 Trimmed Mean ( 66 / 67 ) 15.5534782608696 0.00287436628514859 5411.09821014531 Trimmed Mean ( 67 / 67 ) 15.5538805970149 0.00287659046036173 5407.05422316496 Median 15.57 Midrange 15.56 Midmean - Weighted Average at Xnp 15.3348502994012 Midmean - Weighted Average at X(n+1)p 15.3348502994012 Midmean - Empirical Distribution Function 15.3348502994012 Midmean - Empirical Distribution Function - Averaging 15.3348502994012 Midmean - Empirical Distribution Function - Interpolation 15.3348502994012 Midmean - Closest Observation 15.3348502994012 Midmean - True Basic - Statistics Graphics Toolkit 15.3348502994012 Midmean - MS Excel (old versions) 15.3348502994012 Number of observations 201

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Nov/22/t1290437451795krc8143jhiwp/1dyau1290437571.png (open in new window) http://www.freestatistics.org/blog/date/2010/Nov/22/t1290437451795krc8143jhiwp/1dyau1290437571.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Nov/22/t1290437451795krc8143jhiwp/2dyau1290437571.png (open in new window) http://www.freestatistics.org/blog/date/2010/Nov/22/t1290437451795krc8143jhiwp/2dyau1290437571.ps (open in new window)

Parameters (Session):

par1 = Default ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;

Parameters (R input):

par1 = Default ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;

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')

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