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dit is een test

R Software Module: rwasp_centraltendency.wasp (opens new window with default values)
Title produced by software: Central Tendency
Date of computation: Tue, 06 Nov 2007 01:21:41 -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/Nov/06/vmbm6gu636lvumb1194337962.htm/, Retrieved Tue, 06 Nov 2007 09:32:45 +0100
 
User-defined keywords:
 
Dataseries X:
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112 118 132 129 121 135 148 148 136 119 104 118 115 126 141 135 125 149 170 170 158 133 114 140 145 150 178 163 172 178 199 199 184 162 146 166 171 180 193 181 183 218 230 242 209 191 172 194 196 196 236 235 229 243 264 272 237 211 180 201 204 188 235 227 234 264 302 293 259 229 203 229 242 233 267 269 270 315 364 347 312 274 237 278 284 277 317 313 318 374 413 405 355 306 271 306 315 301 356 348 355 422 465 467 404 347 305 336 340 318 362 348 363 435 491 505 404 359 310 337 360 342 406 396 420 472 548 559 463 407 362 405 417 391 419 461 472 535 622 606 508 461 390 432
 
Text written by user:
help, ik snap er niets van...
 
Output produced by software:


Summary of compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135


Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean280.2986111111119.997193078578628.0377310819092
Geometric Mean255.232771586034
Harmonic Mean231.659113395685
Quadratic Mean304.728214516185
Winsorized Mean ( 1 / 48 )280.2430555555569.9645069740258428.1241265911154
Winsorized Mean ( 2 / 48 )279.6180555555569.8216170003681628.4696558158472
Winsorized Mean ( 3 / 48 )279.4097222222229.7743500509972228.5860155165730
Winsorized Mean ( 4 / 48 )279.1319444444449.696588038729428.7866147689843
Winsorized Mean ( 5 / 48 )278.1944444444449.5309900099064929.1884100345599
Winsorized Mean ( 6 / 48 )278.1111111111119.5051314766914729.2590493664497
Winsorized Mean ( 7 / 48 )277.5277777777789.382813731304729.5783104861005
Winsorized Mean ( 8 / 48 )276.6944444444449.1946081765340230.093119699283
Winsorized Mean ( 9 / 48 )276.7569444444449.1874168963664430.1234773131825
Winsorized Mean ( 10 / 48 )276.6180555555569.1124962044078530.3559035143138
Winsorized Mean ( 11 / 48 )276.6944444444449.0644667186615930.5251762770331
Winsorized Mean ( 12 / 48 )276.6111111111119.0310486573546130.6289027560324
Winsorized Mean ( 13 / 48 )276.6111111111118.9850741245258330.7856237219088
Winsorized Mean ( 14 / 48 )276.6111111111118.9850741245258330.7856237219088
Winsorized Mean ( 15 / 48 )274.0069444444448.6015433404016731.8555558695411
Winsorized Mean ( 16 / 48 )274.1180555555568.5086711137958932.2163181405734
Winsorized Mean ( 17 / 48 )273.0555555555568.3453397061690432.7195255279671
Winsorized Mean ( 18 / 48 )273.3055555555568.2593879961929833.0902913970782
Winsorized Mean ( 19 / 48 )273.3055555555568.2287214569472133.2136112499972
Winsorized Mean ( 20 / 48 )273.3055555555568.1644975817981333.4748773966032
Winsorized Mean ( 21 / 48 )272.7222222222228.0932456973264233.6975093085726
Winsorized Mean ( 22 / 48 )271.9583333333337.9668777890411234.1361246569424
Winsorized Mean ( 23 / 48 )271.9583333333337.9307651116654734.2915632355958
Winsorized Mean ( 24 / 48 )273.1257.7702343504502435.1501624895231
Winsorized Mean ( 25 / 48 )273.8194444444447.6989896610193935.5656334792622
Winsorized Mean ( 26 / 48 )273.8194444444447.6591990892894535.7504017394392
Winsorized Mean ( 27 / 48 )274.3819444444447.6027026420772236.0900534141472
Winsorized Mean ( 28 / 48 )273.6041666666677.3421171352531437.2650233749279
Winsorized Mean ( 29 / 48 )272.5972222222227.2257237604357337.7259401632292
Winsorized Mean ( 30 / 48 )272.5972222222227.1812295758525837.9596863382352
Winsorized Mean ( 31 / 48 )269.3680555555566.776604786239439.7497071250983
Winsorized Mean ( 32 / 48 )267.1458333333336.5415040419706940.8385948582022
Winsorized Mean ( 33 / 48 )268.2916666666676.3797516456838742.0536223926797
Winsorized Mean ( 34 / 48 )268.0555555555566.3552923954298242.1783198753087
Winsorized Mean ( 35 / 48 )268.5416666666676.3073466602048242.5760119324005
Winsorized Mean ( 36 / 48 )268.0416666666676.2557423115635842.8472998593945
Winsorized Mean ( 37 / 48 )268.0416666666676.2041157589480343.2038467818846
Winsorized Mean ( 38 / 48 )267.7777777777786.071650694548344.1029616572334
Winsorized Mean ( 39 / 48 )267.7777777777786.0177593010267344.4979209673758
Winsorized Mean ( 40 / 48 )268.8888888888895.9104962334504945.4934540634864
Winsorized Mean ( 41 / 48 )267.755.6279399638063247.575134369222
Winsorized Mean ( 42 / 48 )268.3333333333335.5725507335798848.1526945490817
Winsorized Mean ( 43 / 48 )268.3333333333335.514540713890848.6592351485261
Winsorized Mean ( 44 / 48 )268.9444444444445.4571757413916749.2827164066846
Winsorized Mean ( 45 / 48 )267.3819444444445.3021285961704250.4291700200495
Winsorized Mean ( 46 / 48 )267.7013888888895.1495041653448151.985857335638
Winsorized Mean ( 47 / 48 )266.7222222222225.0538230165681352.776328206947
Winsorized Mean ( 48 / 48 )267.0555555555564.9591256421463953.851338890452
Trimmed Mean ( 1 / 48 )279.1338028169019.7670664859418828.5790829025961
Trimmed Mean ( 2 / 48 )277.9928571428579.5506788899452629.1071305345133
Trimmed Mean ( 3 / 48 )277.1449275362329.3959503776844629.4962102178036
Trimmed Mean ( 4 / 48 )276.3455882352949.2453684964841229.8901648258135
Trimmed Mean ( 5 / 48 )275.5970149253739.1045136697159930.2703719191593
Trimmed Mean ( 6 / 48 )275.0303030303038.992806512939930.58336712066
Trimmed Mean ( 7 / 48 )274.4615384615388.8758088403033430.9224255952045
Trimmed Mean ( 8 / 48 )273.968758.771310785799531.2346417417506
Trimmed Mean ( 9 / 48 )273.5793650793658.689503634788231.4838886750789
Trimmed Mean ( 10 / 48 )273.1693548387108.6001277884231931.7634064933813
Trimmed Mean ( 11 / 48 )272.7622950819678.5125094499631432.0425247907535
Trimmed Mean ( 12 / 48 )272.3333333333338.4220958998580232.3355773398311
Trimmed Mean ( 13 / 48 )271.8983050847468.326223736714132.6556568358622
Trimmed Mean ( 14 / 48 )271.4482758620698.2255985489442533.0004283879024
Trimmed Mean ( 15 / 48 )270.9824561403518.1135492916336633.3987563765437
Trimmed Mean ( 16 / 48 )270.7232142857148.0363176789761233.6874704435783
Trimmed Mean ( 17 / 48 )270.4454545454557.9603959897860133.9738695025302
Trimmed Mean ( 18 / 48 )270.2407407407417.8936539917867534.2351895613771
Trimmed Mean ( 19 / 48 )270.0094339622647.8275034636299634.4949619271135
Trimmed Mean ( 20 / 48 )269.7692307692317.7557855102809834.7829669105247
Trimmed Mean ( 21 / 48 )269.5196078431377.6812813492798335.0878447992803
Trimmed Mean ( 22 / 48 )269.37.6043647753355235.4138718954494
Trimmed Mean ( 23 / 48 )269.1224489795927.5303197410261235.7385155258919
Trimmed Mean ( 24 / 48 )268.93757.4495056426702236.1013888572076
Trimmed Mean ( 25 / 48 )268.6702127659577.3734948023350736.4372960134011
Trimmed Mean ( 26 / 48 )268.3478260869577.2932145319424636.7941769588239
Trimmed Mean ( 27 / 48 )268.0111111111117.2049104916106337.1983956529623
Trimmed Mean ( 28 / 48 )267.6257.1087667280576437.6471771036893
Trimmed Mean ( 29 / 48 )267.2674418604657.0261466812921538.0389784022148
Trimmed Mean ( 30 / 48 )266.9523809523816.9430497192425538.4488649436755
Trimmed Mean ( 31 / 48 )266.6219512195126.8508355460910938.9181654450368
Trimmed Mean ( 32 / 48 )266.46256.7885081541426139.251996749447
Trimmed Mean ( 33 / 48 )266.4230769230776.7396896313749139.5304667566311
Trimmed Mean ( 34 / 48 )266.3157894736846.6972948329462939.7646805339352
Trimmed Mean ( 35 / 48 )266.2162162162166.6475024823033340.047554239344
Trimmed Mean ( 36 / 48 )266.0833333333336.5914403046310740.3680107891422
Trimmed Mean ( 37 / 48 )265.9714285714296.5286427820013140.7391608719472
Trimmed Mean ( 38 / 48 )265.8529411764716.4577122667302341.1682853301052
Trimmed Mean ( 39 / 48 )265.7424242424246.3869516827432841.6070822894161
Trimmed Mean ( 40 / 48 )265.6256.3063530892041142.1202232483184
Trimmed Mean ( 41 / 48 )265.4354838709686.2203764786881342.6719322826177
Trimmed Mean ( 42 / 48 )265.36.1519965984136143.1242111005737
Trimmed Mean ( 43 / 48 )265.1206896551726.0725138976397443.6591326300989
Trimmed Mean ( 44 / 48 )264.9285714285715.9800999613141844.3016961492983
Trimmed Mean ( 45 / 48 )264.6851851851855.8711903701069345.0820308148796
Trimmed Mean ( 46 / 48 )264.5192307692315.759082955571345.9307901639681
Trimmed Mean ( 47 / 48 )264.325.6412069919947646.8552209438666
Trimmed Mean ( 48 / 48 )264.1666666666675.5069534811024147.9696564667156
Median265.5
Midrange363
Midmean - Weighted Average at Xnp264.904109589041
Midmean - Weighted Average at X(n+1)p264.904109589041
Midmean - Empirical Distribution Function264.904109589041
Midmean - Empirical Distribution Function - Averaging264.904109589041
Midmean - Empirical Distribution Function - Interpolation264.904109589041
Midmean - Closest Observation264.904109589041
Midmean - True Basic - Statistics Graphics Toolkit264.904109589041
Midmean - MS Excel (old versions)267.493333333333
Number of observations144
 
Charts produced by software:
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Nov/06/vmbm6gu636lvumb1194337962/1t5ns1194337298.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Nov/06/vmbm6gu636lvumb1194337962/1t5ns1194337298.ps (open in new window)


http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Nov/06/vmbm6gu636lvumb1194337962/2eaav1194337298.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Nov/06/vmbm6gu636lvumb1194337962/2eaav1194337298.ps (open in new window)


 
Parameters:
 
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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