Home » date » 2010 » Jul » 07 »

Kelly Janbroers - 2de zit - Stap 14/A

*Unverified author*

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

Title produced by software: Central Tendency

Date of computation: Wed, 07 Jul 2010 17:07:33 +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/Jul/07/t127852250494s6gde8w0lzsq3.htm/, Retrieved Wed, 07 Jul 2010 19:08:27 +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/2010/Jul/07/t127852250494s6gde8w0lzsq3.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:

» Textbox « » Textfile « » CSV «

33 32 31 29 49 48 33 23 24 24 25 27 24 21 15 21 49 48 35 36 51 50 61 63 61 62 58 65 93 94 86 88 102 107 121 127 125 128 117 127 160 162 153 160 177 178 196 212 212 211 204 216 248 250 240 249 275 277 286 302 290 290 277 285 311 300 291 299 332 337 343 360 353 351 341 348 381 358 353 358 399 409 407 419 418 421 414 424 463 437 430 436 474 489 482 492 502 500 493 504 538 516 502 501 541 571 559 569 576 573 562 570 597 573 562 556 600 630 624 634

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	'George Udny Yule' @ 72.249.76.132

Central Tendency - Ungrouped Data
Measure	Value	S.E.	Value/S.E.
Arithmetic Mean	280.883333333333	17.6594741846426	15.9055320898287
Geometric Mean	188.536604065998
Harmonic Mean	100.761858431261
Quadratic Mean	340.597171646115
Winsorized Mean ( 1 / 40 )	280.9	17.6476460686604	15.9171369885322
Winsorized Mean ( 2 / 40 )	280.8	17.6311555792246	15.9263525716304
Winsorized Mean ( 3 / 40 )	280.25	17.5299114121449	15.9869604250162
Winsorized Mean ( 4 / 40 )	280.183333333333	17.5105409763599	16.0008382214801
Winsorized Mean ( 5 / 40 )	279.308333333333	17.3812529639985	16.0695166172347
Winsorized Mean ( 6 / 40 )	279.158333333333	17.3598267517452	16.0807096364179
Winsorized Mean ( 7 / 40 )	279.216666666667	17.3526335529555	16.0907372252502
Winsorized Mean ( 8 / 40 )	279.216666666667	17.3173428045815	16.1235282928508
Winsorized Mean ( 9 / 40 )	279.291666666667	17.2884305635071	16.1548305753215
Winsorized Mean ( 10 / 40 )	279.375	17.2564487296519	16.1895998636120
Winsorized Mean ( 11 / 40 )	278.825	17.1556095410653	16.2527014462866
Winsorized Mean ( 12 / 40 )	278.925	17.1435370648894	16.2699796981364
Winsorized Mean ( 13 / 40 )	278.6	17.0985952868741	16.2937361418145
Winsorized Mean ( 14 / 40 )	278.483333333333	17.0223982588723	16.3598177588275
Winsorized Mean ( 15 / 40 )	276.733333333333	16.7546086027230	16.5168485814917
Winsorized Mean ( 16 / 40 )	277.933333333333	16.5113946451509	16.8328199589704
Winsorized Mean ( 17 / 40 )	274.816666666667	16.1089471082825	17.0598776455954
Winsorized Mean ( 18 / 40 )	273.166666666667	15.8678909326894	17.2150582472127
Winsorized Mean ( 19 / 40 )	272.85	15.82927406317	17.2370507270981
Winsorized Mean ( 20 / 40 )	273.016666666667	15.8094925183619	17.2691606861872
Winsorized Mean ( 21 / 40 )	273.016666666667	15.7674849960261	17.3151689527833
Winsorized Mean ( 22 / 40 )	274.116666666667	15.5945304969157	17.5777441148922
Winsorized Mean ( 23 / 40 )	273.35	15.3654121114841	17.7899556495265
Winsorized Mean ( 24 / 40 )	273.15	15.3414117526982	17.8047499410841
Winsorized Mean ( 25 / 40 )	272.733333333333	15.2424832617609	17.8929724671271
Winsorized Mean ( 26 / 40 )	271.433333333333	15.0376219761153	18.0502830676592
Winsorized Mean ( 27 / 40 )	270.083333333333	14.7748726021862	18.2799094520362
Winsorized Mean ( 28 / 40 )	272.416666666667	13.9164452589778	19.5751617311127
Winsorized Mean ( 29 / 40 )	266.616666666667	13.157711648193	20.2631486230573
Winsorized Mean ( 30 / 40 )	267.616666666667	12.9885814069687	20.6039950231273
Winsorized Mean ( 31 / 40 )	266.325	12.7915969578115	20.8203089010995
Winsorized Mean ( 32 / 40 )	266.858333333333	12.3800932185467	21.5554381233213
Winsorized Mean ( 33 / 40 )	267.408333333333	12.1389509871774	22.0289490925371
Winsorized Mean ( 34 / 40 )	269.675	11.7667882479574	22.9183184329685
Winsorized Mean ( 35 / 40 )	270.55	11.6089157878894	23.3053633038015
Winsorized Mean ( 36 / 40 )	270.55	11.3515497652448	23.8337500689419
Winsorized Mean ( 37 / 40 )	269.625	11.1220631568763	24.2423546959721
Winsorized Mean ( 38 / 40 )	268.991666666667	11.0554972309832	24.3310328831538
Winsorized Mean ( 39 / 40 )	266.716666666667	10.7495044725433	24.8119964364796
Winsorized Mean ( 40 / 40 )	269.05	9.241036614097	29.1146990576328
Trimmed Mean ( 1 / 40 )	280.14406779661	17.5615235469265	15.9521505664375
Trimmed Mean ( 2 / 40 )	279.362068965517	17.4632679249747	15.9971243736113
Trimmed Mean ( 3 / 40 )	278.605263157895	17.3609123018984	16.0478469283800
Trimmed Mean ( 4 / 40 )	278.017857142857	17.2842090901237	16.0850783332468
Trimmed Mean ( 5 / 40 )	277.427272727273	17.2013317709433	16.1282438139997
Trimmed Mean ( 6 / 40 )	277.009259259259	17.1383942617028	16.1630812682527
Trimmed Mean ( 7 / 40 )	276.603773584906	17.0687509918399	16.2052732339433
Trimmed Mean ( 8 / 40 )	276.173076923077	16.9881808972987	16.2567774968179
Trimmed Mean ( 9 / 40 )	275.725490196078	16.9002300156012	16.3148957109783
Trimmed Mean ( 10 / 40 )	275.25	16.8022988747001	16.3816869377592
Trimmed Mean ( 11 / 40 )	274.744897959184	16.6931963626539	16.4584955445587
Trimmed Mean ( 12 / 40 )	274.28125	16.5814953344809	16.5414062162197
Trimmed Mean ( 13 / 40 )	273.787234042553	16.4530548402398	16.6405106347146
Trimmed Mean ( 14 / 40 )	273.304347826087	16.3101929321983	16.7566594069253
Trimmed Mean ( 15 / 40 )	272.811111111111	16.1547285505802	16.8873844123684
Trimmed Mean ( 16 / 40 )	272.454545454545	16.0100372537344	17.0177333841615
Trimmed Mean ( 17 / 40 )	271.976744186047	15.8717584386697	17.1358923610762
Trimmed Mean ( 18 / 40 )	271.738095238095	15.7603440614793	17.2418885132250
Trimmed Mean ( 19 / 40 )	271.621951219512	15.6568771452148	17.3484117362783
Trimmed Mean ( 20 / 40 )	271.525	15.5366550555921	17.4764129748939
Trimmed Mean ( 21 / 40 )	271.410256410256	15.3945602777842	17.6302701417153
Trimmed Mean ( 22 / 40 )	271.289473684211	15.2297241198991	17.8131574510759
Trimmed Mean ( 23 / 40 )	271.081081081081	15.0543844021776	18.0067861852836
Trimmed Mean ( 24 / 40 )	270.916666666667	14.8735903318053	18.2146113092375
Trimmed Mean ( 25 / 40 )	270.757142857143	14.6593540359477	18.4699231762321
Trimmed Mean ( 26 / 40 )	270.617647058824	14.4152944916753	18.7729530752982
Trimmed Mean ( 27 / 40 )	270.560606060606	14.1499813237644	19.1209161249004
Trimmed Mean ( 28 / 40 )	270.59375	13.8668326231699	19.5137388150102
Trimmed Mean ( 29 / 40 )	270.467741935484	13.6455608691665	19.8209325749763
Trimmed Mean ( 30 / 40 )	270.733333333333	13.4792342207897	20.0852161850388
Trimmed Mean ( 31 / 40 )	270.948275862069	13.2940685256086	20.3811403063055
Trimmed Mean ( 32 / 40 )	271.267857142857	13.0888941491014	20.7250401793095
Trimmed Mean ( 33 / 40 )	271.574074074074	12.8920585052598	21.0652219708184
Trimmed Mean ( 34 / 40 )	271.865384615385	12.6780242656598	21.443829016148
Trimmed Mean ( 35 / 40 )	272.02	12.4642997134592	21.8239296433371
Trimmed Mean ( 36 / 40 )	272.125	12.2132218566833	22.2811804447069
Trimmed Mean ( 37 / 40 )	272.239130434783	11.9325068446125	22.8149150869919
Trimmed Mean ( 38 / 40 )	272.431818181818	11.6079544484389	23.4694079298749
Trimmed Mean ( 39 / 40 )	272.690476190476	11.1913713285200	24.3661360333522
Trimmed Mean ( 40 / 40 )	273.15	10.7051718869061	25.5157042675886
Median	285.5
Midrange	324.5
Midmean - Weighted Average at Xnp	267.737704918033
Midmean - Weighted Average at X(n+1)p	270.733333333333
Midmean - Empirical Distribution Function	267.737704918033
Midmean - Empirical Distribution Function - Averaging	270.733333333333
Midmean - Empirical Distribution Function - Interpolation	270.733333333333
Midmean - Closest Observation	267.737704918033
Midmean - True Basic - Statistics Graphics Toolkit	270.733333333333
Midmean - MS Excel (old versions)	270.467741935484
Number of observations	120

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Jul/07/t127852250494s6gde8w0lzsq3/12onm1278522449.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Jul/07/t127852250494s6gde8w0lzsq3/12onm1278522449.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Jul/07/t127852250494s6gde8w0lzsq3/2dx4p1278522449.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Jul/07/t127852250494s6gde8w0lzsq3/2dx4p1278522449.ps (open in new window)

Parameters (Session):

par1 = 0.1 ; par2 = 0.99 ; par3 = 0.01 ;

Parameters (R input):

par1 = 0.1 ; par2 = 0.99 ; par3 = 0.01 ;

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')

This work is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 3.0 License.

Software written by Ed van Stee & Patrick Wessa

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