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Tijdreeks 1 - Stap 14

*Unverified author*

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

Title produced by software: Central Tendency

Date of computation: Sat, 24 Jul 2010 13:49:30 +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/24/t12799794017zzpaki9ccwy4tz.htm/, Retrieved Sat, 24 Jul 2010 15:50:03 +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/24/t12799794017zzpaki9ccwy4tz.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:

Habimana Christelle

Dataseries X:

» Textbox « » Textfile « » CSV «

900 899 898 896 916 915 900 890 891 891 892 894 896 889 878 883 901 897 881 866 867 866 862 871 865 856 847 859 870 872 856 839 829 825 822 827 822 812 810 816 820 823 810 793 777 772 765 765 753 742 736 740 742 742 728 707 699 696 689 692 673 653 642 648 654 653 630 609 598 601 592 591 568 538 523 530 529 534 513 491 480 478 462 461 437 411 400 405 395 407 385 366 349 343 332 327 306 276 269 268 260 274 247 226 212 199 188 179 155 124 117 116 105 112 86 64 53 42 32 24

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	1 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

Central Tendency - Ungrouped Data
Measure	Value	S.E.	Value/S.E.
Arithmetic Mean	599.158333333333	24.9486447200246	24.0156665845832
Geometric Mean	491.768184236028
Harmonic Mean	306.561078944024
Quadratic Mean	658.073292523966
Winsorized Mean ( 1 / 40 )	599.216666666667	24.9349270281873	24.0312179774695
Winsorized Mean ( 2 / 40 )	599.15	24.8790031335415	24.0825565551795
Winsorized Mean ( 3 / 40 )	599.4	24.8251487650020	24.1448704164473
Winsorized Mean ( 4 / 40 )	599.766666666667	24.7578998323426	24.2252642884983
Winsorized Mean ( 5 / 40 )	600.641666666667	24.5896854894416	24.426569706415
Winsorized Mean ( 6 / 40 )	601.541666666667	24.4198738225993	24.6332831625842
Winsorized Mean ( 7 / 40 )	601.891666666667	24.3445154724858	24.723912346784
Winsorized Mean ( 8 / 40 )	602.091666666667	24.2927638354835	24.7848153772942
Winsorized Mean ( 9 / 40 )	602.166666666667	24.2801613907637	24.8007687006452
Winsorized Mean ( 10 / 40 )	602.583333333333	24.1657256167594	24.9354537450939
Winsorized Mean ( 11 / 40 )	605.241666666667	23.6835728737514	25.5553361772310
Winsorized Mean ( 12 / 40 )	607.541666666667	23.2961174673439	26.0790952620456
Winsorized Mean ( 13 / 40 )	608.516666666667	23.1463284059078	26.289986731172
Winsorized Mean ( 14 / 40 )	609.683333333333	22.9398524929788	26.5774740059876
Winsorized Mean ( 15 / 40 )	611.183333333333	22.6846083115483	26.9426443225027
Winsorized Mean ( 16 / 40 )	612.25	22.3289741868115	27.4195310038749
Winsorized Mean ( 17 / 40 )	614.941666666667	21.873504097178	28.1135415676724
Winsorized Mean ( 18 / 40 )	616.441666666667	21.5542303354773	28.5995675592291
Winsorized Mean ( 19 / 40 )	616.758333333333	21.2826878127947	28.9793440921757
Winsorized Mean ( 20 / 40 )	616.758333333333	21.2429688345728	29.0335281351806
Winsorized Mean ( 21 / 40 )	617.458333333333	21.1053542924204	29.2560041768681
Winsorized Mean ( 22 / 40 )	617.275	21.0001132533294	29.3938890973427
Winsorized Mean ( 23 / 40 )	622.833333333333	20.2091942263708	30.8193056267728
Winsorized Mean ( 24 / 40 )	627.033333333333	19.6631575941733	31.8887406730208
Winsorized Mean ( 25 / 40 )	627.866666666667	19.5087171973285	32.1839032426307
Winsorized Mean ( 26 / 40 )	629.6	19.1405255906925	32.893558592046
Winsorized Mean ( 27 / 40 )	630.275	18.9024288247884	33.3435986370951
Winsorized Mean ( 28 / 40 )	633.541666666667	18.3399538434386	34.5443435722345
Winsorized Mean ( 29 / 40 )	638.133333333333	17.7837970085436	35.8828507223045
Winsorized Mean ( 30 / 40 )	638.383333333333	17.2559744183839	36.9949165347176
Winsorized Mean ( 31 / 40 )	637.608333333333	16.8945912143972	37.740382424286
Winsorized Mean ( 32 / 40 )	636.275	16.4724579677290	38.6265972720354
Winsorized Mean ( 33 / 40 )	636.275	16.3536244044696	38.9072773266150
Winsorized Mean ( 34 / 40 )	636.841666666667	16.1648501499029	39.3966947272007
Winsorized Mean ( 35 / 40 )	643.841666666667	15.2292104508753	42.2767594382847
Winsorized Mean ( 36 / 40 )	650.741666666667	14.3892490982856	45.2241574401684
Winsorized Mean ( 37 / 40 )	651.05	14.3551045489277	45.3532050415218
Winsorized Mean ( 38 / 40 )	655.483333333333	13.7360011924202	47.7200987500671
Winsorized Mean ( 39 / 40 )	654.833333333333	13.5349704409209	48.3808469469241
Winsorized Mean ( 40 / 40 )	657.166666666667	13.0056835956047	50.5291907061891
Trimmed Mean ( 1 / 40 )	601.347457627119	24.7493720689345	24.2974834251222
Trimmed Mean ( 2 / 40 )	603.551724137931	24.5400121358227	24.5945976227488
Trimmed Mean ( 3 / 40 )	605.868421052632	24.3357381200154	24.8962418178853
Trimmed Mean ( 4 / 40 )	608.178571428571	24.1261505693377	25.2082722306108
Trimmed Mean ( 5 / 40 )	610.472727272727	23.9098240182909	25.5322969673771
Trimmed Mean ( 6 / 40 )	612.657407407407	23.708605733249	25.8411403142199
Trimmed Mean ( 7 / 40 )	614.754716981132	23.5180755217793	26.1396693114549
Trimmed Mean ( 8 / 40 )	616.875	23.3153635539151	26.4578760941695
Trimmed Mean ( 9 / 40 )	619.049019607843	23.0928354307899	26.8069731611416
Trimmed Mean ( 10 / 40 )	621.3	22.8401980390855	27.2020408464407
Trimmed Mean ( 11 / 40 )	623.591836734694	22.5699736520273	27.6292673774868
Trimmed Mean ( 12 / 40 )	625.677083333333	22.3370144327773	28.0107749053166
Trimmed Mean ( 13 / 40 )	627.606382978723	22.1269150625766	28.3639351081614
Trimmed Mean ( 14 / 40 )	629.521739130435	21.9049737148850	28.738758024743
Trimmed Mean ( 15 / 40 )	631.411111111111	21.676315307369	29.1290794656626
Trimmed Mean ( 16 / 40 )	633.25	21.4454317719916	29.5284332221767
Trimmed Mean ( 17 / 40 )	635.081395348837	21.2229660024589	29.9242525891648
Trimmed Mean ( 18 / 40 )	636.77380952381	21.0223657036798	30.2903021714795
Trimmed Mean ( 19 / 40 )	638.426829268293	20.826176045989	30.6550193304090
Trimmed Mean ( 20 / 40 )	640.1375	20.6263683378088	31.0349107276731
Trimmed Mean ( 21 / 40 )	641.935897435897	20.3921457177567	31.4795660211924
Trimmed Mean ( 22 / 40 )	643.776315789474	20.1306486999843	31.9799091119193
Trimmed Mean ( 23 / 40 )	645.72972972973	19.8313632478962	32.5610358530561
Trimmed Mean ( 24 / 40 )	647.388888888889	19.5828019661759	33.0590530408816
Trimmed Mean ( 25 / 40 )	648.842857142857	19.3571278830743	33.5195831252528
Trimmed Mean ( 26 / 40 )	650.323529411765	19.1026229206350	34.0436772538328
Trimmed Mean ( 27 / 40 )	651.772727272727	18.8426040526419	34.5903743161945
Trimmed Mean ( 28 / 40 )	653.265625	18.5564112346775	35.2043084591271
Trimmed Mean ( 29 / 40 )	654.629032258065	18.2861853962591	35.7991028786126
Trimmed Mean ( 30 / 40 )	655.766666666667	18.0341384784285	36.3625169813941
Trimmed Mean ( 31 / 40 )	656.965517241379	17.7931069654888	36.9224733215857
Trimmed Mean ( 32 / 40 )	658.303571428571	17.5383979418159	37.5349888634362
Trimmed Mean ( 33 / 40 )	659.833333333333	17.2737192480276	38.1986834369024
Trimmed Mean ( 34 / 40 )	661.48076923077	16.9503420411708	39.0246266195747
Trimmed Mean ( 35 / 40 )	663.22	16.5655972498699	40.0359848181875
Trimmed Mean ( 36 / 40 )	664.604166666667	16.2473331031264	40.9054312143559
Trimmed Mean ( 37 / 40 )	665.608695652174	15.9899569404474	41.6266721749877
Trimmed Mean ( 38 / 40 )	666.681818181818	15.6482466892439	42.6042502665856
Trimmed Mean ( 39 / 40 )	667.52380952381	15.3199041617514	43.5723228080232
Trimmed Mean ( 40 / 40 )	668.5	14.9122217987247	44.8290006025240
Median	681
Midrange	470
Midmean - Weighted Average at Xnp	651.327868852459
Midmean - Weighted Average at X(n+1)p	655.766666666667
Midmean - Empirical Distribution Function	651.327868852459
Midmean - Empirical Distribution Function - Averaging	655.766666666667
Midmean - Empirical Distribution Function - Interpolation	655.766666666667
Midmean - Closest Observation	651.327868852459
Midmean - True Basic - Statistics Graphics Toolkit	655.766666666667
Midmean - MS Excel (old versions)	657.825396825397
Number of observations	120

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Jul/24/t12799794017zzpaki9ccwy4tz/1an4f1279979368.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Jul/24/t12799794017zzpaki9ccwy4tz/1an4f1279979368.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Jul/24/t12799794017zzpaki9ccwy4tz/23w301279979368.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Jul/24/t12799794017zzpaki9ccwy4tz/23w301279979368.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')

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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