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*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: Fri, 11 Dec 2009 07:14:56 -0700

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2009/Dec/11/t1260540934j3x0cairjw9j55s.htm/, Retrieved Fri, 11 Dec 2009 15:15:37 +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/2009/Dec/11/t1260540934j3x0cairjw9j55s.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:

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No (this computation is public)

User-defined keywords:

Dataseries X:

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4716.99 4926.65 4920.10 5170.09 5246.24 5283.61 4979.05 4825.20 4695.12 4711.54 4727.22 4384.96 4378.75 4472.93 4564.07 4310.54 4171.38 4049.38 3591.37 3720.46 4107.23 4101.71 4162.34 4136.22 4125.88 4031.48 3761.36 3408.56 3228.47 3090.45 2741.14 2980.44 3104.33 3181.57 2863.86 2898.01 3112.33 3254.33 3513.47 3587.61 3727.45 3793.34 3817.58 3845.13 3931.86 4197.52 4307.13 4229.43 4362.28 4217.34 4361.28 4327.74 4417.65 4557.68 4650.35 4967.18 5123.42 5290.85 5535.66 5514.06 5493.88 5694.83 5850.41 6116.64 6175.00 6513.58 6383.78 6673.66 6936.61 7300.68 7392.93 7497.31 7584.71 7160.79 7196.19 7245.63 7347.51 7425.75 7778.51 7822.33 8181.22 8371.47 8347.71 8672.11 8802.79 9138.46 9123.29 9023.21 8850.41 8864.58 9163.74 8516.66 8553.44 7555.20 7851.22 7442.00 7992.53 8264.04 7517.39 7200.40 7193.69 6193.58 5104.21 4800.46 4461.61 4398.59 4243.63 4293.82

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	2 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

Central Tendency - Ungrouped Data
Measure	Value	S.E.	Value/S.E.
Arithmetic Mean	5519.66259259259	177.597852012292	31.0795571570909
Geometric Mean	5226.71809740505
Harmonic Mean	4955.83241581034
Quadratic Mean	5817.35006848304
Winsorized Mean ( 1 / 36 )	5520.56481481481	177.390503674078	31.1209715315867
Winsorized Mean ( 2 / 36 )	5520.9162962963	177.249061503983	31.1477885944814
Winsorized Mean ( 3 / 36 )	5520.42601851852	176.414699977802	31.2923243880082
Winsorized Mean ( 4 / 36 )	5518.62527777778	174.805353861678	31.5701158795435
Winsorized Mean ( 5 / 36 )	5518.61185185185	174.604950615898	31.6062736616894
Winsorized Mean ( 6 / 36 )	5516.41074074074	174.078262797821	31.6892566141221
Winsorized Mean ( 7 / 36 )	5512.42851851852	172.030190766468	32.0433785137265
Winsorized Mean ( 8 / 36 )	5507.11222222222	170.102566429515	32.3752447586039
Winsorized Mean ( 9 / 36 )	5506.20222222222	169.322597207267	32.5190040374948
Winsorized Mean ( 10 / 36 )	5507.03925925926	165.382608714169	33.2987809424211
Winsorized Mean ( 11 / 36 )	5515.30453703704	163.747047968359	33.6818562866719
Winsorized Mean ( 12 / 36 )	5514.24564814815	161.324642986825	34.1810497519495
Winsorized Mean ( 13 / 36 )	5504.72916666667	159.699207166832	34.4693581409960
Winsorized Mean ( 14 / 36 )	5497.00324074074	154.092384139537	35.6734258570688
Winsorized Mean ( 15 / 36 )	5478.34768518519	151.061164631552	36.2657583009321
Winsorized Mean ( 16 / 36 )	5479.09138888889	149.893219149026	36.5532972071371
Winsorized Mean ( 17 / 36 )	5477.22768518519	148.352767539453	36.9202932714321
Winsorized Mean ( 18 / 36 )	5448.96768518519	143.331670821917	38.0164945677308
Winsorized Mean ( 19 / 36 )	5448.62287037037	142.097161643948	38.3443469759300
Winsorized Mean ( 20 / 36 )	5457.68212962963	139.460561935974	39.1342330323841
Winsorized Mean ( 21 / 36 )	5473.14824074074	136.978147951340	39.9563603581867
Winsorized Mean ( 22 / 36 )	5465.52768518518	135.071715035408	40.4638949298336
Winsorized Mean ( 23 / 36 )	5473.21138888889	133.517611676459	40.9924302881602
Winsorized Mean ( 24 / 36 )	5467.14472222222	132.405758591644	41.2908379542885
Winsorized Mean ( 25 / 36 )	5460.94796296296	130.567785936451	41.8246194786583
Winsorized Mean ( 26 / 36 )	5452.16333333333	128.812781001978	42.3262605692025
Winsorized Mean ( 27 / 36 )	5444.93083333333	126.351816417272	43.0934116162736
Winsorized Mean ( 28 / 36 )	5435.54824074074	124.572242542331	43.6337030610464
Winsorized Mean ( 29 / 36 )	5441.43685185185	123.759974522802	43.9676629930892
Winsorized Mean ( 30 / 36 )	5446.24796296296	123.152610061808	44.22356911664
Winsorized Mean ( 31 / 36 )	5440.27472222222	121.578640962938	44.746961136707
Winsorized Mean ( 32 / 36 )	5378.05842592593	112.488041765290	47.8100457748869
Winsorized Mean ( 33 / 36 )	5313.04842592593	100.761592987578	52.7289046192524
Winsorized Mean ( 34 / 36 )	5266.84305555556	94.0604917753613	55.9942113436322
Winsorized Mean ( 35 / 36 )	5225.88333333333	88.7844531318974	58.8603426499661
Winsorized Mean ( 36 / 36 )	5168.21666666667	80.5913471553252	64.128679431377
Trimmed Mean ( 1 / 36 )	5511.49698113208	175.672550810248	31.3736947275576
Trimmed Mean ( 2 / 36 )	5502.08038461538	173.729018916807	31.6704740458481
Trimmed Mean ( 3 / 36 )	5492.10843137255	171.612499714546	32.0029627242067
Trimmed Mean ( 4 / 36 )	5481.9141	169.555303174951	32.3311273510782
Trimmed Mean ( 5 / 36 )	5471.79979591837	167.732477698252	32.6221842722795
Trimmed Mean ( 6 / 36 )	5461.26708333333	165.70324074441	32.9581187356323
Trimmed Mean ( 7 / 36 )	5450.70765957447	163.509057277826	33.3358148491610
Trimmed Mean ( 8 / 36 )	5440.35695652174	161.434291197035	33.7001322097152
Trimmed Mean ( 9 / 36 )	5430.34366666667	159.427108102696	34.0616080370013
Trimmed Mean ( 10 / 36 )	5419.99931818182	157.252563898939	34.4668422809632
Trimmed Mean ( 11 / 36 )	5409.06872093023	155.409986666643	34.8051552988854
Trimmed Mean ( 12 / 36 )	5396.65154761905	153.516437043955	35.1535747672015
Trimmed Mean ( 13 / 36 )	5383.74487804878	151.675865195832	35.4950662130572
Trimmed Mean ( 14 / 36 )	5371.181125	149.763463614663	35.8644291161687
Trimmed Mean ( 15 / 36 )	5358.73717948718	148.330397299184	36.127033143979
Trimmed Mean ( 16 / 36 )	5347.40565789474	147.052994916123	36.3637997372636
Trimmed Mean ( 17 / 36 )	5335.39378378378	145.657020101848	36.6298430384825
Trimmed Mean ( 18 / 36 )	5322.87902777778	144.168487035125	36.9212380406055
Trimmed Mean ( 19 / 36 )	5312.07142857143	143.066571803297	37.1300672240543
Trimmed Mean ( 20 / 36 )	5300.6569117647	141.846169272648	37.369052255307
Trimmed Mean ( 21 / 36 )	5287.80939393939	140.652695293174	37.594796053624
Trimmed Mean ( 22 / 36 )	5272.91609375	139.439240511150	37.8151521366639
Trimmed Mean ( 23 / 36 )	5257.66532258064	138.148027713644	38.0582003926893
Trimmed Mean ( 24 / 36 )	5240.7965	136.672636251289	38.3456165311992
Trimmed Mean ( 25 / 36 )	5223.235	134.931331209617	38.7103199321858
Trimmed Mean ( 26 / 36 )	5204.89714285714	132.966901786237	39.1443063870492
Trimmed Mean ( 27 / 36 )	5185.87666666667	130.714712760292	39.6732437929667
Trimmed Mean ( 28 / 36 )	5165.94942307692	128.205849344187	40.2941788498916
Trimmed Mean ( 29 / 36 )	5145.1518	125.259647756070	41.0758922938986
Trimmed Mean ( 30 / 36 )	5122.16416666667	121.512193654111	42.1534992714155
Trimmed Mean ( 31 / 36 )	5096.80108695652	116.657978550300	43.6901200440302
Trimmed Mean ( 32 / 36 )	5069.60522727273	110.557586206513	45.8548834252141
Trimmed Mean ( 33 / 36 )	5044.81880952381	104.853563667281	48.1129933316518
Trimmed Mean ( 34 / 36 )	5022.87275	100.306404307634	50.075294640162
Trimmed Mean ( 35 / 36 )	5002.47894736842	95.9546046799593	52.133808107004
Trimmed Mean ( 36 / 36 )	4983.33	91.4845449537616	54.4718236563202
Median	4872.65
Midrange	5952.44
Midmean - Weighted Average at Xnp	5166.792
Midmean - Weighted Average at X(n+1)p	5185.87666666667
Midmean - Empirical Distribution Function	5166.792
Midmean - Empirical Distribution Function - Averaging	5185.87666666667
Midmean - Empirical Distribution Function - Interpolation	5185.87666666667
Midmean - Closest Observation	5166.792
Midmean - True Basic - Statistics Graphics Toolkit	5185.87666666667
Midmean - MS Excel (old versions)	5204.89714285714
Number of observations	108

Charts produced by software:

http://www.freestatistics.org/blog/date/2009/Dec/11/t1260540934j3x0cairjw9j55s/1cpdj1260540893.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/11/t1260540934j3x0cairjw9j55s/1cpdj1260540893.ps (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/11/t1260540934j3x0cairjw9j55s/28mmy1260540893.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/11/t1260540934j3x0cairjw9j55s/28mmy1260540893.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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