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

Title produced by software: Central Tendency

Date of computation: Sun, 01 Nov 2009 04:35:57 -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/Nov/01/t1257075494vd24ppuempwto3q.htm/, Retrieved Sun, 01 Nov 2009 12:38:16 +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/Nov/01/t1257075494vd24ppuempwto3q.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:

IsPrivate?

No (this computation is public)

User-defined keywords:

KDGP1W52

Dataseries X:

» Textbox « » Textfile « » CSV «

23,98 24,24 24,92 25,46 25,84 26,08 26,18 26,34 26,42 26,38 26,04 25,58 25,65 25,56 25,62 25,62 25,69 25,68 25,68 25,83 25,93 26,11 24,72 24,62 24,65 25,24 25,56 25,9 25,87 25,78 25,78 25,74 25,78 25,73 24,67 24,31 24,56 25 25,38 25,99 26,22 26,19 26,22 26,22 26,61 26,72 25,46 25,48 25,59 25,88 26 26,97 27,2 27,19 27,19 27,19 27,26 26,9 26,11 25,87 26,02 26,31 26,37 26,52 26,86 26,92 26,98 26,98 27,03 26,75 26,39 26,3 26,3 26,52 26,53 26,98 27,22 27,34 27,41 27,47 27,46 27,53 27,21 26,91 26,95 26,91 27,39 27,62 27,79 27,88 27,9 28,09 28,46 28,73 27,93 27,61 27,65 28,19 28,98 28,99 29,02 29 29,04 29,19 29,23 29,26 29,02 28,47 28,53 28,48 28,68 28,89 29,2 29,21 29,15 29,22 29,34 29,13 28,84 28,76

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	'George Udny Yule' @ 72.249.76.132

Central Tendency - Ungrouped Data
Measure	Value	S.E.	Value/S.E.
Arithmetic Mean	26.8301666666667	0.124173964404947	216.069180002742
Geometric Mean	26.7962066202645
Harmonic Mean	26.7624926231037
Quadratic Mean	26.8643392809129
Winsorized Mean ( 1 / 40 )	26.8316666666667	0.123662555519938	216.974868050019
Winsorized Mean ( 2 / 40 )	26.8323333333333	0.123377522555348	217.481537784130
Winsorized Mean ( 3 / 40 )	26.8383333333333	0.122310410845959	219.428036809837
Winsorized Mean ( 4 / 40 )	26.84	0.121946399576814	220.096698985308
Winsorized Mean ( 5 / 40 )	26.8408333333333	0.121688263115301	220.570436673103
Winsorized Mean ( 6 / 40 )	26.8413333333333	0.121456147250556	220.996087402324
Winsorized Mean ( 7 / 40 )	26.8419166666667	0.120644354056595	222.487963705911
Winsorized Mean ( 8 / 40 )	26.8539166666667	0.118529582157389	226.558772737500
Winsorized Mean ( 9 / 40 )	26.8531666666667	0.116641192697092	230.220268206638
Winsorized Mean ( 10 / 40 )	26.8715	0.113836683965436	236.053081168097
Winsorized Mean ( 11 / 40 )	26.8843333333333	0.112341499507846	239.309012707773
Winsorized Mean ( 12 / 40 )	26.8903333333333	0.111139434298583	241.951324505492
Winsorized Mean ( 13 / 40 )	26.88925	0.110966858712379	242.317844372758
Winsorized Mean ( 14 / 40 )	26.8904166666667	0.110530006308624	243.286122608034
Winsorized Mean ( 15 / 40 )	26.8891666666667	0.107703139012417	249.660009106761
Winsorized Mean ( 16 / 40 )	26.8825	0.106668696365493	252.018641981795
Winsorized Mean ( 17 / 40 )	26.874	0.104641605235291	256.819454743385
Winsorized Mean ( 18 / 40 )	26.871	0.103806502281728	258.856616968683
Winsorized Mean ( 19 / 40 )	26.8678333333333	0.102130401028256	263.073806259705
Winsorized Mean ( 20 / 40 )	26.8428333333333	0.098465551095638	272.611416222729
Winsorized Mean ( 21 / 40 )	26.8393333333333	0.0966661885432009	277.649649146336
Winsorized Mean ( 22 / 40 )	26.843	0.0958399108691476	280.081646117653
Winsorized Mean ( 23 / 40 )	26.8410833333333	0.0955667742733042	280.862083474457
Winsorized Mean ( 24 / 40 )	26.7890833333333	0.087890146278134	304.801897229270
Winsorized Mean ( 25 / 40 )	26.7765833333333	0.0842568847674714	317.796977745263
Winsorized Mean ( 26 / 40 )	26.7440833333333	0.0795851019792617	336.043840721625
Winsorized Mean ( 27 / 40 )	26.7463333333333	0.077794973422597	343.805417710501
Winsorized Mean ( 28 / 40 )	26.7416666666667	0.0772151250525531	346.32679346781
Winsorized Mean ( 29 / 40 )	26.7199166666667	0.074555592387219	358.389167212187
Winsorized Mean ( 30 / 40 )	26.6974166666667	0.069092607832166	386.400477624434
Winsorized Mean ( 31 / 40 )	26.69225	0.0679264166155532	392.958311801895
Winsorized Mean ( 32 / 40 )	26.6975833333333	0.0667819726753892	399.772307761913
Winsorized Mean ( 33 / 40 )	26.6755833333333	0.0642898935901577	414.926543562006
Winsorized Mean ( 34 / 40 )	26.6614166666667	0.0621114584837344	429.251177118127
Winsorized Mean ( 35 / 40 )	26.6643333333333	0.0611779483409828	435.848766694764
Winsorized Mean ( 36 / 40 )	26.6583333333333	0.0586072400826273	454.864165173947
Winsorized Mean ( 37 / 40 )	26.6706666666667	0.0560315454034492	475.993772340694
Winsorized Mean ( 38 / 40 )	26.658	0.0540135111222507	493.543179217955
Winsorized Mean ( 39 / 40 )	26.6385	0.0506254508573485	526.187906455618
Winsorized Mean ( 40 / 40 )	26.6318333333333	0.0485756482623578	548.254820800216
Trimmed Mean ( 1 / 40 )	26.8330508474576	0.122081191441198	219.796764191822
Trimmed Mean ( 2 / 40 )	26.8344827586207	0.120328096249547	223.010947526079
Trimmed Mean ( 3 / 40 )	26.8356140350877	0.118547137992523	226.370830114687
Trimmed Mean ( 4 / 40 )	26.8346428571429	0.116996816042779	229.362163559485
Trimmed Mean ( 5 / 40 )	26.8331818181818	0.115382811507156	232.557878142168
Trimmed Mean ( 6 / 40 )	26.8314814814815	0.113648378226744	236.092075400752
Trimmed Mean ( 7 / 40 )	26.8296226415094	0.111761918409708	240.060505611176
Trimmed Mean ( 8 / 40 )	26.8275961538462	0.109818022396928	244.291379213513
Trimmed Mean ( 9 / 40 )	26.8237254901961	0.108037138646394	248.282450148835
Trimmed Mean ( 10 / 40 )	26.8198	0.106365956807979	252.146464948532
Trimmed Mean ( 11 / 40 )	26.8134693877551	0.104930632616428	255.535192337697
Trimmed Mean ( 12 / 40 )	26.8054166666667	0.103521007769958	258.936975635256
Trimmed Mean ( 13 / 40 )	26.7963829787234	0.102083852993284	262.493843962632
Trimmed Mean ( 14 / 40 )	26.7870652173913	0.100462087897463	266.638547714951
Trimmed Mean ( 15 / 40 )	26.7772222222222	0.0986610773517813	271.406140506115
Trimmed Mean ( 16 / 40 )	26.7670454545455	0.096986215489936	275.988142431673
Trimmed Mean ( 17 / 40 )	26.7569767441860	0.0952008561054636	281.058152613088
Trimmed Mean ( 18 / 40 )	26.7471428571429	0.0934198493720701	286.311132344209
Trimmed Mean ( 19 / 40 )	26.7370731707317	0.091466273166211	292.316197492222
Trimmed Mean ( 20 / 40 )	26.72675	0.0894216252198652	298.884637069452
Trimmed Mean ( 21 / 40 )	26.7178205128205	0.0875664720512504	305.114730409411
Trimmed Mean ( 22 / 40 )	26.7086842105263	0.08563638800803	311.884758708201
Trimmed Mean ( 23 / 40 )	26.6987837837838	0.0834664018234104	319.874622608871
Trimmed Mean ( 24 / 40 )	26.6884722222222	0.0809353718588314	329.750412079068
Trimmed Mean ( 25 / 40 )	26.6812857142857	0.0791141224154848	337.250605829427
Trimmed Mean ( 26 / 40 )	26.6745588235294	0.077463473457396	344.350151535615
Trimmed Mean ( 27 / 40 )	26.6696969696970	0.0761662914193456	350.150919425271
Trimmed Mean ( 28 / 40 )	26.664375	0.0748354262487052	356.306850065698
Trimmed Mean ( 29 / 40 )	26.6590322580645	0.0732976046761755	363.709460572996
Trimmed Mean ( 30 / 40 )	26.6548333333333	0.0718325468254293	371.069028056475
Trimmed Mean ( 31 / 40 )	26.6518965517241	0.0708493356807075	376.177084734212
Trimmed Mean ( 32 / 40 )	26.6491071428571	0.0697817919845776	381.891986218222
Trimmed Mean ( 33 / 40 )	26.6457407407407	0.068596594608504	388.441159401774
Trimmed Mean ( 34 / 40 )	26.6436538461538	0.067500085942716	394.720295152883
Trimmed Mean ( 35 / 40 )	26.6424	0.0664465782046152	400.959699052636
Trimmed Mean ( 36 / 40 )	26.6408333333333	0.0652238598309925	408.452265817522
Trimmed Mean ( 37 / 40 )	26.6395652173913	0.0640817386558257	415.712272734496
Trimmed Mean ( 38 / 40 )	26.6372727272727	0.0630240093486005	422.65277951353
Trimmed Mean ( 39 / 40 )	26.6357142857143	0.0619796741410989	429.74918237029
Trimmed Mean ( 40 / 40 )	26.6355	0.0612172989628561	435.097602332328
Median	26.57
Midrange	26.66
Midmean - Weighted Average at Xnp	26.6131746031746
Midmean - Weighted Average at X(n+1)p	26.6548333333333
Midmean - Empirical Distribution Function	26.6131746031746
Midmean - Empirical Distribution Function - Averaging	26.6548333333333
Midmean - Empirical Distribution Function - Interpolation	26.6548333333333
Midmean - Closest Observation	26.6131746031746
Midmean - True Basic - Statistics Graphics Toolkit	26.6548333333333
Midmean - MS Excel (old versions)	26.6315625
Number of observations	120

Charts produced by software:

http://www.freestatistics.org/blog/date/2009/Nov/01/t1257075494vd24ppuempwto3q/1n71b1257075355.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Nov/01/t1257075494vd24ppuempwto3q/1n71b1257075355.ps (open in new window)

http://www.freestatistics.org/blog/date/2009/Nov/01/t1257075494vd24ppuempwto3q/25hfj1257075355.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Nov/01/t1257075494vd24ppuempwto3q/25hfj1257075355.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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