Home » date » 2010 » Mar » 17 »

Melino Olivini - Opgave 5 - oefening 2.1

*Unverified author*

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

Title produced by software: Central Tendency

Date of computation: Tue, 16 Mar 2010 17:36:09 -0600

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2010/Mar/17/t1268782704zx5ssy0bopxuybv.htm/, Retrieved Wed, 17 Mar 2010 00:38:26 +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/2010/Mar/17/t1268782704zx5ssy0bopxuybv.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:

KDGP1W52

Dataseries X:

» Textbox « » Textfile « » CSV «

5221,3 5115,9 5107,4 5202,1 5307,5 5266,1 5329,8 5263,4 5177,1 5204,9 5185,2 5189,8 5253,8 5372,3 5478,4 5590,5 5699,8 5797,9 5854,3 5902,4 5956,9 6007,8 6101,7 6148,6 6207,4 6232 6291,7 6323,4 6365 6435 6493,4 6606,8 6639,1 6723,5 6759,4 6848,6 6918,1 6963,5 7013,1 7030,9 7112,1 7130,3 7130,8 7076,9 7040,8 7086,5 7120,7 7154,1 7228,2 7297,9 7369,5 7450,7 7459,7 7497,5 7536 7637,4 7715,1 7815,7 7859,5 7951,6 7973,7 7988 8053,1 8112 8169,2 8303,1 8372,7 8470,6 8536,1 8665,8 8773,7 8838,4 8936,2 8995,3 9098,9 9237,1 9315,5 9392,6 9502,2 9671,1 9695,6 9847,9 9836,6 9887,7 9875,6 9905,9 9871,1 9910 9977,3 10031,6 10090,7 10095,8 10126 10212,7 10398,7 10467 10543,6 10634,2 10728,7 10796,4 10875,8 10946,1 11050 11086,1 11217,3 11291,7 11314,1 11356,4 11357,8 11491,4 11625,7 11620,7 11646 11700,6

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	8080.48157894737	189.073627155921	42.7372220044403
Geometric Mean	7829.12982272115
Harmonic Mean	7582.03306404301
Quadratic Mean	8326.69208453237
Winsorized Mean ( 1 / 38 )	8080.07719298246	188.982700360663	42.7556447101354
Winsorized Mean ( 2 / 38 )	8080.7947368421	188.775781285145	42.8063106497549
Winsorized Mean ( 3 / 38 )	8080.87631578947	188.7249489882	42.818272619031
Winsorized Mean ( 4 / 38 )	8076.50087719298	187.961755775094	42.9688520618892
Winsorized Mean ( 5 / 38 )	8071.18070175439	186.961583423593	43.1702628634021
Winsorized Mean ( 6 / 38 )	8071.25438596491	186.930116800933	43.1779240504097
Winsorized Mean ( 7 / 38 )	8069.66403508772	186.391670533224	43.2941236698092
Winsorized Mean ( 8 / 38 )	8070.37280701754	185.842873970869	43.4257856358946
Winsorized Mean ( 9 / 38 )	8065.25701754386	184.847521422420	43.6319457003314
Winsorized Mean ( 10 / 38 )	8053.9850877193	183.103929789989	43.9858669169843
Winsorized Mean ( 11 / 38 )	8054.49649122807	182.059261704649	44.2410697253882
Winsorized Mean ( 12 / 38 )	8045.90701754386	180.170659781352	44.6571435510535
Winsorized Mean ( 13 / 38 )	8042.73684210526	178.391988838693	45.0846301701234
Winsorized Mean ( 14 / 38 )	8046.01578947368	175.322304302482	45.8927106935119
Winsorized Mean ( 15 / 38 )	8051.85789473684	172.202323662135	46.7581256948355
Winsorized Mean ( 16 / 38 )	8053.9350877193	168.472159896283	47.8057329631054
Winsorized Mean ( 17 / 38 )	8055.05350877193	164.863138480728	48.8590329105833
Winsorized Mean ( 18 / 38 )	8051.86403508772	162.184871288812	49.6462091137299
Winsorized Mean ( 19 / 38 )	8048.49736842105	159.736432426099	50.3861094565553
Winsorized Mean ( 20 / 38 )	8025.42719298246	154.430570714054	51.9678659210713
Winsorized Mean ( 21 / 38 )	8018.83245614035	151.33846962553	52.9860813049191
Winsorized Mean ( 22 / 38 )	8031.1254385965	148.513505433310	54.0767347398104
Winsorized Mean ( 23 / 38 )	8039.55877192983	147.305384459143	54.5774942406109
Winsorized Mean ( 24 / 38 )	8039.49561403509	144.380858162293	55.6825587294835
Winsorized Mean ( 25 / 38 )	8032.98245614035	142.329079016931	56.4395028171634
Winsorized Mean ( 26 / 38 )	8031.24912280702	138.966385494983	57.7927467437582
Winsorized Mean ( 27 / 38 )	8037.78596491228	138.021640522093	58.2356935804257
Winsorized Mean ( 28 / 38 )	8043.53333333333	136.368356234138	58.9838695387878
Winsorized Mean ( 29 / 38 )	8058.26228070175	134.075649953890	60.1023547786127
Winsorized Mean ( 30 / 38 )	8072.44649122807	132.298372402852	61.0169750739431
Winsorized Mean ( 31 / 38 )	8096.97456140351	128.324275924959	63.097761534524
Winsorized Mean ( 32 / 38 )	8102.86929824562	127.012961062224	63.795609758881
Winsorized Mean ( 33 / 38 )	8086.4850877193	119.639801277552	67.5902584371525
Winsorized Mean ( 34 / 38 )	8089.8850877193	117.695243292979	68.73587123297
Winsorized Mean ( 35 / 38 )	8065.41578947368	108.857128580336	74.0917558147924
Winsorized Mean ( 36 / 38 )	8052.75263157895	102.677715048285	78.4274623543389
Winsorized Mean ( 37 / 38 )	8042.46403508772	98.3638173979126	81.762422889236
Winsorized Mean ( 38 / 38 )	8032.86403508772	93.7840883583094	85.6527389208875
Trimmed Mean ( 1 / 38 )	8074.70446428571	187.82271716005	42.9910959993460
Trimmed Mean ( 2 / 38 )	8069.13636363636	186.503809787986	43.2652629070108
Trimmed Mean ( 3 / 38 )	8062.98333333333	185.125084706833	43.5542452072447
Trimmed Mean ( 4 / 38 )	8056.56886792453	183.579209896255	43.886063527986
Trimmed Mean ( 5 / 38 )	8051.10673076923	182.064602909742	44.2211533823549
Trimmed Mean ( 6 / 38 )	8046.61960784314	180.602519722589	44.5543042267794
Trimmed Mean ( 7 / 38 )	8041.939	178.939329907281	44.9422662092622
Trimmed Mean ( 8 / 38 )	8037.33163265306	177.152176577962	45.3696465259964
Trimmed Mean ( 9 / 38 )	8032.42708333333	175.214316176379	45.84344052827
Trimmed Mean ( 10 / 38 )	8028.00319148936	173.175936708302	46.3574982996151
Trimmed Mean ( 11 / 38 )	8024.78369565217	171.134438574234	46.8916938198339
Trimmed Mean ( 12 / 38 )	8021.36222222222	168.955856770410	47.4760826617705
Trimmed Mean ( 13 / 38 )	8018.7125	166.740408319310	48.0909971423606
Trimmed Mean ( 14 / 38 )	8016.26279069767	164.449058553779	48.746176239593
Trimmed Mean ( 15 / 38 )	8013.37857142857	162.240712234810	49.391909472333
Trimmed Mean ( 16 / 38 )	8009.81219512195	160.111829326771	50.0263611302247
Trimmed Mean ( 17 / 38 )	8005.8825	158.137981778362	50.6259306585854
Trimmed Mean ( 18 / 38 )	8001.65512820513	156.303652528333	51.1930143587316
Trimmed Mean ( 19 / 38 )	7997.47105263158	154.489076361868	51.7672267901885
Trimmed Mean ( 20 / 38 )	7993.33378378378	152.654347723374	52.3623067602934
Trimmed Mean ( 21 / 38 )	7990.79305555556	151.163706035555	52.8618493494467
Trimmed Mean ( 22 / 38 )	7988.61857142857	149.754720900059	53.3446860534027
Trimmed Mean ( 23 / 38 )	7985.3794117647	148.387951974893	53.8142032792248
Trimmed Mean ( 24 / 38 )	7981.3106060606	146.848213345747	54.3507505077298
Trimmed Mean ( 25 / 38 )	7976.9921875	145.330448794289	54.8886503391399
Trimmed Mean ( 26 / 38 )	7972.87419354839	143.714001289945	55.4773656149412
Trimmed Mean ( 27 / 38 )	7968.60833333333	142.151001977579	56.0573490336014
Trimmed Mean ( 28 / 38 )	7963.5724137931	140.295224648754	56.7629613461959
Trimmed Mean ( 29 / 38 )	7957.75892857143	138.183458840962	57.5883611201986
Trimmed Mean ( 30 / 38 )	7950.4425925926	135.840910094709	58.5276010522124
Trimmed Mean ( 31 / 38 )	7941.52692307692	133.119758116029	59.6570113668247
Trimmed Mean ( 32 / 38 )	7930.094	130.264185859478	60.8770088852707
Trimmed Mean ( 33 / 38 )	7917.27083333333	126.785359782999	62.4462544167896
Trimmed Mean ( 34 / 38 )	7904.56304347826	123.689579632829	63.9064589510522
Trimmed Mean ( 35 / 38 )	7890.44090909091	119.963735989771	65.7735510151476
Trimmed Mean ( 36 / 38 )	7876.87142857143	116.912969769888	67.3738033006512
Trimmed Mean ( 37 / 38 )	7862.9475	114.110190784458	68.906619522285
Trimmed Mean ( 38 / 38 )	7848.39210526316	111.200632333260	70.5786643527538
Median	7765.4
Midrange	8404
Midmean - Weighted Average at Xnp	7929.81578947368
Midmean - Weighted Average at X(n+1)p	7963.5724137931
Midmean - Empirical Distribution Function	7963.5724137931
Midmean - Empirical Distribution Function - Averaging	7963.5724137931
Midmean - Empirical Distribution Function - Interpolation	7957.75892857143
Midmean - Closest Observation	7963.5724137931
Midmean - True Basic - Statistics Graphics Toolkit	7963.5724137931
Midmean - MS Excel (old versions)	7963.5724137931
Number of observations	114

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Mar/17/t1268782704zx5ssy0bopxuybv/1ad7f1268782567.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Mar/17/t1268782704zx5ssy0bopxuybv/1ad7f1268782567.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Mar/17/t1268782704zx5ssy0bopxuybv/2yzej1268782567.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Mar/17/t1268782704zx5ssy0bopxuybv/2yzej1268782567.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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