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CentTend_ATD

*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: Tue, 29 Dec 2009 04:30:52 -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/29/t1262086364pa7o533a9er9wz4.htm/, Retrieved Tue, 29 Dec 2009 12:32:46 +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/29/t1262086364pa7o533a9er9wz4.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:

Dataseries X:

» Textbox « » Textfile « » CSV «

4413 4230 4981 4573 4884 5340 5738 6011 4947 4811 4427 4664 4787 4292 5296 4822 5081 5302 5786 6082 5176 4982 4605 4726 4839 4382 5210 5035 5352 5599 6042 6187 4930 5127 4724 4869 4962 4408 5577 5192 5409 5819 6437 6546 5463 5451 5068 4839 4952 4812 5787 5688 5892 6400 7014 6881 5859 5635 5327 5470 5543 4980 6101 5900 5911 6502 6957 6941 4109 3789 4031 4675 4786 4441 5602 5100 5351 5848 6321 6418 5082 5100 4866 5360 5206 4530 5305 4560 4819 5635 6466 6567 5105 5202 5131 5650 5565 5222 6114 5944 6050 6684 7483 7295 5670 5896 5663 6338 6457 5783 7260 6659 6862 7414 8178 7730 6219 6160 5941 6704 6711

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	5562.2479338843	77.4248078147461	71.8406424358592
Geometric Mean	5499.59396735608
Harmonic Mean	5438.79215282252
Quadratic Mean	5626.54016086424
Winsorized Mean ( 1 / 40 )	5560.54545454545	76.1046093889715	73.0645029150001
Winsorized Mean ( 2 / 40 )	5557.7520661157	74.97068231481	74.1323393960601
Winsorized Mean ( 3 / 40 )	5559.04132231405	74.1435566775012	74.9767285442476
Winsorized Mean ( 4 / 40 )	5557.15702479339	73.0423016123521	76.0813515199201
Winsorized Mean ( 5 / 40 )	5559.42975206612	72.23598058236	76.9620583433145
Winsorized Mean ( 6 / 40 )	5548.52066115702	69.7946645004017	79.4977768125111
Winsorized Mean ( 7 / 40 )	5545.51239669421	69.186407401346	80.1532064604113
Winsorized Mean ( 8 / 40 )	5545.38016528926	68.8814261012017	80.5061753097547
Winsorized Mean ( 9 / 40 )	5541.95867768595	67.9977195338462	81.5021255959534
Winsorized Mean ( 10 / 40 )	5547.74380165289	66.7765305442897	83.0792459032195
Winsorized Mean ( 11 / 40 )	5536.74380165289	64.2581125736856	86.1641212275545
Winsorized Mean ( 12 / 40 )	5537.33884297521	63.989904887486	86.534569049783
Winsorized Mean ( 13 / 40 )	5538.62809917355	63.2371004411823	87.5851052709968
Winsorized Mean ( 14 / 40 )	5542.56198347107	61.9783874315664	89.4273344815708
Winsorized Mean ( 15 / 40 )	5532.52066115702	60.1428820984146	91.9896165285845
Winsorized Mean ( 16 / 40 )	5536.22314049587	58.9890176167937	93.8517602795228
Winsorized Mean ( 17 / 40 )	5530.32231404959	58.0847998102015	95.2111797255138
Winsorized Mean ( 18 / 40 )	5533.89256198347	56.3331843466165	98.2350390124156
Winsorized Mean ( 19 / 40 )	5532.63636363636	56.1213855616143	98.5833886364444
Winsorized Mean ( 20 / 40 )	5533.29752066116	55.2333525081324	100.180366923164
Winsorized Mean ( 21 / 40 )	5530.17355371901	54.7668683873699	100.976625404317
Winsorized Mean ( 22 / 40 )	5528.17355371901	54.1874598924753	102.019425983219
Winsorized Mean ( 23 / 40 )	5516.95867768595	52.5676022799406	104.949787291158
Winsorized Mean ( 24 / 40 )	5516.95867768595	51.7601341492462	106.587024326062
Winsorized Mean ( 25 / 40 )	5495.88429752066	49.1010429917369	111.930092777165
Winsorized Mean ( 26 / 40 )	5494.80991735537	47.619905660956	115.388929085188
Winsorized Mean ( 27 / 40 )	5489.45454545455	46.8216621242469	117.241770078295
Winsorized Mean ( 28 / 40 )	5482.28099173554	45.1829358180476	121.335209686523
Winsorized Mean ( 29 / 40 )	5490.19008264463	43.6211405170341	125.860764243445
Winsorized Mean ( 30 / 40 )	5489.69421487603	42.6243648603548	128.792399203162
Winsorized Mean ( 31 / 40 )	5482.77685950413	41.5470666214709	131.965438365526
Winsorized Mean ( 32 / 40 )	5483.30578512397	41.0258633787827	133.654854122089
Winsorized Mean ( 33 / 40 )	5479.76033057851	39.5545165945609	138.536905576341
Winsorized Mean ( 34 / 40 )	5461.21487603306	37.4590137938695	145.791742037983
Winsorized Mean ( 35 / 40 )	5460.63636363636	37.3349904935238	146.260553209022
Winsorized Mean ( 36 / 40 )	5467.47933884298	34.7197022907584	157.474833541367
Winsorized Mean ( 37 / 40 )	5474.20661157025	33.3251365624877	164.266592015478
Winsorized Mean ( 38 / 40 )	5477.03305785124	32.7784636132258	167.092427591430
Winsorized Mean ( 39 / 40 )	5476.06611570248	32.6088255041898	167.932025487974
Winsorized Mean ( 40 / 40 )	5471.10743801653	30.859648070183	177.290013987644
Trimmed Mean ( 1 / 40 )	5555.16806722689	74.0745844153477	74.9942522266234
Trimmed Mean ( 2 / 40 )	5549.60683760684	71.8131108767117	77.2784630808484
Trimmed Mean ( 3 / 40 )	5545.32173913044	69.9662134304042	79.2571366556287
Trimmed Mean ( 4 / 40 )	5540.42477876106	68.249898474649	81.178505793954
Trimmed Mean ( 5 / 40 )	5535.86486486487	66.6950330557975	83.0026556885207
Trimmed Mean ( 6 / 40 )	5530.63302752294	65.1756215779472	84.8573882936972
Trimmed Mean ( 7 / 40 )	5527.26168224299	64.0599650973616	86.282620882518
Trimmed Mean ( 8 / 40 )	5524.25714285714	62.9387530482571	87.771950909506
Trimmed Mean ( 9 / 40 )	5521.15533980582	61.7385082070913	89.4280652406769
Trimmed Mean ( 10 / 40 )	5518.38613861386	60.5490047343162	91.139171697835
Trimmed Mean ( 11 / 40 )	5514.79797979798	59.4111123271088	92.8243516033553
Trimmed Mean ( 12 / 40 )	5512.30927835052	58.5310395831037	94.1775392614377
Trimmed Mean ( 13 / 40 )	5509.65263157895	57.5719225310749	95.7003412315277
Trimmed Mean ( 14 / 40 )	5506.75268817204	56.5904899853512	97.308800287778
Trimmed Mean ( 15 / 40 )	5503.35164835165	55.6474717923526	98.8967058357528
Trimmed Mean ( 16 / 40 )	5500.70786516854	54.827422630283	100.327675482055
Trimmed Mean ( 17 / 40 )	5497.62068965517	54.0360034258035	101.739957456401
Trimmed Mean ( 18 / 40 )	5494.88235294118	53.2445876098032	103.200768371234
Trimmed Mean ( 19 / 40 )	5491.72289156627	52.5508424405786	104.503041940307
Trimmed Mean ( 20 / 40 )	5488.50617283951	51.7683531105922	106.020490184698
Trimmed Mean ( 21 / 40 )	5485.07594936709	50.9669110450194	107.620333210347
Trimmed Mean ( 22 / 40 )	5481.7012987013	50.0893189394355	109.438527310171
Trimmed Mean ( 23 / 40 )	5478.29333333333	49.1348567979245	111.495050364423
Trimmed Mean ( 24 / 40 )	5475.50684931507	48.2348552871171	113.517638162740
Trimmed Mean ( 25 / 40 )	5472.56338028169	47.2758961320489	115.758004142237
Trimmed Mean ( 26 / 40 )	5470.92753623188	46.5090963558374	117.631344508916
Trimmed Mean ( 27 / 40 )	5469.26865671642	45.7866692202615	119.451114262231
Trimmed Mean ( 28 / 40 )	5467.87692307692	45.0235168662547	121.444909319714
Trimmed Mean ( 29 / 40 )	5466.88888888889	44.3256297148914	123.334714567005
Trimmed Mean ( 30 / 40 )	5465.29508196721	43.6824629018403	125.114169827108
Trimmed Mean ( 31 / 40 )	5465.29508196721	43.0253408150722	127.025027075501
Trimmed Mean ( 32 / 40 )	5462.31578947368	42.365237897828	128.933910453828
Trimmed Mean ( 33 / 40 )	5460.87272727273	41.6113981288704	131.235021480423
Trimmed Mean ( 34 / 40 )	5459.56603773585	40.892665527315	133.509664076289
Trimmed Mean ( 35 / 40 )	5459.45098039216	40.3169240357727	135.413380632611
Trimmed Mean ( 36 / 40 )	5459.36734693878	39.5825334027036	137.923646558860
Trimmed Mean ( 37 / 40 )	5458.78723404255	39.0745384160054	139.701899378204
Trimmed Mean ( 38 / 40 )	5457.66666666667	38.6223884410181	141.308367684233
Trimmed Mean ( 39 / 40 )	5456.23255813954	38.0842575408206	143.267399982559
Trimmed Mean ( 40 / 40 )	5454.73170731707	37.3628063458419	145.993629515577
Median	5451
Midrange	5983.5
Midmean - Weighted Average at Xnp	5455.01666666667
Midmean - Weighted Average at X(n+1)p	5465.29508196721
Midmean - Empirical Distribution Function	5465.29508196721
Midmean - Empirical Distribution Function - Averaging	5465.29508196721
Midmean - Empirical Distribution Function - Interpolation	5465.29508196721
Midmean - Closest Observation	5456.66129032258
Midmean - True Basic - Statistics Graphics Toolkit	5465.29508196721
Midmean - MS Excel (old versions)	5465.29508196721
Number of observations	121

Charts produced by software:

http://www.freestatistics.org/blog/date/2009/Dec/29/t1262086364pa7o533a9er9wz4/1ghj71262086249.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/29/t1262086364pa7o533a9er9wz4/1ghj71262086249.ps (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/29/t1262086364pa7o533a9er9wz4/22i0x1262086249.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/29/t1262086364pa7o533a9er9wz4/22i0x1262086249.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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