Home » date » 2010 » Jul » 11 »

Centrumaten Omzet Product X

*Unverified author*

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

Title produced by software: Central Tendency

Date of computation: Sun, 11 Jul 2010 13:41:39 +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/11/t12788557808efj6paszf8insa.htm/, Retrieved Sun, 11 Jul 2010 15:43:03 +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/11/t12788557808efj6paszf8insa.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:

Febiri Lordina

Dataseries X:

» Textbox « » Textfile « » CSV «

213 212 211 209 229 228 213 203 204 204 205 207 205 208 201 201 220 218 203 185 179 182 182 185 183 192 177 172 188 182 162 150 141 135 139 148 142 156 143 134 146 142 117 106 104 99 105 106 96 104 96 85 91 98 73 70 62 60 70 82 72 73 68 53 61 73 46 50 52 45 58 73 58 49 44 35 46 61 29 33 37 31 44 57 42 34 27 22 30 47 12 13 18 11 26 41 21 24 30 34 48 64 35 44 55 53 73 94 73 78 87 87 91 104 73 84 103 111 131 155

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	3 seconds
R Server	'George Udny Yule' @ 72.249.76.132

Central Tendency - Ungrouped Data
Measure	Value	S.E.	Value/S.E.
Arithmetic Mean	105.716666666667	5.94382177336906	17.7859752020701
Geometric Mean	83.86383665002
Harmonic Mean	62.2515439217573
Quadratic Mean	124.016799937213
Winsorized Mean ( 1 / 40 )	105.716666666667	5.94126460584894	17.7936304271977
Winsorized Mean ( 2 / 40 )	105.6	5.91670000385132	17.8477867614147
Winsorized Mean ( 3 / 40 )	105.675	5.8925980547407	17.9335157460778
Winsorized Mean ( 4 / 40 )	105.608333333333	5.85407631488238	18.0401360783175
Winsorized Mean ( 5 / 40 )	105.65	5.84904227358696	18.0627861893037
Winsorized Mean ( 6 / 40 )	105.7	5.82945769611654	18.1320468403802
Winsorized Mean ( 7 / 40 )	105.758333333333	5.80694305566426	18.2123937361799
Winsorized Mean ( 8 / 40 )	105.691666666667	5.77911331234623	18.2885610567406
Winsorized Mean ( 9 / 40 )	105.766666666667	5.75088269114904	18.3913796102028
Winsorized Mean ( 10 / 40 )	105.766666666667	5.72916678125796	18.4610905398435
Winsorized Mean ( 11 / 40 )	105.583333333333	5.70212481077096	18.5164893504072
Winsorized Mean ( 12 / 40 )	105.683333333333	5.69104145546365	18.5701218591323
Winsorized Mean ( 13 / 40 )	105.791666666667	5.6515149531053	18.7191695579852
Winsorized Mean ( 14 / 40 )	105.908333333333	5.63895012569492	18.7815694362577
Winsorized Mean ( 15 / 40 )	105.783333333333	5.62072973089347	18.8202134594573
Winsorized Mean ( 16 / 40 )	105.916666666667	5.60648862948706	18.8918008518920
Winsorized Mean ( 17 / 40 )	105.633333333333	5.56547396605657	18.9801145378783
Winsorized Mean ( 18 / 40 )	105.933333333333	5.53377373293828	19.1430547119760
Winsorized Mean ( 19 / 40 )	105.141666666667	5.26648799248386	19.9642848928396
Winsorized Mean ( 20 / 40 )	104.641666666667	5.15797763760087	20.2873439977415
Winsorized Mean ( 21 / 40 )	104.466666666667	5.05169263772739	20.6795373666406
Winsorized Mean ( 22 / 40 )	104.466666666667	5.05169263772739	20.6795373666406
Winsorized Mean ( 23 / 40 )	104.083333333333	5.00059636966308	20.8141840770776
Winsorized Mean ( 24 / 40 )	104.083333333333	4.95399823436273	21.0099657709552
Winsorized Mean ( 25 / 40 )	104.291666666667	4.93321498220896	21.1407098702939
Winsorized Mean ( 26 / 40 )	104.291666666667	4.93321498220896	21.1407098702939
Winsorized Mean ( 27 / 40 )	103.841666666667	4.82201411701838	21.5349155242365
Winsorized Mean ( 28 / 40 )	103.608333333333	4.73801445006643	21.8674582834758
Winsorized Mean ( 29 / 40 )	102.641666666667	4.55822579361981	22.5178986987295
Winsorized Mean ( 30 / 40 )	100.391666666667	4.21988914575106	23.790119408172
Winsorized Mean ( 31 / 40 )	99.3583333333333	3.98030508228778	24.962491889246
Winsorized Mean ( 32 / 40 )	99.3583333333333	3.92188779776091	25.3343130800578
Winsorized Mean ( 33 / 40 )	97.9833333333333	3.75995379861159	26.0597173745898
Winsorized Mean ( 34 / 40 )	97.9833333333333	3.63764905714279	26.9358950778762
Winsorized Mean ( 35 / 40 )	97.9833333333333	3.51288112525698	27.8925844170618
Winsorized Mean ( 36 / 40 )	97.3833333333333	3.38076581526519	28.805110633105
Winsorized Mean ( 37 / 40 )	97.075	3.34589012705093	29.0132061465993
Winsorized Mean ( 38 / 40 )	97.7083333333333	3.28425485439942	29.7505332762007
Winsorized Mean ( 39 / 40 )	97.7083333333333	3.21619230983724	30.3801277785774
Winsorized Mean ( 40 / 40 )	97.0416666666667	3.14106700620054	30.8944910997136
Trimmed Mean ( 1 / 40 )	105.474576271186	5.8983704399429	17.8819857696505
Trimmed Mean ( 2 / 40 )	105.224137931034	5.85023079295758	17.9863225323865
Trimmed Mean ( 3 / 40 )	105.026315789474	5.81023275051619	18.0760944181011
Trimmed Mean ( 4 / 40 )	104.794642857143	5.7744658613076	18.1479370341992
Trimmed Mean ( 5 / 40 )	104.572727272727	5.7455274564899	18.2007183961164
Trimmed Mean ( 6 / 40 )	104.333333333333	5.71340144223669	18.2611592040500
Trimmed Mean ( 7 / 40 )	104.075471698113	5.68070294982674	18.3208790562244
Trimmed Mean ( 8 / 40 )	103.798076923077	5.6473469850957	18.3799715507153
Trimmed Mean ( 9 / 40 )	103.519607843137	5.61375246453671	18.4403584762764
Trimmed Mean ( 10 / 40 )	103.22	5.57937362980918	18.5002845926148
Trimmed Mean ( 11 / 40 )	102.908163265306	5.54271303000131	18.5663884650513
Trimmed Mean ( 12 / 40 )	102.604166666667	5.50411487153074	18.6413563418475
Trimmed Mean ( 13 / 40 )	102.276595744681	5.46060545262585	18.7299003072084
Trimmed Mean ( 14 / 40 )	101.923913043478	5.41529556993956	18.8214866071689
Trimmed Mean ( 15 / 40 )	101.544444444444	5.3639840484185	18.9307879232757
Trimmed Mean ( 16 / 40 )	101.159090909091	5.30665889441177	19.0626706788366
Trimmed Mean ( 17 / 40 )	100.744186046512	5.24155724102552	19.2202777560053
Trimmed Mean ( 18 / 40 )	100.333333333333	5.17128677631881	19.4020052789947
Trimmed Mean ( 19 / 40 )	99.8780487804878	5.09300404741746	19.6108323988341
Trimmed Mean ( 20 / 40 )	99.4625	5.03654190405141	19.7481728326319
Trimmed Mean ( 21 / 40 )	99.0641025641026	4.98356739400195	19.8781504757682
Trimmed Mean ( 22 / 40 )	98.6578947368421	4.93350708436009	19.9975175974919
Trimmed Mean ( 23 / 40 )	98.2297297297297	4.87304759401113	20.1577612027537
Trimmed Mean ( 24 / 40 )	97.8055555555556	4.8073056236025	20.3451919252560
Trimmed Mean ( 25 / 40 )	97.3571428571429	4.73409009118148	20.5651225435056
Trimmed Mean ( 26 / 40 )	96.8676470588235	4.64805719096349	20.8404593745423
Trimmed Mean ( 27 / 40 )	96.3484848484848	4.54393175735482	21.2037702134358
Trimmed Mean ( 28 / 40 )	95.828125	4.43463073386993	21.6090427254976
Trimmed Mean ( 29 / 40 )	95.2903225806452	4.31441369968906	22.0865056560322
Trimmed Mean ( 30 / 40 )	94.7833333333333	4.19699190547396	22.5836350100441
Trimmed Mean ( 31 / 40 )	94.396551724138	4.109212324241	22.9719333720663
Trimmed Mean ( 32 / 40 )	94.0535714285714	4.03816369181034	23.2911735646869
Trimmed Mean ( 33 / 40 )	93.6851851851852	3.95721563821324	23.674521115429
Trimmed Mean ( 34 / 40 )	93.3846153846154	3.88301342355090	24.0495216468291
Trimmed Mean ( 35 / 40 )	93.06	3.8078769059165	24.4388151978883
Trimmed Mean ( 36 / 40 )	92.7083333333333	3.73168795270442	24.8435385027695
Trimmed Mean ( 37 / 40 )	92.3695652173913	3.65655505565365	25.2613631714836
Trimmed Mean ( 38 / 40 )	92.0227272727273	3.56360043074174	25.8229644600120
Trimmed Mean ( 39 / 40 )	91.5952380952381	3.45000118228018	26.5493352772421
Trimmed Mean ( 40 / 40 )	91.125	3.31182564495236	27.5150354424262
Median	89
Midrange	120
Midmean - Weighted Average at Xnp	94.032786885246
Midmean - Weighted Average at X(n+1)p	94.7833333333333
Midmean - Empirical Distribution Function	94.032786885246
Midmean - Empirical Distribution Function - Averaging	94.7833333333333
Midmean - Empirical Distribution Function - Interpolation	94.7833333333333
Midmean - Closest Observation	94.032786885246
Midmean - True Basic - Statistics Graphics Toolkit	94.7833333333333
Midmean - MS Excel (old versions)	95.2903225806452
Number of observations	120

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Jul/11/t12788557808efj6paszf8insa/1exe31278855694.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Jul/11/t12788557808efj6paszf8insa/1exe31278855694.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Jul/11/t12788557808efj6paszf8insa/276vo1278855694.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Jul/11/t12788557808efj6paszf8insa/276vo1278855694.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

Disclaimer

Information provided on this web site is provided "AS IS" without warranty of any kind, either express or implied, including, without limitation, warranties of merchantability, fitness for a particular purpose, and noninfringement. We use reasonable efforts to include accurate and timely information and periodically update the information, and software without notice. However, we make no warranties or representations as to the accuracy or completeness of such information (or software), and we assume no liability or responsibility for errors or omissions in the content of this web site, or any software bugs in online applications. Your use of this web site is AT YOUR OWN RISK. Under no circumstances and under no legal theory shall we be liable to you or any other person for any direct, indirect, special, incidental, exemplary, or consequential damages arising from your access to, or use of, this web site.

We may request personal information to be submitted to our servers in order to be able to:

personalize online software applications according to your needs
enforce strict security rules with respect to the data that you upload (e.g. statistical data)
manage user sessions of online applications
alert you about important changes or upgrades in resources or applications

We NEVER allow other companies to directly offer registered users information about their products and services. Banner references and hyperlinks of third parties NEVER contain any personal data of the visitor.

We do NOT sell, nor transmit by any means, personal information, nor statistical data series uploaded by you to third parties.

We carefully protect your data from loss, misuse, alteration, and destruction. However, at any time, and under any circumstance you are solely responsible for managing your passwords, and keeping them secret.

We store a unique ANONYMOUS USER ID in the form of a small 'Cookie' on your computer. This allows us to track your progress when using this website which is necessary to create state-dependent features. The cookie is used for NO OTHER PURPOSE. At any time you may opt to disallow cookies from this website - this will not affect other features of this website.

We examine cookies that are used by third-parties (banner and online ads) very closely: abuse from third-parties automatically results in termination of the advertising contract without refund. We have very good reason to believe that the cookies that are produced by third parties (banner ads) do NOT cause any privacy or security risk.

FreeStatistics.org is safe. There is no need to download any software to use the applications and services contained in this website. Hence, your system's security is not compromised by their use, and your personal data - other than data you submit in the account application form, and the user-agent information that is transmitted by your browser - is never transmitted to our servers.

As a general rule, we do not log on-line behavior of individuals (other than normal logging of webserver 'hits'). However, in cases of abuse, hacking, unauthorized access, Denial of Service attacks, illegal copying, hotlinking, non-compliance with international webstandards (such as robots.txt), or any other harmful behavior, our system engineers are empowered to log, track, identify, publish, and ban misbehaving individuals - even if this leads to ban entire blocks of IP addresses, or disclosing user's identity.

FreeStatistics.org is powered by