Free Statistics

of Irreproducible Research!

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_centraltendency.wasp
Title produced by softwareCentral Tendency
Date of computationTue, 15 Dec 2015 19:20:32 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2015/Dec/15/t1450207325nb7879d7oeir03c.htm/, Retrieved Fri, 20 Sep 2024 23:57:34 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=286571, Retrieved Fri, 20 Sep 2024 23:57:34 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact93
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [Robustness of Cen...] [2015-12-15 19:20:32] [fdf479481d8c420708600f3e04be0f3b] [Current]
Feedback Forum

Post a new message
Dataseries X:
-2.581
0.4767
-0.4967
3.395
-4.654
-2.203
3.327
4.687
3.339
8.529
0.1633
1.545
-2.987
-8.562
3.873
3.268
-11.85
8.02
-4.042
-4.526
5.193
2.375
3.474
-9.199
-0.5591




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Sir Maurice George Kendall' @ kendall.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 1 seconds \tabularnewline
R Server & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=286571&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=286571&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=286571&T=0

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Sir Maurice George Kendall' @ kendall.wessa.net







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean0.0002080000000000461.035699333299650.000200830485559333
Geometric MeanNaN
Harmonic Mean4.37588228693496
Quadratic Mean5.07386979131314
Winsorized Mean ( 1 / 8 )0.0858880.9825096333424250.0874169545878297
Winsorized Mean ( 2 / 8 )-0.08931199999999990.896145723498137-0.0996623625579189
Winsorized Mean ( 3 / 8 )0.3189280.71828570192090.444012736362559
Winsorized Mean ( 4 / 8 )0.2091680.6812221678405170.307048140642671
Winsorized Mean ( 5 / 8 )0.2261680.6362145109609910.355490162678586
Winsorized Mean ( 6 / 8 )0.4604080.5643451622875250.815826963296319
Winsorized Mean ( 7 / 8 )0.5584080.5324960001702671.04866139806017
Winsorized Mean ( 8 / 8 )0.6755280.502346954322741.34474389500528
Trimmed Mean ( 1 / 8 )0.1446173913043480.9218006299678780.156885758810327
Trimmed Mean ( 2 / 8 )0.2145333333333330.8172675276080290.262500743130255
Trimmed Mean ( 3 / 8 )0.4144315789473680.72134765515230.574524053675434
Trimmed Mean ( 4 / 8 )0.4612470588235290.7018253931774270.657210558790543
Trimmed Mean ( 5 / 8 )0.566280.6806783937612040.831934736272329
Trimmed Mean ( 6 / 8 )0.6970923076923080.6572295757095671.06065267519299
Trimmed Mean ( 7 / 8 )0.7867454545454550.6497877623240651.21077296336197
Trimmed Mean ( 8 / 8 )0.8773555555555560.6293189720975961.39413492116919
Median0.4767
Midrange-1.6605
Midmean - Weighted Average at Xnp0.472266666666666
Midmean - Weighted Average at X(n+1)p0.697092307692307
Midmean - Empirical Distribution Function0.697092307692307
Midmean - Empirical Distribution Function - Averaging0.697092307692307
Midmean - Empirical Distribution Function - Interpolation0.697092307692307
Midmean - Closest Observation0.358585714285714
Midmean - True Basic - Statistics Graphics Toolkit0.697092307692307
Midmean - MS Excel (old versions)0.697092307692307
Number of observations25

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 0.000208000000000046 & 1.03569933329965 & 0.000200830485559333 \tabularnewline
Geometric Mean & NaN &  &  \tabularnewline
Harmonic Mean & 4.37588228693496 &  &  \tabularnewline
Quadratic Mean & 5.07386979131314 &  &  \tabularnewline
Winsorized Mean ( 1 / 8 ) & 0.085888 & 0.982509633342425 & 0.0874169545878297 \tabularnewline
Winsorized Mean ( 2 / 8 ) & -0.0893119999999999 & 0.896145723498137 & -0.0996623625579189 \tabularnewline
Winsorized Mean ( 3 / 8 ) & 0.318928 & 0.7182857019209 & 0.444012736362559 \tabularnewline
Winsorized Mean ( 4 / 8 ) & 0.209168 & 0.681222167840517 & 0.307048140642671 \tabularnewline
Winsorized Mean ( 5 / 8 ) & 0.226168 & 0.636214510960991 & 0.355490162678586 \tabularnewline
Winsorized Mean ( 6 / 8 ) & 0.460408 & 0.564345162287525 & 0.815826963296319 \tabularnewline
Winsorized Mean ( 7 / 8 ) & 0.558408 & 0.532496000170267 & 1.04866139806017 \tabularnewline
Winsorized Mean ( 8 / 8 ) & 0.675528 & 0.50234695432274 & 1.34474389500528 \tabularnewline
Trimmed Mean ( 1 / 8 ) & 0.144617391304348 & 0.921800629967878 & 0.156885758810327 \tabularnewline
Trimmed Mean ( 2 / 8 ) & 0.214533333333333 & 0.817267527608029 & 0.262500743130255 \tabularnewline
Trimmed Mean ( 3 / 8 ) & 0.414431578947368 & 0.7213476551523 & 0.574524053675434 \tabularnewline
Trimmed Mean ( 4 / 8 ) & 0.461247058823529 & 0.701825393177427 & 0.657210558790543 \tabularnewline
Trimmed Mean ( 5 / 8 ) & 0.56628 & 0.680678393761204 & 0.831934736272329 \tabularnewline
Trimmed Mean ( 6 / 8 ) & 0.697092307692308 & 0.657229575709567 & 1.06065267519299 \tabularnewline
Trimmed Mean ( 7 / 8 ) & 0.786745454545455 & 0.649787762324065 & 1.21077296336197 \tabularnewline
Trimmed Mean ( 8 / 8 ) & 0.877355555555556 & 0.629318972097596 & 1.39413492116919 \tabularnewline
Median & 0.4767 &  &  \tabularnewline
Midrange & -1.6605 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 0.472266666666666 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 0.697092307692307 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 0.697092307692307 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 0.697092307692307 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 0.697092307692307 &  &  \tabularnewline
Midmean - Closest Observation & 0.358585714285714 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 0.697092307692307 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 0.697092307692307 &  &  \tabularnewline
Number of observations & 25 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=286571&T=1

[TABLE]
[ROW][C]Central Tendency - Ungrouped Data[/C][/ROW]
[ROW][C]Measure[/C][C]Value[/C][C]S.E.[/C][C]Value/S.E.[/C][/ROW]
[ROW][C]Arithmetic Mean[/C][C]0.000208000000000046[/C][C]1.03569933329965[/C][C]0.000200830485559333[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]NaN[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]4.37588228693496[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]5.07386979131314[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 8 )[/C][C]0.085888[/C][C]0.982509633342425[/C][C]0.0874169545878297[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 8 )[/C][C]-0.0893119999999999[/C][C]0.896145723498137[/C][C]-0.0996623625579189[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 8 )[/C][C]0.318928[/C][C]0.7182857019209[/C][C]0.444012736362559[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 8 )[/C][C]0.209168[/C][C]0.681222167840517[/C][C]0.307048140642671[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 8 )[/C][C]0.226168[/C][C]0.636214510960991[/C][C]0.355490162678586[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 8 )[/C][C]0.460408[/C][C]0.564345162287525[/C][C]0.815826963296319[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 8 )[/C][C]0.558408[/C][C]0.532496000170267[/C][C]1.04866139806017[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 8 )[/C][C]0.675528[/C][C]0.50234695432274[/C][C]1.34474389500528[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 8 )[/C][C]0.144617391304348[/C][C]0.921800629967878[/C][C]0.156885758810327[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 8 )[/C][C]0.214533333333333[/C][C]0.817267527608029[/C][C]0.262500743130255[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 8 )[/C][C]0.414431578947368[/C][C]0.7213476551523[/C][C]0.574524053675434[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 8 )[/C][C]0.461247058823529[/C][C]0.701825393177427[/C][C]0.657210558790543[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 8 )[/C][C]0.56628[/C][C]0.680678393761204[/C][C]0.831934736272329[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 8 )[/C][C]0.697092307692308[/C][C]0.657229575709567[/C][C]1.06065267519299[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 8 )[/C][C]0.786745454545455[/C][C]0.649787762324065[/C][C]1.21077296336197[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 8 )[/C][C]0.877355555555556[/C][C]0.629318972097596[/C][C]1.39413492116919[/C][/ROW]
[ROW][C]Median[/C][C]0.4767[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]-1.6605[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]0.472266666666666[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]0.697092307692307[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]0.697092307692307[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]0.697092307692307[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]0.697092307692307[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]0.358585714285714[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]0.697092307692307[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]0.697092307692307[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]25[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=286571&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=286571&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean0.0002080000000000461.035699333299650.000200830485559333
Geometric MeanNaN
Harmonic Mean4.37588228693496
Quadratic Mean5.07386979131314
Winsorized Mean ( 1 / 8 )0.0858880.9825096333424250.0874169545878297
Winsorized Mean ( 2 / 8 )-0.08931199999999990.896145723498137-0.0996623625579189
Winsorized Mean ( 3 / 8 )0.3189280.71828570192090.444012736362559
Winsorized Mean ( 4 / 8 )0.2091680.6812221678405170.307048140642671
Winsorized Mean ( 5 / 8 )0.2261680.6362145109609910.355490162678586
Winsorized Mean ( 6 / 8 )0.4604080.5643451622875250.815826963296319
Winsorized Mean ( 7 / 8 )0.5584080.5324960001702671.04866139806017
Winsorized Mean ( 8 / 8 )0.6755280.502346954322741.34474389500528
Trimmed Mean ( 1 / 8 )0.1446173913043480.9218006299678780.156885758810327
Trimmed Mean ( 2 / 8 )0.2145333333333330.8172675276080290.262500743130255
Trimmed Mean ( 3 / 8 )0.4144315789473680.72134765515230.574524053675434
Trimmed Mean ( 4 / 8 )0.4612470588235290.7018253931774270.657210558790543
Trimmed Mean ( 5 / 8 )0.566280.6806783937612040.831934736272329
Trimmed Mean ( 6 / 8 )0.6970923076923080.6572295757095671.06065267519299
Trimmed Mean ( 7 / 8 )0.7867454545454550.6497877623240651.21077296336197
Trimmed Mean ( 8 / 8 )0.8773555555555560.6293189720975961.39413492116919
Median0.4767
Midrange-1.6605
Midmean - Weighted Average at Xnp0.472266666666666
Midmean - Weighted Average at X(n+1)p0.697092307692307
Midmean - Empirical Distribution Function0.697092307692307
Midmean - Empirical Distribution Function - Averaging0.697092307692307
Midmean - Empirical Distribution Function - Interpolation0.697092307692307
Midmean - Closest Observation0.358585714285714
Midmean - True Basic - Statistics Graphics Toolkit0.697092307692307
Midmean - MS Excel (old versions)0.697092307692307
Number of observations25



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('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('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('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('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('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('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('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('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('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('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('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('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('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('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('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('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('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('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('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('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('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('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('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('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('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')