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of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_centraltendency.wasp
Title produced by softwareCentral Tendency
Date of computationTue, 23 Oct 2007 05:21:27 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2007/Oct/23/0gzqatvsi60xaz11193142019.htm/, Retrieved Sat, 04 May 2024 20:59:45 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=1660, Retrieved Sat, 04 May 2024 20:59:45 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsExtra voorbeeld bij deel 1, vraag 1
Estimated Impact251
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [Extra voorbeeld b...] [2007-10-23 12:21:27] [443d2fe869025e720a9fee03b1da487c] [Current]
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Dataseries X:
1

3

5

7

12

16

19

21

22

23

24

25

26

27

29

31

33

35

37

39

41

43

45

47

49

51

53




Summary of compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\begin{tabular}{lllllllll}
\hline
Summary of compuational 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 & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=1660&T=0

[TABLE]
[ROW][C]Summary of compuational 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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=1660&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=1660&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 compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean28.29629629629632.891097847851959.78738797004747
Geometric Mean21.7350087440493
Harmonic Mean10.8143414345131
Quadratic Mean31.9061122670876
Winsorized Mean ( 1 / 9 )28.29629629629632.8413986839159.95858006709163
Winsorized Mean ( 2 / 9 )28.29629629629632.747604403246110.2985336109035
Winsorized Mean ( 3 / 9 )28.29629629629632.6136911138825610.826182231711
Winsorized Mean ( 4 / 9 )28.74074074074072.3128481674253812.4265574997664
Winsorized Mean ( 5 / 9 )29.11111111111112.017256983131414.4310374704574
Winsorized Mean ( 6 / 9 )29.33333333333331.7410741027707716.8478373704209
Winsorized Mean ( 7 / 9 )29.33333333333331.4945294355141519.6271365663950
Winsorized Mean ( 8 / 9 )29.03703703703701.2871062106070122.5599385643108
Winsorized Mean ( 9 / 9 )28.70370370370371.0619216237957227.0299644159288
Trimmed Mean ( 1 / 9 )28.42.7422618401604210.3564143963505
Trimmed Mean ( 2 / 9 )28.52173913043482.5752466900654911.0753425062006
Trimmed Mean ( 3 / 9 )28.66666666666672.3818093695793312.0356679391725
Trimmed Mean ( 4 / 9 )28.84210526315792.1470272633480613.4335067632917
Trimmed Mean ( 5 / 9 )28.88235294117651.9476274271933314.8295061662784
Trimmed Mean ( 6 / 9 )28.81.7813852287849816.1671936730066
Trimmed Mean ( 7 / 9 )28.61538461538461.6429275837251317.4173133976501
Trimmed Mean ( 8 / 9 )28.36363636363641.5212000482437718.6455663056165
Trimmed Mean ( 9 / 9 )28.11111111111111.3888888888888920.24
Median27
Midrange27
Midmean - Weighted Average at Xnp27.9285714285714
Midmean - Weighted Average at X(n+1)p28.8
Midmean - Empirical Distribution Function28.8
Midmean - Empirical Distribution Function - Averaging28.8
Midmean - Empirical Distribution Function - Interpolation28.6153846153846
Midmean - Closest Observation27.9285714285714
Midmean - True Basic - Statistics Graphics Toolkit28.8
Midmean - MS Excel (old versions)28.8
Number of observations27

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 28.2962962962963 & 2.89109784785195 & 9.78738797004747 \tabularnewline
Geometric Mean & 21.7350087440493 &  &  \tabularnewline
Harmonic Mean & 10.8143414345131 &  &  \tabularnewline
Quadratic Mean & 31.9061122670876 &  &  \tabularnewline
Winsorized Mean ( 1 / 9 ) & 28.2962962962963 & 2.841398683915 & 9.95858006709163 \tabularnewline
Winsorized Mean ( 2 / 9 ) & 28.2962962962963 & 2.7476044032461 & 10.2985336109035 \tabularnewline
Winsorized Mean ( 3 / 9 ) & 28.2962962962963 & 2.61369111388256 & 10.826182231711 \tabularnewline
Winsorized Mean ( 4 / 9 ) & 28.7407407407407 & 2.31284816742538 & 12.4265574997664 \tabularnewline
Winsorized Mean ( 5 / 9 ) & 29.1111111111111 & 2.0172569831314 & 14.4310374704574 \tabularnewline
Winsorized Mean ( 6 / 9 ) & 29.3333333333333 & 1.74107410277077 & 16.8478373704209 \tabularnewline
Winsorized Mean ( 7 / 9 ) & 29.3333333333333 & 1.49452943551415 & 19.6271365663950 \tabularnewline
Winsorized Mean ( 8 / 9 ) & 29.0370370370370 & 1.28710621060701 & 22.5599385643108 \tabularnewline
Winsorized Mean ( 9 / 9 ) & 28.7037037037037 & 1.06192162379572 & 27.0299644159288 \tabularnewline
Trimmed Mean ( 1 / 9 ) & 28.4 & 2.74226184016042 & 10.3564143963505 \tabularnewline
Trimmed Mean ( 2 / 9 ) & 28.5217391304348 & 2.57524669006549 & 11.0753425062006 \tabularnewline
Trimmed Mean ( 3 / 9 ) & 28.6666666666667 & 2.38180936957933 & 12.0356679391725 \tabularnewline
Trimmed Mean ( 4 / 9 ) & 28.8421052631579 & 2.14702726334806 & 13.4335067632917 \tabularnewline
Trimmed Mean ( 5 / 9 ) & 28.8823529411765 & 1.94762742719333 & 14.8295061662784 \tabularnewline
Trimmed Mean ( 6 / 9 ) & 28.8 & 1.78138522878498 & 16.1671936730066 \tabularnewline
Trimmed Mean ( 7 / 9 ) & 28.6153846153846 & 1.64292758372513 & 17.4173133976501 \tabularnewline
Trimmed Mean ( 8 / 9 ) & 28.3636363636364 & 1.52120004824377 & 18.6455663056165 \tabularnewline
Trimmed Mean ( 9 / 9 ) & 28.1111111111111 & 1.38888888888889 & 20.24 \tabularnewline
Median & 27 &  &  \tabularnewline
Midrange & 27 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 27.9285714285714 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 28.8 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 28.8 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 28.8 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 28.6153846153846 &  &  \tabularnewline
Midmean - Closest Observation & 27.9285714285714 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 28.8 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 28.8 &  &  \tabularnewline
Number of observations & 27 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=1660&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]28.2962962962963[/C][C]2.89109784785195[/C][C]9.78738797004747[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]21.7350087440493[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]10.8143414345131[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]31.9061122670876[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 9 )[/C][C]28.2962962962963[/C][C]2.841398683915[/C][C]9.95858006709163[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 9 )[/C][C]28.2962962962963[/C][C]2.7476044032461[/C][C]10.2985336109035[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 9 )[/C][C]28.2962962962963[/C][C]2.61369111388256[/C][C]10.826182231711[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 9 )[/C][C]28.7407407407407[/C][C]2.31284816742538[/C][C]12.4265574997664[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 9 )[/C][C]29.1111111111111[/C][C]2.0172569831314[/C][C]14.4310374704574[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 9 )[/C][C]29.3333333333333[/C][C]1.74107410277077[/C][C]16.8478373704209[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 9 )[/C][C]29.3333333333333[/C][C]1.49452943551415[/C][C]19.6271365663950[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 9 )[/C][C]29.0370370370370[/C][C]1.28710621060701[/C][C]22.5599385643108[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 9 )[/C][C]28.7037037037037[/C][C]1.06192162379572[/C][C]27.0299644159288[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 9 )[/C][C]28.4[/C][C]2.74226184016042[/C][C]10.3564143963505[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 9 )[/C][C]28.5217391304348[/C][C]2.57524669006549[/C][C]11.0753425062006[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 9 )[/C][C]28.6666666666667[/C][C]2.38180936957933[/C][C]12.0356679391725[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 9 )[/C][C]28.8421052631579[/C][C]2.14702726334806[/C][C]13.4335067632917[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 9 )[/C][C]28.8823529411765[/C][C]1.94762742719333[/C][C]14.8295061662784[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 9 )[/C][C]28.8[/C][C]1.78138522878498[/C][C]16.1671936730066[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 9 )[/C][C]28.6153846153846[/C][C]1.64292758372513[/C][C]17.4173133976501[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 9 )[/C][C]28.3636363636364[/C][C]1.52120004824377[/C][C]18.6455663056165[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 9 )[/C][C]28.1111111111111[/C][C]1.38888888888889[/C][C]20.24[/C][/ROW]
[ROW][C]Median[/C][C]27[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]27[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]27.9285714285714[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]28.8[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]28.8[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]28.8[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]28.6153846153846[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]27.9285714285714[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]28.8[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]28.8[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]27[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=1660&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=1660&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 Mean28.29629629629632.891097847851959.78738797004747
Geometric Mean21.7350087440493
Harmonic Mean10.8143414345131
Quadratic Mean31.9061122670876
Winsorized Mean ( 1 / 9 )28.29629629629632.8413986839159.95858006709163
Winsorized Mean ( 2 / 9 )28.29629629629632.747604403246110.2985336109035
Winsorized Mean ( 3 / 9 )28.29629629629632.6136911138825610.826182231711
Winsorized Mean ( 4 / 9 )28.74074074074072.3128481674253812.4265574997664
Winsorized Mean ( 5 / 9 )29.11111111111112.017256983131414.4310374704574
Winsorized Mean ( 6 / 9 )29.33333333333331.7410741027707716.8478373704209
Winsorized Mean ( 7 / 9 )29.33333333333331.4945294355141519.6271365663950
Winsorized Mean ( 8 / 9 )29.03703703703701.2871062106070122.5599385643108
Winsorized Mean ( 9 / 9 )28.70370370370371.0619216237957227.0299644159288
Trimmed Mean ( 1 / 9 )28.42.7422618401604210.3564143963505
Trimmed Mean ( 2 / 9 )28.52173913043482.5752466900654911.0753425062006
Trimmed Mean ( 3 / 9 )28.66666666666672.3818093695793312.0356679391725
Trimmed Mean ( 4 / 9 )28.84210526315792.1470272633480613.4335067632917
Trimmed Mean ( 5 / 9 )28.88235294117651.9476274271933314.8295061662784
Trimmed Mean ( 6 / 9 )28.81.7813852287849816.1671936730066
Trimmed Mean ( 7 / 9 )28.61538461538461.6429275837251317.4173133976501
Trimmed Mean ( 8 / 9 )28.36363636363641.5212000482437718.6455663056165
Trimmed Mean ( 9 / 9 )28.11111111111111.3888888888888920.24
Median27
Midrange27
Midmean - Weighted Average at Xnp27.9285714285714
Midmean - Weighted Average at X(n+1)p28.8
Midmean - Empirical Distribution Function28.8
Midmean - Empirical Distribution Function - Averaging28.8
Midmean - Empirical Distribution Function - Interpolation28.6153846153846
Midmean - Closest Observation27.9285714285714
Midmean - True Basic - Statistics Graphics Toolkit28.8
Midmean - MS Excel (old versions)28.8
Number of observations27



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')