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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_centraltendency.wasp
Title produced by softwareCentral Tendency
Date of computationThu, 15 Dec 2016 12:57:36 +0100
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2016/Dec/15/t14818031509wd9o2kib3by0mp.htm/, Retrieved Fri, 03 May 2024 06:13:00 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=299897, Retrieved Fri, 03 May 2024 06:13:00 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact59

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [] [2016-12-15 11:57:36] [9412b5b3b31fe4708efb1e5c8c74b28f] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
588,55
930,75
3228,65
2268,55
2414,5
3305,25
4342,05
3198,75
3091,35
3993,05
5331,5
3814,65
3707,6
4513,6
5634,2
4344,4
4060
4530,35
5348,75
4504,9
4281,35
4423,45
5197,9
4883,9
4155,25
4415,75
5384,05
5153,8
4564,1
5545
7585,4
6252,2
5785,65
6664,95
8639,85
6841,35

Tables (Output of Computation)





Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R ServerBig Analytics Cloud Computing Center

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input view raw input (R code)  \tabularnewline
Raw Outputview raw output of R engine  \tabularnewline
Computing time1 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=299897&T=0

[TABLE]
[ROW]
Summary of computational transaction[/C][/ROW] [ROW]Raw Input[/C] view raw input (R code) [/C][/ROW] [ROW]Raw Output[/C]view raw output of R engine [/C][/ROW] [ROW]Computing time[/C]1 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=299897&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=299897&T=0

As an alternative you can also use a QR Code:  
QR Code


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

Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R ServerBig Analytics Cloud Computing Center






Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean4525.7271.72516.6555
Geometric Mean4119.04
Harmonic Mean3408.48
Quadratic Mean4802.73
Winsorized Mean ( 1 / 12 )4505.92256.46417.5694
Winsorized Mean ( 2 / 12 )4538.91216.80620.9354
Winsorized Mean ( 3 / 12 )4536.37208.84821.7209
Winsorized Mean ( 4 / 12 )4565.71175.75925.9772
Winsorized Mean ( 5 / 12 )4515.83155.65429.012
Winsorized Mean ( 6 / 12 )4495.57148.73930.2246
Winsorized Mean ( 7 / 12 )4493.12141.39731.7766
Winsorized Mean ( 8 / 12 )4546.77113.50940.0564
Winsorized Mean ( 9 / 12 )4564.7106.11543.0167
Winsorized Mean ( 10 / 12 )4609.4795.495448.269
Winsorized Mean ( 11 / 12 )4589.183.051955.2558
Winsorized Mean ( 12 / 12 )4606.1574.316361.9804
Trimmed Mean ( 1 / 12 )4520.5232.40719.4507
Trimmed Mean ( 2 / 12 )4536.9196.52823.0852
Trimmed Mean ( 3 / 12 )4535.7178.94425.347
Trimmed Mean ( 4 / 12 )4535.41157.80128.7414
Trimmed Mean ( 5 / 12 )4524.92145.65331.0664
Trimmed Mean ( 6 / 12 )4527.65137.53332.9204
Trimmed Mean ( 7 / 12 )4536.39127.64735.5385
Trimmed Mean ( 8 / 12 )4547.52114.61939.6751
Trimmed Mean ( 9 / 12 )4547.71108.26942.0036
Trimmed Mean ( 10 / 12 )4543.46100.1645.362
Trimmed Mean ( 11 / 12 )4526.4990.167550.2008
Trimmed Mean ( 12 / 12 )4509.4178.227957.6445
Median4464.17
Midrange4614.2
Midmean - Weighted Average at Xnp4503.49
Midmean - Weighted Average at X(n+1)p4547.71
Midmean - Empirical Distribution Function4503.49
Midmean - Empirical Distribution Function - Averaging4547.71
Midmean - Empirical Distribution Function - Interpolation4547.71
Midmean - Closest Observation4503.49
Midmean - True Basic - Statistics Graphics Toolkit4547.71
Midmean - MS Excel (old versions)4547.52
Number of observations36

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 4525.7 & 271.725 & 16.6555 \tabularnewline
Geometric Mean & 4119.04 &  &  \tabularnewline
Harmonic Mean & 3408.48 &  &  \tabularnewline
Quadratic Mean & 4802.73 &  &  \tabularnewline
Winsorized Mean ( 1 / 12 ) & 4505.92 & 256.464 & 17.5694 \tabularnewline
Winsorized Mean ( 2 / 12 ) & 4538.91 & 216.806 & 20.9354 \tabularnewline
Winsorized Mean ( 3 / 12 ) & 4536.37 & 208.848 & 21.7209 \tabularnewline
Winsorized Mean ( 4 / 12 ) & 4565.71 & 175.759 & 25.9772 \tabularnewline
Winsorized Mean ( 5 / 12 ) & 4515.83 & 155.654 & 29.012 \tabularnewline
Winsorized Mean ( 6 / 12 ) & 4495.57 & 148.739 & 30.2246 \tabularnewline
Winsorized Mean ( 7 / 12 ) & 4493.12 & 141.397 & 31.7766 \tabularnewline
Winsorized Mean ( 8 / 12 ) & 4546.77 & 113.509 & 40.0564 \tabularnewline
Winsorized Mean ( 9 / 12 ) & 4564.7 & 106.115 & 43.0167 \tabularnewline
Winsorized Mean ( 10 / 12 ) & 4609.47 & 95.4954 & 48.269 \tabularnewline
Winsorized Mean ( 11 / 12 ) & 4589.1 & 83.0519 & 55.2558 \tabularnewline
Winsorized Mean ( 12 / 12 ) & 4606.15 & 74.3163 & 61.9804 \tabularnewline
Trimmed Mean ( 1 / 12 ) & 4520.5 & 232.407 & 19.4507 \tabularnewline
Trimmed Mean ( 2 / 12 ) & 4536.9 & 196.528 & 23.0852 \tabularnewline
Trimmed Mean ( 3 / 12 ) & 4535.7 & 178.944 & 25.347 \tabularnewline
Trimmed Mean ( 4 / 12 ) & 4535.41 & 157.801 & 28.7414 \tabularnewline
Trimmed Mean ( 5 / 12 ) & 4524.92 & 145.653 & 31.0664 \tabularnewline
Trimmed Mean ( 6 / 12 ) & 4527.65 & 137.533 & 32.9204 \tabularnewline
Trimmed Mean ( 7 / 12 ) & 4536.39 & 127.647 & 35.5385 \tabularnewline
Trimmed Mean ( 8 / 12 ) & 4547.52 & 114.619 & 39.6751 \tabularnewline
Trimmed Mean ( 9 / 12 ) & 4547.71 & 108.269 & 42.0036 \tabularnewline
Trimmed Mean ( 10 / 12 ) & 4543.46 & 100.16 & 45.362 \tabularnewline
Trimmed Mean ( 11 / 12 ) & 4526.49 & 90.1675 & 50.2008 \tabularnewline
Trimmed Mean ( 12 / 12 ) & 4509.41 & 78.2279 & 57.6445 \tabularnewline
Median & 4464.17 &  &  \tabularnewline
Midrange & 4614.2 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 4503.49 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 4547.71 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 4503.49 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 4547.71 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 4547.71 &  &  \tabularnewline
Midmean - Closest Observation & 4503.49 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 4547.71 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 4547.52 &  &  \tabularnewline
Number of observations & 36 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=299897&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]4525.7[/C][C]271.725[/C][C]16.6555[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]4119.04[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]3408.48[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]4802.73[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 12 )[/C][C]4505.92[/C][C]256.464[/C][C]17.5694[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 12 )[/C][C]4538.91[/C][C]216.806[/C][C]20.9354[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 12 )[/C][C]4536.37[/C][C]208.848[/C][C]21.7209[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 12 )[/C][C]4565.71[/C][C]175.759[/C][C]25.9772[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 12 )[/C][C]4515.83[/C][C]155.654[/C][C]29.012[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 12 )[/C][C]4495.57[/C][C]148.739[/C][C]30.2246[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 12 )[/C][C]4493.12[/C][C]141.397[/C][C]31.7766[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 12 )[/C][C]4546.77[/C][C]113.509[/C][C]40.0564[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 12 )[/C][C]4564.7[/C][C]106.115[/C][C]43.0167[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 12 )[/C][C]4609.47[/C][C]95.4954[/C][C]48.269[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 12 )[/C][C]4589.1[/C][C]83.0519[/C][C]55.2558[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 12 )[/C][C]4606.15[/C][C]74.3163[/C][C]61.9804[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 12 )[/C][C]4520.5[/C][C]232.407[/C][C]19.4507[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 12 )[/C][C]4536.9[/C][C]196.528[/C][C]23.0852[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 12 )[/C][C]4535.7[/C][C]178.944[/C][C]25.347[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 12 )[/C][C]4535.41[/C][C]157.801[/C][C]28.7414[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 12 )[/C][C]4524.92[/C][C]145.653[/C][C]31.0664[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 12 )[/C][C]4527.65[/C][C]137.533[/C][C]32.9204[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 12 )[/C][C]4536.39[/C][C]127.647[/C][C]35.5385[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 12 )[/C][C]4547.52[/C][C]114.619[/C][C]39.6751[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 12 )[/C][C]4547.71[/C][C]108.269[/C][C]42.0036[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 12 )[/C][C]4543.46[/C][C]100.16[/C][C]45.362[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 12 )[/C][C]4526.49[/C][C]90.1675[/C][C]50.2008[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 12 )[/C][C]4509.41[/C][C]78.2279[/C][C]57.6445[/C][/ROW]
[ROW][C]Median[/C][C]4464.17[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]4614.2[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]4503.49[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]4547.71[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]4503.49[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]4547.71[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]4547.71[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]4503.49[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]4547.71[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]4547.52[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]36[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=299897&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=299897&T=1

As an alternative you can also use a QR Code:  
QR Code


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

Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean4525.7271.72516.6555
Geometric Mean4119.04
Harmonic Mean3408.48
Quadratic Mean4802.73
Winsorized Mean ( 1 / 12 )4505.92256.46417.5694
Winsorized Mean ( 2 / 12 )4538.91216.80620.9354
Winsorized Mean ( 3 / 12 )4536.37208.84821.7209
Winsorized Mean ( 4 / 12 )4565.71175.75925.9772
Winsorized Mean ( 5 / 12 )4515.83155.65429.012
Winsorized Mean ( 6 / 12 )4495.57148.73930.2246
Winsorized Mean ( 7 / 12 )4493.12141.39731.7766
Winsorized Mean ( 8 / 12 )4546.77113.50940.0564
Winsorized Mean ( 9 / 12 )4564.7106.11543.0167
Winsorized Mean ( 10 / 12 )4609.4795.495448.269
Winsorized Mean ( 11 / 12 )4589.183.051955.2558
Winsorized Mean ( 12 / 12 )4606.1574.316361.9804
Trimmed Mean ( 1 / 12 )4520.5232.40719.4507
Trimmed Mean ( 2 / 12 )4536.9196.52823.0852
Trimmed Mean ( 3 / 12 )4535.7178.94425.347
Trimmed Mean ( 4 / 12 )4535.41157.80128.7414
Trimmed Mean ( 5 / 12 )4524.92145.65331.0664
Trimmed Mean ( 6 / 12 )4527.65137.53332.9204
Trimmed Mean ( 7 / 12 )4536.39127.64735.5385
Trimmed Mean ( 8 / 12 )4547.52114.61939.6751
Trimmed Mean ( 9 / 12 )4547.71108.26942.0036
Trimmed Mean ( 10 / 12 )4543.46100.1645.362
Trimmed Mean ( 11 / 12 )4526.4990.167550.2008
Trimmed Mean ( 12 / 12 )4509.4178.227957.6445
Median4464.17
Midrange4614.2
Midmean - Weighted Average at Xnp4503.49
Midmean - Weighted Average at X(n+1)p4547.71
Midmean - Empirical Distribution Function4503.49
Midmean - Empirical Distribution Function - Averaging4547.71
Midmean - Empirical Distribution Function - Interpolation4547.71
Midmean - Closest Observation4503.49
Midmean - True Basic - Statistics Graphics Toolkit4547.71
Midmean - MS Excel (old versions)4547.52
Number of observations36


Figures (Output of Computation)

Input Parameters & R Code

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,'Arithmetic Mean',header=TRUE)
a<-table.element(a,signif(arm,6))
a<-table.element(a, signif(armse,6))
a<-table.element(a,signif(armose,6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Geometric Mean',header=TRUE)
a<-table.element(a,signif(geo,6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Harmonic Mean',header=TRUE)
a<-table.element(a,signif(har,6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Quadratic Mean',header=TRUE)
a<-table.element(a,signif(qua,6))
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, mylabel,header=TRUE)
a<-table.element(a,signif(win[j,1],6))
a<-table.element(a,signif(win[j,2],6))
a<-table.element(a,signif(win[j,1]/win[j,2],6))
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, mylabel,header=TRUE)
a<-table.element(a,signif(tri[j,1],6))
a<-table.element(a,signif(tri[j,2],6))
a<-table.element(a,signif(tri[j,1]/tri[j,2],6))
a<-table.row.end(a)
}
a<-table.row.start(a)
a<-table.element(a, 'Median',header=TRUE)
a<-table.element(a,signif(median(x),6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Midrange',header=TRUE)
a<-table.element(a,signif(midr,6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <-  'Midmean'
mylabel <- paste(mymid,'Weighted Average at Xnp',sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,signif(midm[1],6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <-  'Midmean'
mylabel <- paste(mymid,'Weighted Average at X(n+1)p',sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,signif(midm[2],6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <-  'Midmean'
mylabel <- paste(mymid,'Empirical Distribution Function',sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,signif(midm[3],6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <-  'Midmean'
mylabel <- paste(mymid,'Empirical Distribution Function - Averaging',sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,signif(midm[4],6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <-  'Midmean'
mylabel <- paste(mymid,'Empirical Distribution Function - Interpolation',sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,signif(midm[5],6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <-  'Midmean'
mylabel <- paste(mymid,'Closest Observation',sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,signif(midm[6],6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <-  'Midmean'
mylabel <- paste(mymid,'True Basic - Statistics Graphics Toolkit',sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,signif(midm[7],6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <-  'Midmean'
mylabel <- paste(mymid,'MS Excel (old versions)',sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,signif(midm[8],6))
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,signif(length(x),6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')