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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_centraltendency.wasp
Title produced by softwareCentral Tendency
Date of computationWed, 30 Nov 2016 13:27:47 +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/Nov/30/t1480509194ys9rghj2dcab1bu.htm/, Retrieved Sun, 19 May 2024 01:30:03 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=297368, Retrieved Sun, 19 May 2024 01:30:03 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact57
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [] [2016-11-30 12:27:47] [f8e2c3c70b883e93ecb746821352be11] [Current]
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Dataseries X:
4930
5540
6590
6570
6130
5800
5800
4950
4080
4090
4350
3970
3230
3470
2980
3370
3170
3010
3000
3400
3200
3070
3240
3830
3140
2840
3060
4470
4310
3770
4620
5280
5470
5260
5200
5810
4400
4640
4250
3480
3080




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=297368&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=297368&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=297368&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 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 Mean4264.63172.43224.7322
Geometric Mean4131.18
Harmonic Mean4006.44
Quadratic Mean4401.87
Winsorized Mean ( 1 / 13 )4267.56171.59524.8699
Winsorized Mean ( 2 / 13 )4247.07164.73425.7814
Winsorized Mean ( 3 / 13 )4224.39158.3126.6843
Winsorized Mean ( 4 / 13 )4228.29157.14426.907
Winsorized Mean ( 5 / 13 )4229.51156.91826.9536
Winsorized Mean ( 6 / 13 )4192.93147.5328.4209
Winsorized Mean ( 7 / 13 )4191.22142.9229.3255
Winsorized Mean ( 8 / 13 )4160133.80731.0896
Winsorized Mean ( 9 / 13 )4162.2131.67931.6086
Winsorized Mean ( 10 / 13 )4154.88127.3232.6335
Winsorized Mean ( 11 / 13 )4090.49113.56736.0183
Winsorized Mean ( 12 / 13 )4122.68105.49239.0806
Winsorized Mean ( 13 / 13 )4040.2486.96446.4588
Trimmed Mean ( 1 / 13 )4241.54166.94525.4068
Trimmed Mean ( 2 / 13 )4212.7160.37826.2674
Trimmed Mean ( 3 / 13 )4192.57156.37626.8109
Trimmed Mean ( 4 / 13 )4179.39154.10827.1199
Trimmed Mean ( 5 / 13 )4163.23150.95327.5797
Trimmed Mean ( 6 / 13 )4144.48145.99528.3879
Trimmed Mean ( 7 / 13 )4132.22142.33829.031
Trimmed Mean ( 8 / 13 )4118.4138.10529.8209
Trimmed Mean ( 9 / 13 )4109.13134.78930.4858
Trimmed Mean ( 10 / 13 )4097.62129.4631.6516
Trimmed Mean ( 11 / 13 )4085.26121.73533.5585
Trimmed Mean ( 12 / 13 )4084.12115.14135.4706
Trimmed Mean ( 13 / 13 )4075.33106.44438.2861
Median4090
Midrange4715
Midmean - Weighted Average at Xnp4042.5
Midmean - Weighted Average at X(n+1)p4097.62
Midmean - Empirical Distribution Function4097.62
Midmean - Empirical Distribution Function - Averaging4097.62
Midmean - Empirical Distribution Function - Interpolation4097.62
Midmean - Closest Observation4056.82
Midmean - True Basic - Statistics Graphics Toolkit4097.62
Midmean - MS Excel (old versions)4097.62
Number of observations41

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 4264.63 & 172.432 & 24.7322 \tabularnewline
Geometric Mean & 4131.18 &  &  \tabularnewline
Harmonic Mean & 4006.44 &  &  \tabularnewline
Quadratic Mean & 4401.87 &  &  \tabularnewline
Winsorized Mean ( 1 / 13 ) & 4267.56 & 171.595 & 24.8699 \tabularnewline
Winsorized Mean ( 2 / 13 ) & 4247.07 & 164.734 & 25.7814 \tabularnewline
Winsorized Mean ( 3 / 13 ) & 4224.39 & 158.31 & 26.6843 \tabularnewline
Winsorized Mean ( 4 / 13 ) & 4228.29 & 157.144 & 26.907 \tabularnewline
Winsorized Mean ( 5 / 13 ) & 4229.51 & 156.918 & 26.9536 \tabularnewline
Winsorized Mean ( 6 / 13 ) & 4192.93 & 147.53 & 28.4209 \tabularnewline
Winsorized Mean ( 7 / 13 ) & 4191.22 & 142.92 & 29.3255 \tabularnewline
Winsorized Mean ( 8 / 13 ) & 4160 & 133.807 & 31.0896 \tabularnewline
Winsorized Mean ( 9 / 13 ) & 4162.2 & 131.679 & 31.6086 \tabularnewline
Winsorized Mean ( 10 / 13 ) & 4154.88 & 127.32 & 32.6335 \tabularnewline
Winsorized Mean ( 11 / 13 ) & 4090.49 & 113.567 & 36.0183 \tabularnewline
Winsorized Mean ( 12 / 13 ) & 4122.68 & 105.492 & 39.0806 \tabularnewline
Winsorized Mean ( 13 / 13 ) & 4040.24 & 86.964 & 46.4588 \tabularnewline
Trimmed Mean ( 1 / 13 ) & 4241.54 & 166.945 & 25.4068 \tabularnewline
Trimmed Mean ( 2 / 13 ) & 4212.7 & 160.378 & 26.2674 \tabularnewline
Trimmed Mean ( 3 / 13 ) & 4192.57 & 156.376 & 26.8109 \tabularnewline
Trimmed Mean ( 4 / 13 ) & 4179.39 & 154.108 & 27.1199 \tabularnewline
Trimmed Mean ( 5 / 13 ) & 4163.23 & 150.953 & 27.5797 \tabularnewline
Trimmed Mean ( 6 / 13 ) & 4144.48 & 145.995 & 28.3879 \tabularnewline
Trimmed Mean ( 7 / 13 ) & 4132.22 & 142.338 & 29.031 \tabularnewline
Trimmed Mean ( 8 / 13 ) & 4118.4 & 138.105 & 29.8209 \tabularnewline
Trimmed Mean ( 9 / 13 ) & 4109.13 & 134.789 & 30.4858 \tabularnewline
Trimmed Mean ( 10 / 13 ) & 4097.62 & 129.46 & 31.6516 \tabularnewline
Trimmed Mean ( 11 / 13 ) & 4085.26 & 121.735 & 33.5585 \tabularnewline
Trimmed Mean ( 12 / 13 ) & 4084.12 & 115.141 & 35.4706 \tabularnewline
Trimmed Mean ( 13 / 13 ) & 4075.33 & 106.444 & 38.2861 \tabularnewline
Median & 4090 &  &  \tabularnewline
Midrange & 4715 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 4042.5 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 4097.62 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 4097.62 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 4097.62 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 4097.62 &  &  \tabularnewline
Midmean - Closest Observation & 4056.82 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 4097.62 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 4097.62 &  &  \tabularnewline
Number of observations & 41 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=297368&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]4264.63[/C][C]172.432[/C][C]24.7322[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]4131.18[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]4006.44[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]4401.87[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 13 )[/C][C]4267.56[/C][C]171.595[/C][C]24.8699[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 13 )[/C][C]4247.07[/C][C]164.734[/C][C]25.7814[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 13 )[/C][C]4224.39[/C][C]158.31[/C][C]26.6843[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 13 )[/C][C]4228.29[/C][C]157.144[/C][C]26.907[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 13 )[/C][C]4229.51[/C][C]156.918[/C][C]26.9536[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 13 )[/C][C]4192.93[/C][C]147.53[/C][C]28.4209[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 13 )[/C][C]4191.22[/C][C]142.92[/C][C]29.3255[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 13 )[/C][C]4160[/C][C]133.807[/C][C]31.0896[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 13 )[/C][C]4162.2[/C][C]131.679[/C][C]31.6086[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 13 )[/C][C]4154.88[/C][C]127.32[/C][C]32.6335[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 13 )[/C][C]4090.49[/C][C]113.567[/C][C]36.0183[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 13 )[/C][C]4122.68[/C][C]105.492[/C][C]39.0806[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 13 )[/C][C]4040.24[/C][C]86.964[/C][C]46.4588[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 13 )[/C][C]4241.54[/C][C]166.945[/C][C]25.4068[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 13 )[/C][C]4212.7[/C][C]160.378[/C][C]26.2674[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 13 )[/C][C]4192.57[/C][C]156.376[/C][C]26.8109[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 13 )[/C][C]4179.39[/C][C]154.108[/C][C]27.1199[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 13 )[/C][C]4163.23[/C][C]150.953[/C][C]27.5797[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 13 )[/C][C]4144.48[/C][C]145.995[/C][C]28.3879[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 13 )[/C][C]4132.22[/C][C]142.338[/C][C]29.031[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 13 )[/C][C]4118.4[/C][C]138.105[/C][C]29.8209[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 13 )[/C][C]4109.13[/C][C]134.789[/C][C]30.4858[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 13 )[/C][C]4097.62[/C][C]129.46[/C][C]31.6516[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 13 )[/C][C]4085.26[/C][C]121.735[/C][C]33.5585[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 13 )[/C][C]4084.12[/C][C]115.141[/C][C]35.4706[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 13 )[/C][C]4075.33[/C][C]106.444[/C][C]38.2861[/C][/ROW]
[ROW][C]Median[/C][C]4090[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]4715[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]4042.5[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]4097.62[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]4097.62[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]4097.62[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]4097.62[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]4056.82[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]4097.62[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]4097.62[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]41[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=297368&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=297368&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 Mean4264.63172.43224.7322
Geometric Mean4131.18
Harmonic Mean4006.44
Quadratic Mean4401.87
Winsorized Mean ( 1 / 13 )4267.56171.59524.8699
Winsorized Mean ( 2 / 13 )4247.07164.73425.7814
Winsorized Mean ( 3 / 13 )4224.39158.3126.6843
Winsorized Mean ( 4 / 13 )4228.29157.14426.907
Winsorized Mean ( 5 / 13 )4229.51156.91826.9536
Winsorized Mean ( 6 / 13 )4192.93147.5328.4209
Winsorized Mean ( 7 / 13 )4191.22142.9229.3255
Winsorized Mean ( 8 / 13 )4160133.80731.0896
Winsorized Mean ( 9 / 13 )4162.2131.67931.6086
Winsorized Mean ( 10 / 13 )4154.88127.3232.6335
Winsorized Mean ( 11 / 13 )4090.49113.56736.0183
Winsorized Mean ( 12 / 13 )4122.68105.49239.0806
Winsorized Mean ( 13 / 13 )4040.2486.96446.4588
Trimmed Mean ( 1 / 13 )4241.54166.94525.4068
Trimmed Mean ( 2 / 13 )4212.7160.37826.2674
Trimmed Mean ( 3 / 13 )4192.57156.37626.8109
Trimmed Mean ( 4 / 13 )4179.39154.10827.1199
Trimmed Mean ( 5 / 13 )4163.23150.95327.5797
Trimmed Mean ( 6 / 13 )4144.48145.99528.3879
Trimmed Mean ( 7 / 13 )4132.22142.33829.031
Trimmed Mean ( 8 / 13 )4118.4138.10529.8209
Trimmed Mean ( 9 / 13 )4109.13134.78930.4858
Trimmed Mean ( 10 / 13 )4097.62129.4631.6516
Trimmed Mean ( 11 / 13 )4085.26121.73533.5585
Trimmed Mean ( 12 / 13 )4084.12115.14135.4706
Trimmed Mean ( 13 / 13 )4075.33106.44438.2861
Median4090
Midrange4715
Midmean - Weighted Average at Xnp4042.5
Midmean - Weighted Average at X(n+1)p4097.62
Midmean - Empirical Distribution Function4097.62
Midmean - Empirical Distribution Function - Averaging4097.62
Midmean - Empirical Distribution Function - Interpolation4097.62
Midmean - Closest Observation4056.82
Midmean - True Basic - Statistics Graphics Toolkit4097.62
Midmean - MS Excel (old versions)4097.62
Number of observations41



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')