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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 computationThu, 22 Dec 2016 17:02:31 +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/22/t1482422770tfhti8pf2581hsv.htm/, Retrieved Mon, 29 Apr 2024 02:17:43 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=302549, Retrieved Mon, 29 Apr 2024 02:17:43 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact71
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [CT] [2016-12-22 16:02:31] [636d0f72197ac5e1dae4a755427db02a] [Current]
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Dataseries X:
2601.76
2819.1
2368.84
2683.5
2649.22
2760.3
2326
2819.3
2957.02
3460.5
2873.16
3252.48
3628.52
3899.22
3049.36
3751.58
4639.42
4991.02
4076.28
4782.4
5173.8
5177.94
4048.46
4828.98
4727.62
5366.84
4597.38
4838.16
4268.2
4769.34
4223.34
4396.38
4911.6
5368.4
4665
5081.46
















































































































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
R Framework error message
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.

\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
R Framework error message & 
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
\tabularnewline \hline \end{tabular} %Source: https://freestatistics.org/blog/index.php?pk=302549&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] [ROW]R Framework error message[/C][C]
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=302549&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=302549&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
R Framework error message
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean3967.55163.52124.2632
Geometric Mean3840.44
Harmonic Mean3707.68
Quadratic Mean4083.79
Winsorized Mean ( 1 / 12 )3968.7163.17324.322
Winsorized Mean ( 2 / 12 )3971.14157.31125.2439
Winsorized Mean ( 3 / 12 )3974.75156.26425.4361
Winsorized Mean ( 4 / 12 )3968.3153.15525.9103
Winsorized Mean ( 5 / 12 )3966.41148.08926.784
Winsorized Mean ( 6 / 12 )3962.97143.26927.6611
Winsorized Mean ( 7 / 12 )3948.73140.61828.0812
Winsorized Mean ( 8 / 12 )3958.66137.52628.7847
Winsorized Mean ( 9 / 12 )3967.98130.75630.3464
Winsorized Mean ( 10 / 12 )3990124.50632.0467
Winsorized Mean ( 11 / 12 )4039.32109.10537.0223
Winsorized Mean ( 12 / 12 )4087.7991.365244.7412
Trimmed Mean ( 1 / 12 )3974.63160.85924.7087
Trimmed Mean ( 2 / 12 )3981.31157.20125.3263
Trimmed Mean ( 3 / 12 )3987.4156.02225.5567
Trimmed Mean ( 4 / 12 )3992.82154.21425.8915
Trimmed Mean ( 5 / 12 )4001.31152.30426.2719
Trimmed Mean ( 6 / 12 )4011.78150.81626.6005
Trimmed Mean ( 7 / 12 )4025.1149.45426.932
Trimmed Mean ( 8 / 12 )4044.73146.86827.5399
Trimmed Mean ( 9 / 12 )4066.25142.35128.5649
Trimmed Mean ( 10 / 12 )4090.82136.13430.0498
Trimmed Mean ( 11 / 12 )4116.74126.08632.6502
Trimmed Mean ( 12 / 12 )4137.86115.72935.7546
Median4149.81
Midrange3847.2
Midmean - Weighted Average at Xnp4003.46
Midmean - Weighted Average at X(n+1)p4066.25
Midmean - Empirical Distribution Function4003.46
Midmean - Empirical Distribution Function - Averaging4066.25
Midmean - Empirical Distribution Function - Interpolation4066.25
Midmean - Closest Observation4003.46
Midmean - True Basic - Statistics Graphics Toolkit4066.25
Midmean - MS Excel (old versions)4044.73
Number of observations36

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 3967.55 & 163.521 & 24.2632 \tabularnewline
Geometric Mean & 3840.44 &  &  \tabularnewline
Harmonic Mean & 3707.68 &  &  \tabularnewline
Quadratic Mean & 4083.79 &  &  \tabularnewline
Winsorized Mean ( 1 / 12 ) & 3968.7 & 163.173 & 24.322 \tabularnewline
Winsorized Mean ( 2 / 12 ) & 3971.14 & 157.311 & 25.2439 \tabularnewline
Winsorized Mean ( 3 / 12 ) & 3974.75 & 156.264 & 25.4361 \tabularnewline
Winsorized Mean ( 4 / 12 ) & 3968.3 & 153.155 & 25.9103 \tabularnewline
Winsorized Mean ( 5 / 12 ) & 3966.41 & 148.089 & 26.784 \tabularnewline
Winsorized Mean ( 6 / 12 ) & 3962.97 & 143.269 & 27.6611 \tabularnewline
Winsorized Mean ( 7 / 12 ) & 3948.73 & 140.618 & 28.0812 \tabularnewline
Winsorized Mean ( 8 / 12 ) & 3958.66 & 137.526 & 28.7847 \tabularnewline
Winsorized Mean ( 9 / 12 ) & 3967.98 & 130.756 & 30.3464 \tabularnewline
Winsorized Mean ( 10 / 12 ) & 3990 & 124.506 & 32.0467 \tabularnewline
Winsorized Mean ( 11 / 12 ) & 4039.32 & 109.105 & 37.0223 \tabularnewline
Winsorized Mean ( 12 / 12 ) & 4087.79 & 91.3652 & 44.7412 \tabularnewline
Trimmed Mean ( 1 / 12 ) & 3974.63 & 160.859 & 24.7087 \tabularnewline
Trimmed Mean ( 2 / 12 ) & 3981.31 & 157.201 & 25.3263 \tabularnewline
Trimmed Mean ( 3 / 12 ) & 3987.4 & 156.022 & 25.5567 \tabularnewline
Trimmed Mean ( 4 / 12 ) & 3992.82 & 154.214 & 25.8915 \tabularnewline
Trimmed Mean ( 5 / 12 ) & 4001.31 & 152.304 & 26.2719 \tabularnewline
Trimmed Mean ( 6 / 12 ) & 4011.78 & 150.816 & 26.6005 \tabularnewline
Trimmed Mean ( 7 / 12 ) & 4025.1 & 149.454 & 26.932 \tabularnewline
Trimmed Mean ( 8 / 12 ) & 4044.73 & 146.868 & 27.5399 \tabularnewline
Trimmed Mean ( 9 / 12 ) & 4066.25 & 142.351 & 28.5649 \tabularnewline
Trimmed Mean ( 10 / 12 ) & 4090.82 & 136.134 & 30.0498 \tabularnewline
Trimmed Mean ( 11 / 12 ) & 4116.74 & 126.086 & 32.6502 \tabularnewline
Trimmed Mean ( 12 / 12 ) & 4137.86 & 115.729 & 35.7546 \tabularnewline
Median & 4149.81 &  &  \tabularnewline
Midrange & 3847.2 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 4003.46 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 4066.25 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 4003.46 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 4066.25 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 4066.25 &  &  \tabularnewline
Midmean - Closest Observation & 4003.46 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 4066.25 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 4044.73 &  &  \tabularnewline
Number of observations & 36 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=302549&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]3967.55[/C][C]163.521[/C][C]24.2632[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]3840.44[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]3707.68[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]4083.79[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 12 )[/C][C]3968.7[/C][C]163.173[/C][C]24.322[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 12 )[/C][C]3971.14[/C][C]157.311[/C][C]25.2439[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 12 )[/C][C]3974.75[/C][C]156.264[/C][C]25.4361[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 12 )[/C][C]3968.3[/C][C]153.155[/C][C]25.9103[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 12 )[/C][C]3966.41[/C][C]148.089[/C][C]26.784[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 12 )[/C][C]3962.97[/C][C]143.269[/C][C]27.6611[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 12 )[/C][C]3948.73[/C][C]140.618[/C][C]28.0812[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 12 )[/C][C]3958.66[/C][C]137.526[/C][C]28.7847[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 12 )[/C][C]3967.98[/C][C]130.756[/C][C]30.3464[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 12 )[/C][C]3990[/C][C]124.506[/C][C]32.0467[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 12 )[/C][C]4039.32[/C][C]109.105[/C][C]37.0223[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 12 )[/C][C]4087.79[/C][C]91.3652[/C][C]44.7412[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 12 )[/C][C]3974.63[/C][C]160.859[/C][C]24.7087[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 12 )[/C][C]3981.31[/C][C]157.201[/C][C]25.3263[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 12 )[/C][C]3987.4[/C][C]156.022[/C][C]25.5567[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 12 )[/C][C]3992.82[/C][C]154.214[/C][C]25.8915[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 12 )[/C][C]4001.31[/C][C]152.304[/C][C]26.2719[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 12 )[/C][C]4011.78[/C][C]150.816[/C][C]26.6005[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 12 )[/C][C]4025.1[/C][C]149.454[/C][C]26.932[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 12 )[/C][C]4044.73[/C][C]146.868[/C][C]27.5399[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 12 )[/C][C]4066.25[/C][C]142.351[/C][C]28.5649[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 12 )[/C][C]4090.82[/C][C]136.134[/C][C]30.0498[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 12 )[/C][C]4116.74[/C][C]126.086[/C][C]32.6502[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 12 )[/C][C]4137.86[/C][C]115.729[/C][C]35.7546[/C][/ROW]
[ROW][C]Median[/C][C]4149.81[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]3847.2[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]4003.46[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]4066.25[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]4003.46[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]4066.25[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]4066.25[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]4003.46[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]4066.25[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]4044.73[/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=302549&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=302549&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 Mean3967.55163.52124.2632
Geometric Mean3840.44
Harmonic Mean3707.68
Quadratic Mean4083.79
Winsorized Mean ( 1 / 12 )3968.7163.17324.322
Winsorized Mean ( 2 / 12 )3971.14157.31125.2439
Winsorized Mean ( 3 / 12 )3974.75156.26425.4361
Winsorized Mean ( 4 / 12 )3968.3153.15525.9103
Winsorized Mean ( 5 / 12 )3966.41148.08926.784
Winsorized Mean ( 6 / 12 )3962.97143.26927.6611
Winsorized Mean ( 7 / 12 )3948.73140.61828.0812
Winsorized Mean ( 8 / 12 )3958.66137.52628.7847
Winsorized Mean ( 9 / 12 )3967.98130.75630.3464
Winsorized Mean ( 10 / 12 )3990124.50632.0467
Winsorized Mean ( 11 / 12 )4039.32109.10537.0223
Winsorized Mean ( 12 / 12 )4087.7991.365244.7412
Trimmed Mean ( 1 / 12 )3974.63160.85924.7087
Trimmed Mean ( 2 / 12 )3981.31157.20125.3263
Trimmed Mean ( 3 / 12 )3987.4156.02225.5567
Trimmed Mean ( 4 / 12 )3992.82154.21425.8915
Trimmed Mean ( 5 / 12 )4001.31152.30426.2719
Trimmed Mean ( 6 / 12 )4011.78150.81626.6005
Trimmed Mean ( 7 / 12 )4025.1149.45426.932
Trimmed Mean ( 8 / 12 )4044.73146.86827.5399
Trimmed Mean ( 9 / 12 )4066.25142.35128.5649
Trimmed Mean ( 10 / 12 )4090.82136.13430.0498
Trimmed Mean ( 11 / 12 )4116.74126.08632.6502
Trimmed Mean ( 12 / 12 )4137.86115.72935.7546
Median4149.81
Midrange3847.2
Midmean - Weighted Average at Xnp4003.46
Midmean - Weighted Average at X(n+1)p4066.25
Midmean - Empirical Distribution Function4003.46
Midmean - Empirical Distribution Function - Averaging4066.25
Midmean - Empirical Distribution Function - Interpolation4066.25
Midmean - Closest Observation4003.46
Midmean - True Basic - Statistics Graphics Toolkit4066.25
Midmean - MS Excel (old versions)4044.73
Number of observations36



Parameters (Session):
par1 = 12 ; par2 = -0.3 ; par3 = 0 ; par4 = 1 ; par5 = 12 ; par6 = 3 ; par7 = 1 ; par8 = 2 ; par9 = 0 ; par10 = FALSE ;
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')