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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 computationSat, 17 Dec 2016 12:38:20 +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/17/t1481974746lni2sojsbjt2jkr.htm/, Retrieved Fri, 01 Nov 2024 03:40:41 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=300716, Retrieved Fri, 01 Nov 2024 03:40:41 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact92
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [Central Tendency ...] [2016-12-17 11:38:20] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataseries X:
6590
6600
6610
6730
6860
6880
6880
7000
7110
7130
7120
7220
7330
7280
7140
7170
7210
7160
7120
7230
7370
7360
7340
7470
7610
7640
7590
7730
7850
7800
7710
7800
7900
7870
7810
7940
8100
8140
8080
8130




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=300716&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=300716&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=300716&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 Mean7390.2570.7383104.473
Geometric Mean7377
Harmonic Mean7363.72
Quadratic Mean7403.44
Winsorized Mean ( 1 / 13 )7390.2570.5986104.68
Winsorized Mean ( 2 / 13 )7389.2570.0589105.472
Winsorized Mean ( 3 / 13 )7396.7567.238110.008
Winsorized Mean ( 4 / 13 )7395.7560.6587121.924
Winsorized Mean ( 5 / 13 )7393.2558.9702125.373
Winsorized Mean ( 6 / 13 )7388.7557.9956127.402
Winsorized Mean ( 7 / 13 )7406.2552.7994140.271
Winsorized Mean ( 8 / 13 )7420.2547.0386157.748
Winsorized Mean ( 9 / 13 )7420.2546.1845160.665
Winsorized Mean ( 10 / 13 )7420.2546.1845160.665
Winsorized Mean ( 11 / 13 )7403.7541.762177.284
Winsorized Mean ( 12 / 13 )7400.7540.0647184.72
Winsorized Mean ( 13 / 13 )7384.534.5668213.63
Trimmed Mean ( 1 / 13 )7391.5868.5322107.856
Trimmed Mean ( 2 / 13 )7393.0665.6564112.602
Trimmed Mean ( 3 / 13 )7395.2962.0394119.203
Trimmed Mean ( 4 / 13 )7394.6958.6044126.18
Trimmed Mean ( 5 / 13 )7394.3356.9708129.792
Trimmed Mean ( 6 / 13 )7394.6455.1992133.963
Trimmed Mean ( 7 / 13 )7396.1552.8076140.059
Trimmed Mean ( 8 / 13 )7393.7551.2447144.283
Trimmed Mean ( 9 / 13 )7387.7350.8581145.261
Trimmed Mean ( 10 / 13 )7380.550.0604147.432
Trimmed Mean ( 11 / 13 )7371.6748.0689153.356
Trimmed Mean ( 12 / 13 )7364.3846.5203158.304
Trimmed Mean ( 13 / 13 )7355.7143.7615168.086
Median7335
Midrange7365
Midmean - Weighted Average at Xnp7387.73
Midmean - Weighted Average at X(n+1)p7387.73
Midmean - Empirical Distribution Function7387.73
Midmean - Empirical Distribution Function - Averaging7387.73
Midmean - Empirical Distribution Function - Interpolation7387.73
Midmean - Closest Observation7387.73
Midmean - True Basic - Statistics Graphics Toolkit7387.73
Midmean - MS Excel (old versions)7387.73
Number of observations40

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 7390.25 & 70.7383 & 104.473 \tabularnewline
Geometric Mean & 7377 &  &  \tabularnewline
Harmonic Mean & 7363.72 &  &  \tabularnewline
Quadratic Mean & 7403.44 &  &  \tabularnewline
Winsorized Mean ( 1 / 13 ) & 7390.25 & 70.5986 & 104.68 \tabularnewline
Winsorized Mean ( 2 / 13 ) & 7389.25 & 70.0589 & 105.472 \tabularnewline
Winsorized Mean ( 3 / 13 ) & 7396.75 & 67.238 & 110.008 \tabularnewline
Winsorized Mean ( 4 / 13 ) & 7395.75 & 60.6587 & 121.924 \tabularnewline
Winsorized Mean ( 5 / 13 ) & 7393.25 & 58.9702 & 125.373 \tabularnewline
Winsorized Mean ( 6 / 13 ) & 7388.75 & 57.9956 & 127.402 \tabularnewline
Winsorized Mean ( 7 / 13 ) & 7406.25 & 52.7994 & 140.271 \tabularnewline
Winsorized Mean ( 8 / 13 ) & 7420.25 & 47.0386 & 157.748 \tabularnewline
Winsorized Mean ( 9 / 13 ) & 7420.25 & 46.1845 & 160.665 \tabularnewline
Winsorized Mean ( 10 / 13 ) & 7420.25 & 46.1845 & 160.665 \tabularnewline
Winsorized Mean ( 11 / 13 ) & 7403.75 & 41.762 & 177.284 \tabularnewline
Winsorized Mean ( 12 / 13 ) & 7400.75 & 40.0647 & 184.72 \tabularnewline
Winsorized Mean ( 13 / 13 ) & 7384.5 & 34.5668 & 213.63 \tabularnewline
Trimmed Mean ( 1 / 13 ) & 7391.58 & 68.5322 & 107.856 \tabularnewline
Trimmed Mean ( 2 / 13 ) & 7393.06 & 65.6564 & 112.602 \tabularnewline
Trimmed Mean ( 3 / 13 ) & 7395.29 & 62.0394 & 119.203 \tabularnewline
Trimmed Mean ( 4 / 13 ) & 7394.69 & 58.6044 & 126.18 \tabularnewline
Trimmed Mean ( 5 / 13 ) & 7394.33 & 56.9708 & 129.792 \tabularnewline
Trimmed Mean ( 6 / 13 ) & 7394.64 & 55.1992 & 133.963 \tabularnewline
Trimmed Mean ( 7 / 13 ) & 7396.15 & 52.8076 & 140.059 \tabularnewline
Trimmed Mean ( 8 / 13 ) & 7393.75 & 51.2447 & 144.283 \tabularnewline
Trimmed Mean ( 9 / 13 ) & 7387.73 & 50.8581 & 145.261 \tabularnewline
Trimmed Mean ( 10 / 13 ) & 7380.5 & 50.0604 & 147.432 \tabularnewline
Trimmed Mean ( 11 / 13 ) & 7371.67 & 48.0689 & 153.356 \tabularnewline
Trimmed Mean ( 12 / 13 ) & 7364.38 & 46.5203 & 158.304 \tabularnewline
Trimmed Mean ( 13 / 13 ) & 7355.71 & 43.7615 & 168.086 \tabularnewline
Median & 7335 &  &  \tabularnewline
Midrange & 7365 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 7387.73 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 7387.73 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 7387.73 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 7387.73 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 7387.73 &  &  \tabularnewline
Midmean - Closest Observation & 7387.73 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 7387.73 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 7387.73 &  &  \tabularnewline
Number of observations & 40 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=300716&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]7390.25[/C][C]70.7383[/C][C]104.473[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]7377[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]7363.72[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]7403.44[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 13 )[/C][C]7390.25[/C][C]70.5986[/C][C]104.68[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 13 )[/C][C]7389.25[/C][C]70.0589[/C][C]105.472[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 13 )[/C][C]7396.75[/C][C]67.238[/C][C]110.008[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 13 )[/C][C]7395.75[/C][C]60.6587[/C][C]121.924[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 13 )[/C][C]7393.25[/C][C]58.9702[/C][C]125.373[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 13 )[/C][C]7388.75[/C][C]57.9956[/C][C]127.402[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 13 )[/C][C]7406.25[/C][C]52.7994[/C][C]140.271[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 13 )[/C][C]7420.25[/C][C]47.0386[/C][C]157.748[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 13 )[/C][C]7420.25[/C][C]46.1845[/C][C]160.665[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 13 )[/C][C]7420.25[/C][C]46.1845[/C][C]160.665[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 13 )[/C][C]7403.75[/C][C]41.762[/C][C]177.284[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 13 )[/C][C]7400.75[/C][C]40.0647[/C][C]184.72[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 13 )[/C][C]7384.5[/C][C]34.5668[/C][C]213.63[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 13 )[/C][C]7391.58[/C][C]68.5322[/C][C]107.856[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 13 )[/C][C]7393.06[/C][C]65.6564[/C][C]112.602[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 13 )[/C][C]7395.29[/C][C]62.0394[/C][C]119.203[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 13 )[/C][C]7394.69[/C][C]58.6044[/C][C]126.18[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 13 )[/C][C]7394.33[/C][C]56.9708[/C][C]129.792[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 13 )[/C][C]7394.64[/C][C]55.1992[/C][C]133.963[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 13 )[/C][C]7396.15[/C][C]52.8076[/C][C]140.059[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 13 )[/C][C]7393.75[/C][C]51.2447[/C][C]144.283[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 13 )[/C][C]7387.73[/C][C]50.8581[/C][C]145.261[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 13 )[/C][C]7380.5[/C][C]50.0604[/C][C]147.432[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 13 )[/C][C]7371.67[/C][C]48.0689[/C][C]153.356[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 13 )[/C][C]7364.38[/C][C]46.5203[/C][C]158.304[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 13 )[/C][C]7355.71[/C][C]43.7615[/C][C]168.086[/C][/ROW]
[ROW][C]Median[/C][C]7335[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]7365[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]7387.73[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]7387.73[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]7387.73[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]7387.73[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]7387.73[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]7387.73[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]7387.73[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]7387.73[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]40[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=300716&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=300716&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 Mean7390.2570.7383104.473
Geometric Mean7377
Harmonic Mean7363.72
Quadratic Mean7403.44
Winsorized Mean ( 1 / 13 )7390.2570.5986104.68
Winsorized Mean ( 2 / 13 )7389.2570.0589105.472
Winsorized Mean ( 3 / 13 )7396.7567.238110.008
Winsorized Mean ( 4 / 13 )7395.7560.6587121.924
Winsorized Mean ( 5 / 13 )7393.2558.9702125.373
Winsorized Mean ( 6 / 13 )7388.7557.9956127.402
Winsorized Mean ( 7 / 13 )7406.2552.7994140.271
Winsorized Mean ( 8 / 13 )7420.2547.0386157.748
Winsorized Mean ( 9 / 13 )7420.2546.1845160.665
Winsorized Mean ( 10 / 13 )7420.2546.1845160.665
Winsorized Mean ( 11 / 13 )7403.7541.762177.284
Winsorized Mean ( 12 / 13 )7400.7540.0647184.72
Winsorized Mean ( 13 / 13 )7384.534.5668213.63
Trimmed Mean ( 1 / 13 )7391.5868.5322107.856
Trimmed Mean ( 2 / 13 )7393.0665.6564112.602
Trimmed Mean ( 3 / 13 )7395.2962.0394119.203
Trimmed Mean ( 4 / 13 )7394.6958.6044126.18
Trimmed Mean ( 5 / 13 )7394.3356.9708129.792
Trimmed Mean ( 6 / 13 )7394.6455.1992133.963
Trimmed Mean ( 7 / 13 )7396.1552.8076140.059
Trimmed Mean ( 8 / 13 )7393.7551.2447144.283
Trimmed Mean ( 9 / 13 )7387.7350.8581145.261
Trimmed Mean ( 10 / 13 )7380.550.0604147.432
Trimmed Mean ( 11 / 13 )7371.6748.0689153.356
Trimmed Mean ( 12 / 13 )7364.3846.5203158.304
Trimmed Mean ( 13 / 13 )7355.7143.7615168.086
Median7335
Midrange7365
Midmean - Weighted Average at Xnp7387.73
Midmean - Weighted Average at X(n+1)p7387.73
Midmean - Empirical Distribution Function7387.73
Midmean - Empirical Distribution Function - Averaging7387.73
Midmean - Empirical Distribution Function - Interpolation7387.73
Midmean - Closest Observation7387.73
Midmean - True Basic - Statistics Graphics Toolkit7387.73
Midmean - MS Excel (old versions)7387.73
Number of observations40



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')