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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, 21 Jan 2016 15:33:19 +0000
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/Jan/21/t1453392344qi0euj6e0zbyigr.htm/, Retrieved Sun, 28 Apr 2024 22:07:20 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=289917, Retrieved Sun, 28 Apr 2024 22:07:20 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact63
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [examenvraag 6b Je...] [2016-01-21 15:33:19] [ccc71ceaf436dffbdd9bd6ede4807a6d] [Current]
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Dataseries X:
19.6427
13.7242
14.8027
8.42832
6.80835
8.82499
8.76937
7.69536
7.65933
1.86731
3.72965
3.26542
-7.7517
0.957393
-3.04433
-12.5655
-6.9441
-6.8168
-8.56987
-4.46034
-11.229
-3.03305
-9.87928
-4.30931
-2.82241
-2.62636
-4.92814
-2.61029
-6.89788
-7.6867




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational 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 & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=289917&T=0

[TABLE]
[ROW][C]Summary of computational 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]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=289917&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=289917&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 Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean1.10000000006945e-061.528167619095797.19816325332371e-07
Geometric MeanNaN
Harmonic Mean-71.8167341927852
Quadratic Mean8.22943448175723
Winsorized Mean ( 1 / 10 )-0.1167822333333331.45142875654578-0.0804601898692297
Winsorized Mean ( 2 / 10 )-0.09870091.40376560768307-0.0703115245592224
Winsorized Mean ( 3 / 10 )-0.45768091.22451083485156-0.373766313023668
Winsorized Mean ( 4 / 10 )-0.3560075666666661.19849213036825-0.2970462280443
Winsorized Mean ( 5 / 10 )-0.40201591.18139963920658-0.340287813419337
Winsorized Mean ( 6 / 10 )-0.40008791.11324975757638-0.359387367728712
Winsorized Mean ( 7 / 10 )-0.3977102333333331.10895966374305-0.358633633247715
Winsorized Mean ( 8 / 10 )-0.60301691.04846105993163-0.575144774608339
Winsorized Mean ( 9 / 10 )-0.96002890.717590783162815-1.3378500985877
Winsorized Mean ( 10 / 10 )-0.95883890.653611332705087-1.46698634497611
Trimmed Mean ( 1 / 10 )-0.2527559642857141.40209193055057-0.180270607638732
Trimmed Mean ( 2 / 10 )-0.4096487307692311.32340285203765-0.309541973661679
Trimmed Mean ( 3 / 10 )-0.6039911251.23949262732296-0.487289001713946
Trimmed Mean ( 4 / 10 )-0.6704957727272731.22704247501186-0.546432406686485
Trimmed Mean ( 5 / 10 )-0.788428851.20968664000609-0.651762881332667
Trimmed Mean ( 6 / 10 )-0.9172331666666671.17606388674331-0.779917806341808
Trimmed Mean ( 7 / 10 )-1.07884106251.14075793267673-0.945723042195778
Trimmed Mean ( 8 / 10 )-1.28735051.05219123622344-1.22349479417886
Trimmed Mean ( 9 / 10 )-1.501204750.891157666894153-1.68455572539927
Trimmed Mean ( 10 / 10 )-1.68159670.852436006978042-1.97269552932355
Median-2.724385
Midrange3.5386
Midmean - Weighted Average at Xnp-1.6613858
Midmean - Weighted Average at X(n+1)p-1.0788410625
Midmean - Empirical Distribution Function-1.0788410625
Midmean - Empirical Distribution Function - Averaging-1.0788410625
Midmean - Empirical Distribution Function - Interpolation-1.2873505
Midmean - Closest Observation-1.0788410625
Midmean - True Basic - Statistics Graphics Toolkit-1.0788410625
Midmean - MS Excel (old versions)-1.0788410625
Number of observations30

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 1.10000000006945e-06 & 1.52816761909579 & 7.19816325332371e-07 \tabularnewline
Geometric Mean & NaN &  &  \tabularnewline
Harmonic Mean & -71.8167341927852 &  &  \tabularnewline
Quadratic Mean & 8.22943448175723 &  &  \tabularnewline
Winsorized Mean ( 1 / 10 ) & -0.116782233333333 & 1.45142875654578 & -0.0804601898692297 \tabularnewline
Winsorized Mean ( 2 / 10 ) & -0.0987009 & 1.40376560768307 & -0.0703115245592224 \tabularnewline
Winsorized Mean ( 3 / 10 ) & -0.4576809 & 1.22451083485156 & -0.373766313023668 \tabularnewline
Winsorized Mean ( 4 / 10 ) & -0.356007566666666 & 1.19849213036825 & -0.2970462280443 \tabularnewline
Winsorized Mean ( 5 / 10 ) & -0.4020159 & 1.18139963920658 & -0.340287813419337 \tabularnewline
Winsorized Mean ( 6 / 10 ) & -0.4000879 & 1.11324975757638 & -0.359387367728712 \tabularnewline
Winsorized Mean ( 7 / 10 ) & -0.397710233333333 & 1.10895966374305 & -0.358633633247715 \tabularnewline
Winsorized Mean ( 8 / 10 ) & -0.6030169 & 1.04846105993163 & -0.575144774608339 \tabularnewline
Winsorized Mean ( 9 / 10 ) & -0.9600289 & 0.717590783162815 & -1.3378500985877 \tabularnewline
Winsorized Mean ( 10 / 10 ) & -0.9588389 & 0.653611332705087 & -1.46698634497611 \tabularnewline
Trimmed Mean ( 1 / 10 ) & -0.252755964285714 & 1.40209193055057 & -0.180270607638732 \tabularnewline
Trimmed Mean ( 2 / 10 ) & -0.409648730769231 & 1.32340285203765 & -0.309541973661679 \tabularnewline
Trimmed Mean ( 3 / 10 ) & -0.603991125 & 1.23949262732296 & -0.487289001713946 \tabularnewline
Trimmed Mean ( 4 / 10 ) & -0.670495772727273 & 1.22704247501186 & -0.546432406686485 \tabularnewline
Trimmed Mean ( 5 / 10 ) & -0.78842885 & 1.20968664000609 & -0.651762881332667 \tabularnewline
Trimmed Mean ( 6 / 10 ) & -0.917233166666667 & 1.17606388674331 & -0.779917806341808 \tabularnewline
Trimmed Mean ( 7 / 10 ) & -1.0788410625 & 1.14075793267673 & -0.945723042195778 \tabularnewline
Trimmed Mean ( 8 / 10 ) & -1.2873505 & 1.05219123622344 & -1.22349479417886 \tabularnewline
Trimmed Mean ( 9 / 10 ) & -1.50120475 & 0.891157666894153 & -1.68455572539927 \tabularnewline
Trimmed Mean ( 10 / 10 ) & -1.6815967 & 0.852436006978042 & -1.97269552932355 \tabularnewline
Median & -2.724385 &  &  \tabularnewline
Midrange & 3.5386 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & -1.6613858 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & -1.0788410625 &  &  \tabularnewline
Midmean - Empirical Distribution Function & -1.0788410625 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & -1.0788410625 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & -1.2873505 &  &  \tabularnewline
Midmean - Closest Observation & -1.0788410625 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & -1.0788410625 &  &  \tabularnewline
Midmean - MS Excel (old versions) & -1.0788410625 &  &  \tabularnewline
Number of observations & 30 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=289917&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]1.10000000006945e-06[/C][C]1.52816761909579[/C][C]7.19816325332371e-07[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]NaN[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]-71.8167341927852[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]8.22943448175723[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 10 )[/C][C]-0.116782233333333[/C][C]1.45142875654578[/C][C]-0.0804601898692297[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 10 )[/C][C]-0.0987009[/C][C]1.40376560768307[/C][C]-0.0703115245592224[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 10 )[/C][C]-0.4576809[/C][C]1.22451083485156[/C][C]-0.373766313023668[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 10 )[/C][C]-0.356007566666666[/C][C]1.19849213036825[/C][C]-0.2970462280443[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 10 )[/C][C]-0.4020159[/C][C]1.18139963920658[/C][C]-0.340287813419337[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 10 )[/C][C]-0.4000879[/C][C]1.11324975757638[/C][C]-0.359387367728712[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 10 )[/C][C]-0.397710233333333[/C][C]1.10895966374305[/C][C]-0.358633633247715[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 10 )[/C][C]-0.6030169[/C][C]1.04846105993163[/C][C]-0.575144774608339[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 10 )[/C][C]-0.9600289[/C][C]0.717590783162815[/C][C]-1.3378500985877[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 10 )[/C][C]-0.9588389[/C][C]0.653611332705087[/C][C]-1.46698634497611[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 10 )[/C][C]-0.252755964285714[/C][C]1.40209193055057[/C][C]-0.180270607638732[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 10 )[/C][C]-0.409648730769231[/C][C]1.32340285203765[/C][C]-0.309541973661679[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 10 )[/C][C]-0.603991125[/C][C]1.23949262732296[/C][C]-0.487289001713946[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 10 )[/C][C]-0.670495772727273[/C][C]1.22704247501186[/C][C]-0.546432406686485[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 10 )[/C][C]-0.78842885[/C][C]1.20968664000609[/C][C]-0.651762881332667[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 10 )[/C][C]-0.917233166666667[/C][C]1.17606388674331[/C][C]-0.779917806341808[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 10 )[/C][C]-1.0788410625[/C][C]1.14075793267673[/C][C]-0.945723042195778[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 10 )[/C][C]-1.2873505[/C][C]1.05219123622344[/C][C]-1.22349479417886[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 10 )[/C][C]-1.50120475[/C][C]0.891157666894153[/C][C]-1.68455572539927[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 10 )[/C][C]-1.6815967[/C][C]0.852436006978042[/C][C]-1.97269552932355[/C][/ROW]
[ROW][C]Median[/C][C]-2.724385[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]3.5386[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]-1.6613858[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]-1.0788410625[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]-1.0788410625[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]-1.0788410625[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]-1.2873505[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]-1.0788410625[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]-1.0788410625[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]-1.0788410625[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]30[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=289917&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=289917&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 Mean1.10000000006945e-061.528167619095797.19816325332371e-07
Geometric MeanNaN
Harmonic Mean-71.8167341927852
Quadratic Mean8.22943448175723
Winsorized Mean ( 1 / 10 )-0.1167822333333331.45142875654578-0.0804601898692297
Winsorized Mean ( 2 / 10 )-0.09870091.40376560768307-0.0703115245592224
Winsorized Mean ( 3 / 10 )-0.45768091.22451083485156-0.373766313023668
Winsorized Mean ( 4 / 10 )-0.3560075666666661.19849213036825-0.2970462280443
Winsorized Mean ( 5 / 10 )-0.40201591.18139963920658-0.340287813419337
Winsorized Mean ( 6 / 10 )-0.40008791.11324975757638-0.359387367728712
Winsorized Mean ( 7 / 10 )-0.3977102333333331.10895966374305-0.358633633247715
Winsorized Mean ( 8 / 10 )-0.60301691.04846105993163-0.575144774608339
Winsorized Mean ( 9 / 10 )-0.96002890.717590783162815-1.3378500985877
Winsorized Mean ( 10 / 10 )-0.95883890.653611332705087-1.46698634497611
Trimmed Mean ( 1 / 10 )-0.2527559642857141.40209193055057-0.180270607638732
Trimmed Mean ( 2 / 10 )-0.4096487307692311.32340285203765-0.309541973661679
Trimmed Mean ( 3 / 10 )-0.6039911251.23949262732296-0.487289001713946
Trimmed Mean ( 4 / 10 )-0.6704957727272731.22704247501186-0.546432406686485
Trimmed Mean ( 5 / 10 )-0.788428851.20968664000609-0.651762881332667
Trimmed Mean ( 6 / 10 )-0.9172331666666671.17606388674331-0.779917806341808
Trimmed Mean ( 7 / 10 )-1.07884106251.14075793267673-0.945723042195778
Trimmed Mean ( 8 / 10 )-1.28735051.05219123622344-1.22349479417886
Trimmed Mean ( 9 / 10 )-1.501204750.891157666894153-1.68455572539927
Trimmed Mean ( 10 / 10 )-1.68159670.852436006978042-1.97269552932355
Median-2.724385
Midrange3.5386
Midmean - Weighted Average at Xnp-1.6613858
Midmean - Weighted Average at X(n+1)p-1.0788410625
Midmean - Empirical Distribution Function-1.0788410625
Midmean - Empirical Distribution Function - Averaging-1.0788410625
Midmean - Empirical Distribution Function - Interpolation-1.2873505
Midmean - Closest Observation-1.0788410625
Midmean - True Basic - Statistics Graphics Toolkit-1.0788410625
Midmean - MS Excel (old versions)-1.0788410625
Number of observations30



Parameters (Session):
par1 = 1 ; par2 = Do not include Seasonal Dummies ; par3 = Linear Trend ;
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')