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of Irreproducible Research!

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_centraltendency.wasp
Title produced by softwareCentral Tendency
Date of computationMon, 20 Oct 2008 11:48:29 -0600
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2008/Oct/20/t1224524941tmxn58ufpe35yy1.htm/, Retrieved Sun, 19 May 2024 16:33:40 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=17789, Retrieved Sun, 19 May 2024 16:33:40 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact132
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F       [Central Tendency] [central tendency ...] [2008-10-20 17:48:29] [db9a5fd0f9c3e1245d8075d8bb09236d] [Current]
Feedback Forum
2008-10-22 19:46:29 [Michaël De Kuyer] [reply
Deze vraag is fout beantwoord. Je zegt dat central tendency robuust is. Naar mijn mening is dit niet zo aangezien de mediaan en het rekenkundig gemiddelde zeer sterk van mekaar verschillen wat er dus op wijst dat er een aantal extreme waarden zijn.
2008-10-23 18:30:09 [Ciska Tanghe] [reply
Deze tijdreeks is niet robuust. Dit kan je zowel aan de mediaan en het gemiddelde zien als aan de grafiek van de winsorized mean.

Post a new message
Dataseries X:
42142,2
43132
41787,8
46750,5
46743,5
45353,7
41891,5
43503,6
44355,8
45864
42867,9
45672,9
45492,1
45797,2
43089,1
46556,4
47793
49670,2
47602,5
51996,8
51698,3
53634,6
50601,8
54876,9
56339,7
56404,9
53204,9
57236,7
58848,9
59262,1
57189,2
60739,3
65855
66902,3




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\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 & 3 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=17789&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=17789&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=17789&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 time3 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean50319.33235294121196.6737035010842.0493340880836
Geometric Mean49872.5802742308
Harmonic Mean49449.4262254005
Quadratic Mean50786.7318389679
Winsorized Mean ( 1 / 11 )50291.57941176471183.4090165607842.4972082415951
Winsorized Mean ( 2 / 11 )50005.40294117651073.9584170864146.5617682636524
Winsorized Mean ( 3 / 11 )49939.09411764711022.3448327796548.8476026057351
Winsorized Mean ( 4 / 11 )49916.50588235291003.6617465542349.7343911469441
Winsorized Mean ( 5 / 11 )49685.7264705882941.4638183168852.774971808704
Winsorized Mean ( 6 / 11 )49742.9205882353925.80924237983553.7291250845248
Winsorized Mean ( 7 / 11 )49756.9852.21372671832258.3854712028664
Winsorized Mean ( 8 / 11 )49976.3588235294805.54261658351962.0406143569288
Winsorized Mean ( 9 / 11 )49625.7823529412709.15266774929869.9789828196557
Winsorized Mean ( 10 / 11 )49313.5764705882619.98810532921679.539552528032
Winsorized Mean ( 11 / 11 )49214.7705882353583.75603492900484.3070865969218
Trimmed Mean ( 1 / 11 )50067.7251125.6394698161944.4793615918389
Trimmed Mean ( 2 / 11 )49814.02333333331038.8477586037047.9512256928652
Trimmed Mean ( 3 / 11 )49697.82857142861002.8474547950049.5567180569727
Trimmed Mean ( 4 / 11 )49592.6615384615978.1463680951650.7006549899461
Trimmed Mean ( 5 / 11 )49477.9666666667945.63329486513352.3225725398377
Trimmed Mean ( 6 / 11 )49413.75922.36610639788953.5728163223335
Trimmed Mean ( 7 / 11 )49320.485884.7974839438855.7421171454509
Trimmed Mean ( 8 / 11 )49202.7222222222852.52919554229857.7138266695068
Trimmed Mean ( 9 / 11 )48997.225806.16260598694860.7783400471856
Trimmed Mean ( 10 / 11 )48827.6142857143772.87932774724163.1762456734807
Trimmed Mean ( 11 / 11 )48689.925755.93356341127464.4103230187038
Median47697.75
Midrange54345.05
Midmean - Weighted Average at Xnp48782.9
Midmean - Weighted Average at X(n+1)p49202.7222222222
Midmean - Empirical Distribution Function49202.7222222222
Midmean - Empirical Distribution Function - Averaging49202.7222222222
Midmean - Empirical Distribution Function - Interpolation48997.225
Midmean - Closest Observation49202.7222222222
Midmean - True Basic - Statistics Graphics Toolkit49202.7222222222
Midmean - MS Excel (old versions)49202.7222222222
Number of observations34

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 50319.3323529412 & 1196.67370350108 & 42.0493340880836 \tabularnewline
Geometric Mean & 49872.5802742308 &  &  \tabularnewline
Harmonic Mean & 49449.4262254005 &  &  \tabularnewline
Quadratic Mean & 50786.7318389679 &  &  \tabularnewline
Winsorized Mean ( 1 / 11 ) & 50291.5794117647 & 1183.40901656078 & 42.4972082415951 \tabularnewline
Winsorized Mean ( 2 / 11 ) & 50005.4029411765 & 1073.95841708641 & 46.5617682636524 \tabularnewline
Winsorized Mean ( 3 / 11 ) & 49939.0941176471 & 1022.34483277965 & 48.8476026057351 \tabularnewline
Winsorized Mean ( 4 / 11 ) & 49916.5058823529 & 1003.66174655423 & 49.7343911469441 \tabularnewline
Winsorized Mean ( 5 / 11 ) & 49685.7264705882 & 941.46381831688 & 52.774971808704 \tabularnewline
Winsorized Mean ( 6 / 11 ) & 49742.9205882353 & 925.809242379835 & 53.7291250845248 \tabularnewline
Winsorized Mean ( 7 / 11 ) & 49756.9 & 852.213726718322 & 58.3854712028664 \tabularnewline
Winsorized Mean ( 8 / 11 ) & 49976.3588235294 & 805.542616583519 & 62.0406143569288 \tabularnewline
Winsorized Mean ( 9 / 11 ) & 49625.7823529412 & 709.152667749298 & 69.9789828196557 \tabularnewline
Winsorized Mean ( 10 / 11 ) & 49313.5764705882 & 619.988105329216 & 79.539552528032 \tabularnewline
Winsorized Mean ( 11 / 11 ) & 49214.7705882353 & 583.756034929004 & 84.3070865969218 \tabularnewline
Trimmed Mean ( 1 / 11 ) & 50067.725 & 1125.63946981619 & 44.4793615918389 \tabularnewline
Trimmed Mean ( 2 / 11 ) & 49814.0233333333 & 1038.84775860370 & 47.9512256928652 \tabularnewline
Trimmed Mean ( 3 / 11 ) & 49697.8285714286 & 1002.84745479500 & 49.5567180569727 \tabularnewline
Trimmed Mean ( 4 / 11 ) & 49592.6615384615 & 978.14636809516 & 50.7006549899461 \tabularnewline
Trimmed Mean ( 5 / 11 ) & 49477.9666666667 & 945.633294865133 & 52.3225725398377 \tabularnewline
Trimmed Mean ( 6 / 11 ) & 49413.75 & 922.366106397889 & 53.5728163223335 \tabularnewline
Trimmed Mean ( 7 / 11 ) & 49320.485 & 884.79748394388 & 55.7421171454509 \tabularnewline
Trimmed Mean ( 8 / 11 ) & 49202.7222222222 & 852.529195542298 & 57.7138266695068 \tabularnewline
Trimmed Mean ( 9 / 11 ) & 48997.225 & 806.162605986948 & 60.7783400471856 \tabularnewline
Trimmed Mean ( 10 / 11 ) & 48827.6142857143 & 772.879327747241 & 63.1762456734807 \tabularnewline
Trimmed Mean ( 11 / 11 ) & 48689.925 & 755.933563411274 & 64.4103230187038 \tabularnewline
Median & 47697.75 &  &  \tabularnewline
Midrange & 54345.05 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 48782.9 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 49202.7222222222 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 49202.7222222222 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 49202.7222222222 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 48997.225 &  &  \tabularnewline
Midmean - Closest Observation & 49202.7222222222 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 49202.7222222222 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 49202.7222222222 &  &  \tabularnewline
Number of observations & 34 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=17789&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]50319.3323529412[/C][C]1196.67370350108[/C][C]42.0493340880836[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]49872.5802742308[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]49449.4262254005[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]50786.7318389679[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 11 )[/C][C]50291.5794117647[/C][C]1183.40901656078[/C][C]42.4972082415951[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 11 )[/C][C]50005.4029411765[/C][C]1073.95841708641[/C][C]46.5617682636524[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 11 )[/C][C]49939.0941176471[/C][C]1022.34483277965[/C][C]48.8476026057351[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 11 )[/C][C]49916.5058823529[/C][C]1003.66174655423[/C][C]49.7343911469441[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 11 )[/C][C]49685.7264705882[/C][C]941.46381831688[/C][C]52.774971808704[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 11 )[/C][C]49742.9205882353[/C][C]925.809242379835[/C][C]53.7291250845248[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 11 )[/C][C]49756.9[/C][C]852.213726718322[/C][C]58.3854712028664[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 11 )[/C][C]49976.3588235294[/C][C]805.542616583519[/C][C]62.0406143569288[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 11 )[/C][C]49625.7823529412[/C][C]709.152667749298[/C][C]69.9789828196557[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 11 )[/C][C]49313.5764705882[/C][C]619.988105329216[/C][C]79.539552528032[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 11 )[/C][C]49214.7705882353[/C][C]583.756034929004[/C][C]84.3070865969218[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 11 )[/C][C]50067.725[/C][C]1125.63946981619[/C][C]44.4793615918389[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 11 )[/C][C]49814.0233333333[/C][C]1038.84775860370[/C][C]47.9512256928652[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 11 )[/C][C]49697.8285714286[/C][C]1002.84745479500[/C][C]49.5567180569727[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 11 )[/C][C]49592.6615384615[/C][C]978.14636809516[/C][C]50.7006549899461[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 11 )[/C][C]49477.9666666667[/C][C]945.633294865133[/C][C]52.3225725398377[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 11 )[/C][C]49413.75[/C][C]922.366106397889[/C][C]53.5728163223335[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 11 )[/C][C]49320.485[/C][C]884.79748394388[/C][C]55.7421171454509[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 11 )[/C][C]49202.7222222222[/C][C]852.529195542298[/C][C]57.7138266695068[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 11 )[/C][C]48997.225[/C][C]806.162605986948[/C][C]60.7783400471856[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 11 )[/C][C]48827.6142857143[/C][C]772.879327747241[/C][C]63.1762456734807[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 11 )[/C][C]48689.925[/C][C]755.933563411274[/C][C]64.4103230187038[/C][/ROW]
[ROW][C]Median[/C][C]47697.75[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]54345.05[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]48782.9[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]49202.7222222222[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]49202.7222222222[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]49202.7222222222[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]48997.225[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]49202.7222222222[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]49202.7222222222[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]49202.7222222222[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]34[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=17789&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=17789&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 Mean50319.33235294121196.6737035010842.0493340880836
Geometric Mean49872.5802742308
Harmonic Mean49449.4262254005
Quadratic Mean50786.7318389679
Winsorized Mean ( 1 / 11 )50291.57941176471183.4090165607842.4972082415951
Winsorized Mean ( 2 / 11 )50005.40294117651073.9584170864146.5617682636524
Winsorized Mean ( 3 / 11 )49939.09411764711022.3448327796548.8476026057351
Winsorized Mean ( 4 / 11 )49916.50588235291003.6617465542349.7343911469441
Winsorized Mean ( 5 / 11 )49685.7264705882941.4638183168852.774971808704
Winsorized Mean ( 6 / 11 )49742.9205882353925.80924237983553.7291250845248
Winsorized Mean ( 7 / 11 )49756.9852.21372671832258.3854712028664
Winsorized Mean ( 8 / 11 )49976.3588235294805.54261658351962.0406143569288
Winsorized Mean ( 9 / 11 )49625.7823529412709.15266774929869.9789828196557
Winsorized Mean ( 10 / 11 )49313.5764705882619.98810532921679.539552528032
Winsorized Mean ( 11 / 11 )49214.7705882353583.75603492900484.3070865969218
Trimmed Mean ( 1 / 11 )50067.7251125.6394698161944.4793615918389
Trimmed Mean ( 2 / 11 )49814.02333333331038.8477586037047.9512256928652
Trimmed Mean ( 3 / 11 )49697.82857142861002.8474547950049.5567180569727
Trimmed Mean ( 4 / 11 )49592.6615384615978.1463680951650.7006549899461
Trimmed Mean ( 5 / 11 )49477.9666666667945.63329486513352.3225725398377
Trimmed Mean ( 6 / 11 )49413.75922.36610639788953.5728163223335
Trimmed Mean ( 7 / 11 )49320.485884.7974839438855.7421171454509
Trimmed Mean ( 8 / 11 )49202.7222222222852.52919554229857.7138266695068
Trimmed Mean ( 9 / 11 )48997.225806.16260598694860.7783400471856
Trimmed Mean ( 10 / 11 )48827.6142857143772.87932774724163.1762456734807
Trimmed Mean ( 11 / 11 )48689.925755.93356341127464.4103230187038
Median47697.75
Midrange54345.05
Midmean - Weighted Average at Xnp48782.9
Midmean - Weighted Average at X(n+1)p49202.7222222222
Midmean - Empirical Distribution Function49202.7222222222
Midmean - Empirical Distribution Function - Averaging49202.7222222222
Midmean - Empirical Distribution Function - Interpolation48997.225
Midmean - Closest Observation49202.7222222222
Midmean - True Basic - Statistics Graphics Toolkit49202.7222222222
Midmean - MS Excel (old versions)49202.7222222222
Number of observations34



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,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')