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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 computationTue, 24 Nov 2015 14:59:56 +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/2015/Nov/24/t14483772627wxk7g94ex2wlwh.htm/, Retrieved Sun, 19 May 2024 14:51:24 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=284031, Retrieved Sun, 19 May 2024 14:51:24 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact89
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [Mediaan jongens j...] [2015-11-24 14:59:56] [d7b41ff8615e11945ad30de5daa5ba50] [Current]
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Dataseries X:
12,9
12,8
7,4
6,7
14,8
13,3
11,1
8,2
11,4
6,4
11,3
10
6,4
10,8
13,8
11,7
13,4
11,7
9
9,7
10,8
12,7
11,8
5,9
11,4
13
11,3
6,7
12,1
13,3
5,7
13,3
7,6
11,1
13
9,9
11,1




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ jenkins.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 & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=284031&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]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=284031&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=284031&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'Gwilym Jenkins' @ jenkins.wessa.net







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean10.63513513513510.41897945895983225.3834284896404
Geometric Mean10.2928749628629
Harmonic Mean9.90765675978956
Quadratic Mean10.9282055103148
Winsorized Mean ( 1 / 12 )10.61351351351350.41058008773060825.8500444387779
Winsorized Mean ( 2 / 12 )10.61891891891890.39785154696317126.6906563515308
Winsorized Mean ( 3 / 12 )10.61081081081080.39630015211620126.7746826594696
Winsorized Mean ( 4 / 12 )10.64324324324320.38692094273124127.5075398300064
Winsorized Mean ( 5 / 12 )10.64324324324320.38692094273124127.5075398300064
Winsorized Mean ( 6 / 12 )10.70810810810810.34663501194654730.8915941525242
Winsorized Mean ( 7 / 12 )10.74594594594590.3367080207095331.9147311171902
Winsorized Mean ( 8 / 12 )10.85405405405410.29981462226957136.2025506691094
Winsorized Mean ( 9 / 12 )11.02432432432430.24903433333631244.2682909486073
Winsorized Mean ( 10 / 12 )11.18648648648650.20272772618316455.1798547593807
Winsorized Mean ( 11 / 12 )11.06756756756760.15524145941575171.2926019197461
Winsorized Mean ( 12 / 12 )11.00270270270270.13114685201746783.8960488448269
Trimmed Mean ( 1 / 12 )10.65714285714290.40178772175035426.5243119195279
Trimmed Mean ( 2 / 12 )10.70606060606060.38866368265963527.5458219630885
Trimmed Mean ( 3 / 12 )10.7580645161290.37907000498385528.3801524116561
Trimmed Mean ( 4 / 12 )10.82068965517240.36481250027009929.6609618561892
Trimmed Mean ( 5 / 12 )10.88148148148150.3476431446770431.3007221574594
Trimmed Mean ( 6 / 12 )10.9520.31984996482726134.2410542577823
Trimmed Mean ( 7 / 12 )11.01739130434780.29646482130809937.1625586325404
Trimmed Mean ( 8 / 12 )11.08571428571430.26170555194410342.3594921978654
Trimmed Mean ( 9 / 12 )11.14210526315790.22351730959484949.8489592745826
Trimmed Mean ( 10 / 12 )11.17058823529410.18918647544512759.0453847665984
Trimmed Mean ( 11 / 12 )11.16666666666670.15786270908810370.7365706009428
Trimmed Mean ( 12 / 12 )11.19230769230770.13275268043145484.3094667160923
Median11.3
Midrange10.25
Midmean - Weighted Average at Xnp11.05
Midmean - Weighted Average at X(n+1)p11.1421052631579
Midmean - Empirical Distribution Function11.1421052631579
Midmean - Empirical Distribution Function - Averaging11.1421052631579
Midmean - Empirical Distribution Function - Interpolation11.1421052631579
Midmean - Closest Observation10.995
Midmean - True Basic - Statistics Graphics Toolkit11.1421052631579
Midmean - MS Excel (old versions)11.1421052631579
Number of observations37

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 10.6351351351351 & 0.418979458959832 & 25.3834284896404 \tabularnewline
Geometric Mean & 10.2928749628629 &  &  \tabularnewline
Harmonic Mean & 9.90765675978956 &  &  \tabularnewline
Quadratic Mean & 10.9282055103148 &  &  \tabularnewline
Winsorized Mean ( 1 / 12 ) & 10.6135135135135 & 0.410580087730608 & 25.8500444387779 \tabularnewline
Winsorized Mean ( 2 / 12 ) & 10.6189189189189 & 0.397851546963171 & 26.6906563515308 \tabularnewline
Winsorized Mean ( 3 / 12 ) & 10.6108108108108 & 0.396300152116201 & 26.7746826594696 \tabularnewline
Winsorized Mean ( 4 / 12 ) & 10.6432432432432 & 0.386920942731241 & 27.5075398300064 \tabularnewline
Winsorized Mean ( 5 / 12 ) & 10.6432432432432 & 0.386920942731241 & 27.5075398300064 \tabularnewline
Winsorized Mean ( 6 / 12 ) & 10.7081081081081 & 0.346635011946547 & 30.8915941525242 \tabularnewline
Winsorized Mean ( 7 / 12 ) & 10.7459459459459 & 0.33670802070953 & 31.9147311171902 \tabularnewline
Winsorized Mean ( 8 / 12 ) & 10.8540540540541 & 0.299814622269571 & 36.2025506691094 \tabularnewline
Winsorized Mean ( 9 / 12 ) & 11.0243243243243 & 0.249034333336312 & 44.2682909486073 \tabularnewline
Winsorized Mean ( 10 / 12 ) & 11.1864864864865 & 0.202727726183164 & 55.1798547593807 \tabularnewline
Winsorized Mean ( 11 / 12 ) & 11.0675675675676 & 0.155241459415751 & 71.2926019197461 \tabularnewline
Winsorized Mean ( 12 / 12 ) & 11.0027027027027 & 0.131146852017467 & 83.8960488448269 \tabularnewline
Trimmed Mean ( 1 / 12 ) & 10.6571428571429 & 0.401787721750354 & 26.5243119195279 \tabularnewline
Trimmed Mean ( 2 / 12 ) & 10.7060606060606 & 0.388663682659635 & 27.5458219630885 \tabularnewline
Trimmed Mean ( 3 / 12 ) & 10.758064516129 & 0.379070004983855 & 28.3801524116561 \tabularnewline
Trimmed Mean ( 4 / 12 ) & 10.8206896551724 & 0.364812500270099 & 29.6609618561892 \tabularnewline
Trimmed Mean ( 5 / 12 ) & 10.8814814814815 & 0.34764314467704 & 31.3007221574594 \tabularnewline
Trimmed Mean ( 6 / 12 ) & 10.952 & 0.319849964827261 & 34.2410542577823 \tabularnewline
Trimmed Mean ( 7 / 12 ) & 11.0173913043478 & 0.296464821308099 & 37.1625586325404 \tabularnewline
Trimmed Mean ( 8 / 12 ) & 11.0857142857143 & 0.261705551944103 & 42.3594921978654 \tabularnewline
Trimmed Mean ( 9 / 12 ) & 11.1421052631579 & 0.223517309594849 & 49.8489592745826 \tabularnewline
Trimmed Mean ( 10 / 12 ) & 11.1705882352941 & 0.189186475445127 & 59.0453847665984 \tabularnewline
Trimmed Mean ( 11 / 12 ) & 11.1666666666667 & 0.157862709088103 & 70.7365706009428 \tabularnewline
Trimmed Mean ( 12 / 12 ) & 11.1923076923077 & 0.132752680431454 & 84.3094667160923 \tabularnewline
Median & 11.3 &  &  \tabularnewline
Midrange & 10.25 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 11.05 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 11.1421052631579 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 11.1421052631579 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 11.1421052631579 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 11.1421052631579 &  &  \tabularnewline
Midmean - Closest Observation & 10.995 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 11.1421052631579 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 11.1421052631579 &  &  \tabularnewline
Number of observations & 37 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=284031&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]10.6351351351351[/C][C]0.418979458959832[/C][C]25.3834284896404[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]10.2928749628629[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]9.90765675978956[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]10.9282055103148[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 12 )[/C][C]10.6135135135135[/C][C]0.410580087730608[/C][C]25.8500444387779[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 12 )[/C][C]10.6189189189189[/C][C]0.397851546963171[/C][C]26.6906563515308[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 12 )[/C][C]10.6108108108108[/C][C]0.396300152116201[/C][C]26.7746826594696[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 12 )[/C][C]10.6432432432432[/C][C]0.386920942731241[/C][C]27.5075398300064[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 12 )[/C][C]10.6432432432432[/C][C]0.386920942731241[/C][C]27.5075398300064[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 12 )[/C][C]10.7081081081081[/C][C]0.346635011946547[/C][C]30.8915941525242[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 12 )[/C][C]10.7459459459459[/C][C]0.33670802070953[/C][C]31.9147311171902[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 12 )[/C][C]10.8540540540541[/C][C]0.299814622269571[/C][C]36.2025506691094[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 12 )[/C][C]11.0243243243243[/C][C]0.249034333336312[/C][C]44.2682909486073[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 12 )[/C][C]11.1864864864865[/C][C]0.202727726183164[/C][C]55.1798547593807[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 12 )[/C][C]11.0675675675676[/C][C]0.155241459415751[/C][C]71.2926019197461[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 12 )[/C][C]11.0027027027027[/C][C]0.131146852017467[/C][C]83.8960488448269[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 12 )[/C][C]10.6571428571429[/C][C]0.401787721750354[/C][C]26.5243119195279[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 12 )[/C][C]10.7060606060606[/C][C]0.388663682659635[/C][C]27.5458219630885[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 12 )[/C][C]10.758064516129[/C][C]0.379070004983855[/C][C]28.3801524116561[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 12 )[/C][C]10.8206896551724[/C][C]0.364812500270099[/C][C]29.6609618561892[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 12 )[/C][C]10.8814814814815[/C][C]0.34764314467704[/C][C]31.3007221574594[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 12 )[/C][C]10.952[/C][C]0.319849964827261[/C][C]34.2410542577823[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 12 )[/C][C]11.0173913043478[/C][C]0.296464821308099[/C][C]37.1625586325404[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 12 )[/C][C]11.0857142857143[/C][C]0.261705551944103[/C][C]42.3594921978654[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 12 )[/C][C]11.1421052631579[/C][C]0.223517309594849[/C][C]49.8489592745826[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 12 )[/C][C]11.1705882352941[/C][C]0.189186475445127[/C][C]59.0453847665984[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 12 )[/C][C]11.1666666666667[/C][C]0.157862709088103[/C][C]70.7365706009428[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 12 )[/C][C]11.1923076923077[/C][C]0.132752680431454[/C][C]84.3094667160923[/C][/ROW]
[ROW][C]Median[/C][C]11.3[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]10.25[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]11.05[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]11.1421052631579[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]11.1421052631579[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]11.1421052631579[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]11.1421052631579[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]10.995[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]11.1421052631579[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]11.1421052631579[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]37[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=284031&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=284031&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 Mean10.63513513513510.41897945895983225.3834284896404
Geometric Mean10.2928749628629
Harmonic Mean9.90765675978956
Quadratic Mean10.9282055103148
Winsorized Mean ( 1 / 12 )10.61351351351350.41058008773060825.8500444387779
Winsorized Mean ( 2 / 12 )10.61891891891890.39785154696317126.6906563515308
Winsorized Mean ( 3 / 12 )10.61081081081080.39630015211620126.7746826594696
Winsorized Mean ( 4 / 12 )10.64324324324320.38692094273124127.5075398300064
Winsorized Mean ( 5 / 12 )10.64324324324320.38692094273124127.5075398300064
Winsorized Mean ( 6 / 12 )10.70810810810810.34663501194654730.8915941525242
Winsorized Mean ( 7 / 12 )10.74594594594590.3367080207095331.9147311171902
Winsorized Mean ( 8 / 12 )10.85405405405410.29981462226957136.2025506691094
Winsorized Mean ( 9 / 12 )11.02432432432430.24903433333631244.2682909486073
Winsorized Mean ( 10 / 12 )11.18648648648650.20272772618316455.1798547593807
Winsorized Mean ( 11 / 12 )11.06756756756760.15524145941575171.2926019197461
Winsorized Mean ( 12 / 12 )11.00270270270270.13114685201746783.8960488448269
Trimmed Mean ( 1 / 12 )10.65714285714290.40178772175035426.5243119195279
Trimmed Mean ( 2 / 12 )10.70606060606060.38866368265963527.5458219630885
Trimmed Mean ( 3 / 12 )10.7580645161290.37907000498385528.3801524116561
Trimmed Mean ( 4 / 12 )10.82068965517240.36481250027009929.6609618561892
Trimmed Mean ( 5 / 12 )10.88148148148150.3476431446770431.3007221574594
Trimmed Mean ( 6 / 12 )10.9520.31984996482726134.2410542577823
Trimmed Mean ( 7 / 12 )11.01739130434780.29646482130809937.1625586325404
Trimmed Mean ( 8 / 12 )11.08571428571430.26170555194410342.3594921978654
Trimmed Mean ( 9 / 12 )11.14210526315790.22351730959484949.8489592745826
Trimmed Mean ( 10 / 12 )11.17058823529410.18918647544512759.0453847665984
Trimmed Mean ( 11 / 12 )11.16666666666670.15786270908810370.7365706009428
Trimmed Mean ( 12 / 12 )11.19230769230770.13275268043145484.3094667160923
Median11.3
Midrange10.25
Midmean - Weighted Average at Xnp11.05
Midmean - Weighted Average at X(n+1)p11.1421052631579
Midmean - Empirical Distribution Function11.1421052631579
Midmean - Empirical Distribution Function - Averaging11.1421052631579
Midmean - Empirical Distribution Function - Interpolation11.1421052631579
Midmean - Closest Observation10.995
Midmean - True Basic - Statistics Graphics Toolkit11.1421052631579
Midmean - MS Excel (old versions)11.1421052631579
Number of observations37



Parameters (Session):
par1 = 8 ; par2 = 0 ;
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')