bezettingsgraad bedden toeristische sector België

*Unverified author*

R Software Module: /rwasp_centraltendency.wasp (opens new window with default values)

Title produced by software: Central Tendency

Date of computation: Wed, 25 Nov 2009 10:40:17 -0700

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2009/Nov/25/t1259170852jto6zrlukdn203e.htm/, Retrieved Wed, 25 Nov 2009 18:40:54 +0100

BibTeX entries for LaTeX users:

@Manual{KEY, author = {{YOUR NAME}}, publisher = {Office for Research Development and Education}, title = {Statistical Computations at FreeStatistics.org, URL http://www.freestatistics.org/blog/date/2009/Nov/25/t1259170852jto6zrlukdn203e.htm/}, year = {2009}, } @Manual{R, title = {R: A Language and Environment for Statistical Computing}, author = {{R Development Core Team}}, organization = {R Foundation for Statistical Computing}, address = {Vienna, Austria}, year = {2009}, note = {{ISBN} 3-900051-07-0}, url = {http://www.R-project.org}, }

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords:

KDGP1W52

Dataseries X:

» Textbox « » Textfile « » CSV «

24.3 29.4 31.8 36.7 37.1 37.7 39.4 43.3 39.6 34.3 32 29.6 22.3 28.9 31.7 34.2 38.6 37.2 38.8 43.4 38.8 36.3 33 29.2 22.64 28.44 30.14 34.39 36.82 36.74 38.9 42.8 39.09 37.49 33.17 30.98 21.2 27.8 29 35.4 37.5 34.7 38.4 39.9 35.9 34.7 30.4 29 21.5 28 29.3 34.3 36.6 36.2 37.5 41.6 39.4 37.3 32.7 30.7 22.9 29.1 29.5 37.1 37.7 38.4 39.4 40.6 39.7 36.6 32.8 31.6 24.1 30.3 31.8 38.7 37.8 38.4 40.7 43.8 41.5 39.3 35.9 33.4

Output produced by software:

Summary of computational transaction Raw Input view raw input (R code) Raw Output view raw output of R engine Computing time 1 seconds R Server 'Gwilym Jenkins' @ 72.249.127.135 Central Tendency - Ungrouped Data Measure Value S.E. Value/S.E. Arithmetic Mean 34.3964285714286 0.590250115767886 58.2743275309324 Geometric Mean 33.9352480725001 Harmonic Mean 33.4285058062099 Quadratic Mean 34.8142370302725 Winsorized Mean ( 1 / 28 ) 34.3952380952381 0.588401533630601 58.4553848509026 Winsorized Mean ( 2 / 28 ) 34.4119047619048 0.583064501848508 59.0190358919255 Winsorized Mean ( 3 / 28 ) 34.4061904761905 0.576847226269177 59.6452386513432 Winsorized Mean ( 4 / 28 ) 34.3614285714286 0.564380639379184 60.883428973088 Winsorized Mean ( 5 / 28 ) 34.4269047619048 0.546578833817654 62.9861652736265 Winsorized Mean ( 6 / 28 ) 34.3840476190476 0.53480596100099 64.2925661387383 Winsorized Mean ( 7 / 28 ) 34.6673809523810 0.474572825372433 73.0496545502259 Winsorized Mean ( 8 / 28 ) 34.6197619047619 0.461646942466982 74.9918578898375 Winsorized Mean ( 9 / 28 ) 34.6454761904762 0.450738458432996 76.8638121338083 Winsorized Mean ( 10 / 28 ) 34.6883333333333 0.440252653734524 78.7918778889421 Winsorized Mean ( 11 / 28 ) 34.6752380952381 0.434710238302329 79.7663248757497 Winsorized Mean ( 12 / 28 ) 34.6752380952381 0.434710238302329 79.7663248757497 Winsorized Mean ( 13 / 28 ) 34.6907142857143 0.43228733544014 80.2492033461804 Winsorized Mean ( 14 / 28 ) 34.6907142857143 0.427523045975030 81.1434953327416 Winsorized Mean ( 15 / 28 ) 34.6710714285714 0.419952460832258 82.5595148552306 Winsorized Mean ( 16 / 28 ) 34.6539285714286 0.412484601074111 84.0126600634051 Winsorized Mean ( 17 / 28 ) 34.6539285714286 0.406890028921333 85.1677999170838 Winsorized Mean ( 18 / 28 ) 34.6753571428571 0.403631693594861 85.9084102985777 Winsorized Mean ( 19 / 28 ) 34.7748809523810 0.382668578267284 90.8746704781483 Winsorized Mean ( 20 / 28 ) 34.7891666666667 0.374203618255451 92.9685469874793 Winsorized Mean ( 21 / 28 ) 34.7641666666667 0.364521244200807 95.369384417869 Winsorized Mean ( 22 / 28 ) 34.8427380952381 0.353302603335351 98.620100068059 Winsorized Mean ( 23 / 28 ) 34.9194047619048 0.342574512131770 101.932290714241 Winsorized Mean ( 24 / 28 ) 34.9251190476190 0.297869683048464 117.249659952593 Winsorized Mean ( 25 / 28 ) 34.9251190476190 0.290433652761794 120.251626199336 Winsorized Mean ( 26 / 28 ) 34.9560714285714 0.286307581969672 122.092719962527 Winsorized Mean ( 27 / 28 ) 34.8917857142857 0.278974289254835 125.071689607973 Winsorized Mean ( 28 / 28 ) 34.9584523809524 0.270124091989370 129.416269846557 Trimmed Mean ( 1 / 28 ) 34.4426829268293 0.571092104984128 60.3102067534036 Trimmed Mean ( 2 / 28 ) 34.4925 0.550936759792936 62.6070041377592 Trimmed Mean ( 3 / 28 ) 34.5358974358974 0.53076228758644 65.0684840344331 Trimmed Mean ( 4 / 28 ) 34.5836842105263 0.509895167832695 67.8250871792411 Trimmed Mean ( 5 / 28 ) 34.6467567567568 0.48979383902106 70.7374286822481 Trimmed Mean ( 6 / 28 ) 34.6980555555556 0.471723633269536 73.5558982174837 Trimmed Mean ( 7 / 28 ) 34.7608571428571 0.453447696398191 76.6590224605138 Trimmed Mean ( 8 / 28 ) 34.7773529411765 0.447054530442397 77.7921944035808 Trimmed Mean ( 9 / 28 ) 34.8024242424242 0.442059286840428 78.7279563589104 Trimmed Mean ( 10 / 28 ) 34.8253125 0.438090925681172 79.4933436383128 Trimmed Mean ( 11 / 28 ) 34.8438709677419 0.435078684133752 80.0863665318759 Trimmed Mean ( 12 / 28 ) 34.8653333333333 0.432105309058753 80.6871209457709 Trimmed Mean ( 13 / 28 ) 34.8882758620690 0.428130344791559 81.4898459931748 Trimmed Mean ( 14 / 28 ) 34.9110714285714 0.42337785758923 82.4584252642775 Trimmed Mean ( 15 / 28 ) 34.9355555555556 0.418047996825319 83.5682883804209 Trimmed Mean ( 16 / 28 ) 34.9640384615385 0.412435767622588 84.77450601116 Trimmed Mean ( 17 / 28 ) 34.9966 0.406383011255065 86.1172810642777 Trimmed Mean ( 18 / 28 ) 35.031875 0.399396891984812 87.711936930476 Trimmed Mean ( 19 / 28 ) 35.0680434782609 0.390780294545842 89.7385153952462 Trimmed Mean ( 20 / 28 ) 35.0975 0.383729077288744 91.4642701772382 Trimmed Mean ( 21 / 28 ) 35.1283333333333 0.375861212658073 93.4609162911686 Trimmed Mean ( 22 / 28 ) 35.16475 0.36703576774981 95.8074201203466 Trimmed Mean ( 23 / 28 ) 35.1971052631579 0.35751949044041 98.4480740331118 Trimmed Mean ( 24 / 28 ) 35.2252777777778 0.346918517973421 101.537611723790 Trimmed Mean ( 25 / 28 ) 35.2561764705882 0.342788974000384 102.850964134420 Trimmed Mean ( 26 / 28 ) 35.2909375 0.337779859886524 104.479105154037 Trimmed Mean ( 27 / 28 ) 35.327 0.330713665783004 106.820502613217 Trimmed Mean ( 28 / 28 ) 35.3753571428571 0.321055831792135 110.184440336722 Median 35.9 Midrange 32.5 Midmean - Weighted Average at Xnp 35.0160465116279 Midmean - Weighted Average at X(n+1)p 35.1283333333333 Midmean - Empirical Distribution Function 35.0160465116279 Midmean - Empirical Distribution Function - Averaging 35.1283333333333 Midmean - Empirical Distribution Function - Interpolation 35.1283333333333 Midmean - Closest Observation 35.0160465116279 Midmean - True Basic - Statistics Graphics Toolkit 35.1283333333333 Midmean - MS Excel (old versions) 35.0975 Number of observations 84

Charts produced by software:

http://www.freestatistics.org/blog/date/2009/Nov/25/t1259170852jto6zrlukdn203e/18evq1259170815.png (open in new window) http://www.freestatistics.org/blog/date/2009/Nov/25/t1259170852jto6zrlukdn203e/18evq1259170815.ps (open in new window) http://www.freestatistics.org/blog/date/2009/Nov/25/t1259170852jto6zrlukdn203e/2mvey1259170815.png (open in new window) http://www.freestatistics.org/blog/date/2009/Nov/25/t1259170852jto6zrlukdn203e/2mvey1259170815.ps (open in new window)

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('http://www.xycoon.com/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('http://www.xycoon.com/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('http://www.xycoon.com/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('http://www.xycoon.com/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('http://www.xycoon.com/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('http://www.xycoon.com/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('http://www.xycoon.com/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('http://www.xycoon.com/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('http://www.xycoon.com/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('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean') mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/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('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean') mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/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('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean') mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/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('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean') mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/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('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean') mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/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('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean') mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/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('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean') mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/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('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean') mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/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')

Copyright

This work is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 3.0 License.

Software written by Ed van Stee & Patrick Wessa

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