niet werkende werkzoekende tss 20-25 jaar frederic.ledent@student.kdg.be

*Unverified author*

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

Title produced by software: Central Tendency

Date of computation: Wed, 28 Oct 2009 12:21:49 -0600

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2009/Oct/28/t12567542328kpl0bsj7wcbqix.htm/, Retrieved Wed, 28 Oct 2009 19:23:54 +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/Oct/28/t12567542328kpl0bsj7wcbqix.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 «

89507 87562 85209 82360 79054 79069 107551 115759 115585 110260 103444 102303 101397 97994 94044 91159 87239 89235 118647 125620 125154 117529 109459 108483 107137 104699 100804 96066 91971 93228 120144 127233 127166 118194 109940 106683 102834 99882 96666 92540 88744 89321 115870 122401 122030 113802 105791 103076 98658 96945 92497 90687 88796 90015 113228 118711 117460 106556 97347 92657 93118 89037 83570 81693 75956 73993 97088 102394 96549 89727 82336 82653 82303 79596 74472 73562 66618 69029 89899 93774 90305 83799 80320 82497

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 97591.5476190476 1612.83738071739 60.5092297498949 Geometric Mean 96485.4177383224 Harmonic Mean 95381.4099516348 Quadratic Mean 98691.5064899807 Winsorized Mean ( 1 / 28 ) 97619.4523809524 1606.26202488895 60.7743013707254 Winsorized Mean ( 2 / 28 ) 97690.5714285714 1576.71649148376 61.9582353303355 Winsorized Mean ( 3 / 28 ) 97689.3214285714 1570.36876296022 62.2078862829787 Winsorized Mean ( 4 / 28 ) 97581.0357142857 1539.67976124788 63.3774880792081 Winsorized Mean ( 5 / 28 ) 97647.2857142857 1519.81697455200 64.2493717002139 Winsorized Mean ( 6 / 28 ) 97733.8571428571 1458.17098791237 67.0249634322929 Winsorized Mean ( 7 / 28 ) 97615.6904761905 1436.35242931461 67.960821093727 Winsorized Mean ( 8 / 28 ) 97659.7857142857 1427.54312813801 68.4110930096149 Winsorized Mean ( 9 / 28 ) 97688.8214285714 1407.30267458316 69.4156439782984 Winsorized Mean ( 10 / 28 ) 97773.1071428571 1369.75473157614 71.3800105149862 Winsorized Mean ( 11 / 28 ) 97843.9523809524 1357.02213001892 72.1019578211212 Winsorized Mean ( 12 / 28 ) 97621.5238095238 1317.62505935433 74.0890005973027 Winsorized Mean ( 13 / 28 ) 97608.0595238095 1314.24342944491 74.2693912991717 Winsorized Mean ( 14 / 28 ) 97601.8928571429 1306.23907967917 74.719777087909 Winsorized Mean ( 15 / 28 ) 97311.3571428571 1250.61098030175 77.8110528978224 Winsorized Mean ( 16 / 28 ) 97376.6904761905 1208.93441555206 80.5475377518504 Winsorized Mean ( 17 / 28 ) 96822.369047619 1111.11593318448 87.1397539679992 Winsorized Mean ( 18 / 28 ) 97055.9404761905 1059.38560799323 91.615309613316 Winsorized Mean ( 19 / 28 ) 97406.3095238095 983.780843546249 99.0122039505136 Winsorized Mean ( 20 / 28 ) 97250.8333333333 940.337448254705 103.421206412479 Winsorized Mean ( 21 / 28 ) 97313.3333333333 871.183279655213 111.702480529524 Winsorized Mean ( 22 / 28 ) 97218.5238095238 854.307235536297 113.798080790565 Winsorized Mean ( 23 / 28 ) 97160.2023809524 829.1978583488 117.173725670770 Winsorized Mean ( 24 / 28 ) 97180.4880952381 817.529829916805 118.870877292793 Winsorized Mean ( 25 / 28 ) 96978.4047619048 783.35903910149 123.798156300256 Winsorized Mean ( 26 / 28 ) 96697.9761904762 731.356382580235 132.217313602056 Winsorized Mean ( 27 / 28 ) 96365.2976190476 670.678833324723 143.683224862399 Winsorized Mean ( 28 / 28 ) 96299.9642857143 648.32629001651 148.536262941399 Trimmed Mean ( 1 / 28 ) 97607.7926829268 1566.44841170705 62.3115271166562 Trimmed Mean ( 2 / 28 ) 97595.55 1520.29680853585 64.1950633929114 Trimmed Mean ( 3 / 28 ) 97544.3846153846 1484.98117529682 65.6872869758009 Trimmed Mean ( 4 / 28 ) 97490.9868421053 1446.53671586606 67.39613711342 Trimmed Mean ( 5 / 28 ) 97465.4324324324 1412.42171700140 69.0059004752159 Trimmed Mean ( 6 / 28 ) 97423 1378.23713026667 70.6866749273764 Trimmed Mean ( 7 / 28 ) 97360.8285714286 1354.12119775433 71.8996414300959 Trimmed Mean ( 8 / 28 ) 97315.8529411765 1330.56385713115 73.1388068446414 Trimmed Mean ( 9 / 28 ) 97261.1363636364 1304.17427276670 74.5767942173132 Trimmed Mean ( 10 / 28 ) 97198.765625 1276.63087625882 76.1369378044829 Trimmed Mean ( 11 / 28 ) 97120.9516129032 1250.82480803055 77.6455271668475 Trimmed Mean ( 12 / 28 ) 97028.9333333333 1221.67564741845 79.4228267857899 Trimmed Mean ( 13 / 28 ) 96957.4137931034 1193.88626553114 81.2115999592046 Trimmed Mean ( 14 / 28 ) 96882.3392857143 1160.12692383226 83.5101205699817 Trimmed Mean ( 15 / 28 ) 96802.3888888889 1119.71755710919 86.452506057694 Trimmed Mean ( 16 / 28 ) 96747.576923077 1080.98436207951 89.4995157348638 Trimmed Mean ( 17 / 28 ) 96681.52 1040.69503001698 92.9009144959813 Trimmed Mean ( 18 / 28 ) 96667.0208333333 1010.38897015031 95.6730761015262 Trimmed Mean ( 19 / 28 ) 96627.5652173913 981.86175746642 98.4125967658904 Trimmed Mean ( 20 / 28 ) 96549.3181818182 959.686465367984 100.605063909906 Trimmed Mean ( 21 / 28 ) 96479.1666666667 939.251526288929 102.719201370761 Trimmed Mean ( 22 / 28 ) 96395.75 925.576901007954 104.146667764748 Trimmed Mean ( 23 / 28 ) 96313.0789473684 909.508055155095 105.895795426402 Trimmed Mean ( 24 / 28 ) 96227.1388888889 891.898109840884 107.890282339600 Trimmed Mean ( 25 / 28 ) 96129 868.545601379443 110.678126568514 Trimmed Mean ( 26 / 28 ) 96039.8125 843.886417212796 113.806562756635 Trimmed Mean ( 27 / 28 ) 95968.9333333333 822.553668630672 116.671941288762 Trimmed Mean ( 28 / 28 ) 95924.8928571429 808.146833892446 118.697356512702 Median 96307.5 Midrange 96925.5 Midmean - Weighted Average at Xnp 96271.7906976744 Midmean - Weighted Average at X(n+1)p 96479.1666666667 Midmean - Empirical Distribution Function 96271.7906976744 Midmean - Empirical Distribution Function - Averaging 96479.1666666667 Midmean - Empirical Distribution Function - Interpolation 96479.1666666667 Midmean - Closest Observation 96271.7906976744 Midmean - True Basic - Statistics Graphics Toolkit 96479.1666666667 Midmean - MS Excel (old versions) 96549.3181818182 Number of observations 84

Charts produced by software:

http://www.freestatistics.org/blog/date/2009/Oct/28/t12567542328kpl0bsj7wcbqix/1ci2z1256754108.png (open in new window) http://www.freestatistics.org/blog/date/2009/Oct/28/t12567542328kpl0bsj7wcbqix/1ci2z1256754108.ps (open in new window) http://www.freestatistics.org/blog/date/2009/Oct/28/t12567542328kpl0bsj7wcbqix/2em861256754108.png (open in new window) http://www.freestatistics.org/blog/date/2009/Oct/28/t12567542328kpl0bsj7wcbqix/2em861256754108.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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