Aantal nieuwe inschrijvingen personenwagens

*The author of this computation has been verified*

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

Title produced by software: Central Tendency

Date of computation: Tue, 22 Dec 2009 09:06:50 -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/Dec/22/t1261498087f4occpihxhmngzi.htm/, Retrieved Tue, 22 Dec 2009 17:08:10 +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/Dec/22/t1261498087f4occpihxhmngzi.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:

Dataseries X:

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27071 29462 26105 22397 23843 21705 18089 20764 25316 17704 15548 28029 29383 36438 32034 22679 24319 18004 17537 20366 22782 19169 13807 29743 25591 29096 26482 22405 27044 17970 18730 19684 19785 18479 10698 31956 29506 34506 27165 26736 23691 18157 17328 18205 20995 17382 9367 31124 26551 30651 25859 25100 25778 20418 18688 20424 24776 19814 12738 31566 30111 30019 31934 25826 26835 20205 17789 20520 22518 15572 11509 25447 24090 27786 26195 20516 22759 19028 16971

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 2 seconds R Server 'Gwilym Jenkins' @ 72.249.127.135 Central Tendency - Ungrouped Data Measure Value S.E. Value/S.E. Arithmetic Mean 23067.9620253165 641.011591610261 35.9868094855637 Geometric Mean 22311.878982548 Harmonic Mean 21472.8084376397 Quadratic Mean 23752.4893248388 Winsorized Mean ( 1 / 26 ) 23060.3544303797 630.464571406996 36.5767649384586 Winsorized Mean ( 2 / 26 ) 23018.3037974684 612.196896196453 37.5995107790971 Winsorized Mean ( 3 / 26 ) 23062.0126582278 600.86693710804 38.3812309081688 Winsorized Mean ( 4 / 26 ) 23115.0253164557 589.206962935707 39.230740250057 Winsorized Mean ( 5 / 26 ) 23201.9240506329 563.978655316059 41.1397201506329 Winsorized Mean ( 6 / 26 ) 23170.1772151899 557.398065678413 41.5684564441201 Winsorized Mean ( 7 / 26 ) 23252.2278481013 529.514234208053 43.9123754300534 Winsorized Mean ( 8 / 26 ) 23233.6962025316 514.517553636865 45.1562751130731 Winsorized Mean ( 9 / 26 ) 23229.3670886076 511.825058030874 45.385365026826 Winsorized Mean ( 10 / 26 ) 23214.0506329114 503.090984245067 46.1428476356938 Winsorized Mean ( 11 / 26 ) 23204.3037974684 494.307620297395 46.943042843458 Winsorized Mean ( 12 / 26 ) 23210.5316455696 491.382222332429 47.235187987463 Winsorized Mean ( 13 / 26 ) 23227.3164556962 485.088488614739 47.8826379121594 Winsorized Mean ( 14 / 26 ) 23182.4810126582 476.061807421897 48.6963681001895 Winsorized Mean ( 15 / 26 ) 22996.0253164557 442.849764204722 51.9273739656436 Winsorized Mean ( 16 / 26 ) 22960.582278481 433.798408933812 52.9291528175805 Winsorized Mean ( 17 / 26 ) 22837.2784810127 413.82360174925 55.1860222193188 Winsorized Mean ( 18 / 26 ) 22878.2911392405 402.096515334613 56.897511584257 Winsorized Mean ( 19 / 26 ) 22922.0632911392 394.240752953215 58.1422978711169 Winsorized Mean ( 20 / 26 ) 22879.7848101266 385.750884355698 59.3123327464087 Winsorized Mean ( 21 / 26 ) 22932.6835443038 371.491774395425 61.7313359942492 Winsorized Mean ( 22 / 26 ) 22920.4303797468 359.502307388567 63.7560035323317 Winsorized Mean ( 23 / 26 ) 23050.2784810127 337.254972150763 68.3467417367193 Winsorized Mean ( 24 / 26 ) 22993.7721518987 322.086936696363 71.3899557297953 Winsorized Mean ( 25 / 26 ) 22974.4683544304 317.298952713168 72.4063794033346 Winsorized Mean ( 26 / 26 ) 23022.1898734177 290.899984081651 79.141255184654 Trimmed Mean ( 1 / 26 ) 23072.2597402597 608.307799681472 37.9285942944362 Trimmed Mean ( 2 / 26 ) 23084.8 582.260286677223 39.6468736202803 Trimmed Mean ( 3 / 26 ) 23120.7808219178 563.241435334252 41.0495027025079 Trimmed Mean ( 4 / 26 ) 23142.5774647887 545.978765833651 42.3873214729377 Trimmed Mean ( 5 / 26 ) 23150.4637681159 529.817415983564 43.6951732232866 Trimmed Mean ( 6 / 26 ) 23138.3283582090 518.418405656483 44.6325363948227 Trimmed Mean ( 7 / 26 ) 23131.8769230769 506.54925082692 45.665602871419 Trimmed Mean ( 8 / 26 ) 23110.3174603175 499.077597112184 46.3060606086926 Trimmed Mean ( 9 / 26 ) 23090.3442622951 493.241572779121 46.8134592390395 Trimmed Mean ( 10 / 26 ) 23069.6610169492 486.466351528044 47.4229326334388 Trimmed Mean ( 11 / 26 ) 23049.6491228070 479.7425195035 48.0458749969917 Trimmed Mean ( 12 / 26 ) 23029.4545454545 472.960853455265 48.6920944454715 Trimmed Mean ( 13 / 26 ) 23006.9622641509 464.836976090829 49.4946904990953 Trimmed Mean ( 14 / 26 ) 22980.7058823529 455.656528964025 50.4342732333971 Trimmed Mean ( 15 / 26 ) 22957.4693877551 445.712494370294 51.5073498672941 Trimmed Mean ( 16 / 26 ) 22953.1489361702 439.611378057482 52.212363195861 Trimmed Mean ( 17 / 26 ) 22952.3333333333 433.137849846555 52.9908280734748 Trimmed Mean ( 18 / 26 ) 22964.7674418605 428.222422098151 53.6281293476893 Trimmed Mean ( 19 / 26 ) 22974.0243902439 423.535838734392 54.2434011225468 Trimmed Mean ( 20 / 26 ) 22979.5641025641 418.250623512569 54.9420916807636 Trimmed Mean ( 21 / 26 ) 22979.5641025641 412.205115518916 55.7478867617537 Trimmed Mean ( 22 / 26 ) 22996.4 406.452991069791 56.5782526030208 Trimmed Mean ( 23 / 26 ) 23004.6666666667 400.409796396773 57.4528067836556 Trimmed Mean ( 24 / 26 ) 22999.6129032258 396.472222182327 58.0106540040248 Trimmed Mean ( 25 / 26 ) 23000.2758620690 393.360317834272 58.4712662138923 Trimmed Mean ( 26 / 26 ) 23003.2962962963 388.309851514159 59.2395382362776 Median 22759 Midrange 22902.5 Midmean - Weighted Average at Xnp 22872.275 Midmean - Weighted Average at X(n+1)p 22974.0243902439 Midmean - Empirical Distribution Function 22974.0243902439 Midmean - Empirical Distribution Function - Averaging 22974.0243902439 Midmean - Empirical Distribution Function - Interpolation 22979.5641025641 Midmean - Closest Observation 22872.275 Midmean - True Basic - Statistics Graphics Toolkit 22974.0243902439 Midmean - MS Excel (old versions) 22974.0243902439 Number of observations 79

Charts produced by software:

http://www.freestatistics.org/blog/date/2009/Dec/22/t1261498087f4occpihxhmngzi/1a2ws1261498008.png (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/22/t1261498087f4occpihxhmngzi/1a2ws1261498008.ps (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/22/t1261498087f4occpihxhmngzi/2evjk1261498008.png (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/22/t1261498087f4occpihxhmngzi/2evjk1261498008.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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