Centrummaten Toegekende bouwvergunningen voor het aantal woningen

*Unverified author*

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

Title produced by software: Central Tendency

Date of computation: Sun, 10 Jan 2010 08:35:23 -0700

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2010/Jan/10/t1263137894xhyrtu9yrwzeo1u.htm/, Retrieved Sun, 10 Jan 2010 16:38:16 +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/2010/Jan/10/t1263137894xhyrtu9yrwzeo1u.htm/}, year = {2010}, } @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 = {2010}, 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 «

2766 3851 3289 3848 3348 3682 4058 3655 3811 3341 3032 3475 3353 3186 3902 4164 3499 4145 3796 3711 3949 3740 3243 4407 4814 3908 5250 3937 4004 5560 3922 3759 4138 4634 3996 4308 4143 4429 5219 4929 5761 5592 4163 4962 5208 4755 4491 5732 5731 5040 6102 4904 5369 5578 4619 4731 5011 5299 4146 4625 4736 4219 5116 4205 4121 5103 4300 4578 3809 5526 4248 3830 4430 4837 4408 4569 4104 4807 3944 3794 4390 4041 4104 4823

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 4357.88095238095 77.8572907179964 55.9726765752156 Geometric Mean 4300.39476437426 Harmonic Mean 4243.06754287287 Quadratic Mean 4415.22958471179 Winsorized Mean ( 1 / 28 ) 4356.98809523810 76.1347272890799 57.2273422441618 Winsorized Mean ( 2 / 28 ) 4359.96428571429 75.2529554210769 57.9374492512375 Winsorized Mean ( 3 / 28 ) 4361.96428571429 74.870487615519 58.2601292529868 Winsorized Mean ( 4 / 28 ) 4357.53571428571 73.0769198534615 59.6294387205115 Winsorized Mean ( 5 / 28 ) 4359.79761904762 72.3724406150177 60.2411302147372 Winsorized Mean ( 6 / 28 ) 4359.01190476190 72.0282433569795 60.5180926481601 Winsorized Mean ( 7 / 28 ) 4356.59523809524 71.3935384063253 61.0222624532258 Winsorized Mean ( 8 / 28 ) 4353.26190476190 66.6329291836356 65.3319906253052 Winsorized Mean ( 9 / 28 ) 4348.33333333333 64.8747819285235 67.0265579948178 Winsorized Mean ( 10 / 28 ) 4361.07142857143 61.0853775174306 71.3930502815834 Winsorized Mean ( 11 / 28 ) 4360.54761904762 59.891366096153 72.807616577771 Winsorized Mean ( 12 / 28 ) 4363.11904761905 59.0618990445603 73.8736667496454 Winsorized Mean ( 13 / 28 ) 4353.36904761905 56.0724594218192 77.6382754119938 Winsorized Mean ( 14 / 28 ) 4354.36904761905 55.3041913417611 78.7348832335424 Winsorized Mean ( 15 / 28 ) 4349.36904761905 52.6955494809661 82.5376922806367 Winsorized Mean ( 16 / 28 ) 4344.22619047619 51.7824079338325 83.8938621013383 Winsorized Mean ( 17 / 28 ) 4336.94047619048 49.9295468959894 86.8612023502829 Winsorized Mean ( 18 / 28 ) 4330.29761904762 48.818953705457 88.7011558087443 Winsorized Mean ( 19 / 28 ) 4328.94047619048 47.4404822372476 91.2499256340113 Winsorized Mean ( 20 / 28 ) 4317.27380952381 44.6115520569906 96.7747951025903 Winsorized Mean ( 21 / 28 ) 4314.52380952381 44.0273068794658 97.9965415857878 Winsorized Mean ( 22 / 28 ) 4325.52380952381 42.0397302596851 102.891331195621 Winsorized Mean ( 23 / 28 ) 4325.25 41.5727347698927 104.040545418541 Winsorized Mean ( 24 / 28 ) 4314.39285714286 39.0406176599226 110.510363712094 Winsorized Mean ( 25 / 28 ) 4313.20238095238 37.7360073110582 114.299383752993 Winsorized Mean ( 26 / 28 ) 4313.82142857143 37.2675398170368 115.752782441501 Winsorized Mean ( 27 / 28 ) 4284.25 32.9715618133383 129.937733136647 Winsorized Mean ( 28 / 28 ) 4296.91666666667 30.7008833174176 139.960685242854 Trimmed Mean ( 1 / 28 ) 4356.0243902439 74.3194111907378 58.6122026594686 Trimmed Mean ( 2 / 28 ) 4355.0125 72.2153699008797 60.3058947974308 Trimmed Mean ( 3 / 28 ) 4352.34615384615 70.3162752408285 61.8967108104015 Trimmed Mean ( 4 / 28 ) 4348.80263157895 68.2663103568094 63.7034960414433 Trimmed Mean ( 5 / 28 ) 4346.32432432432 66.5076237459307 65.3507685213344 Trimmed Mean ( 6 / 28 ) 4343.18055555556 64.6497404351851 67.1801700412058 Trimmed Mean ( 7 / 28 ) 4340.01428571429 62.5449287551303 69.3903466211606 Trimmed Mean ( 8 / 28 ) 4337.08823529412 60.2033820147296 72.0406078554356 Trimmed Mean ( 9 / 28 ) 4334.51515151515 58.5459126604246 74.0361701534317 Trimmed Mean ( 10 / 28 ) 4332.5 56.9476794474054 76.0786048183284 Trimmed Mean ( 11 / 28 ) 4328.62903225806 55.7962137514344 77.5792610506083 Trimmed Mean ( 12 / 28 ) 4324.56666666667 54.623282874751 79.1707572132331 Trimmed Mean ( 13 / 28 ) 4319.91379310345 53.334471126415 80.9966556687936 Trimmed Mean ( 14 / 28 ) 4316.05357142857 52.326543509124 82.483062743787 Trimmed Mean ( 15 / 28 ) 4311.7962962963 51.2003872088402 84.2141345281042 Trimmed Mean ( 16 / 28 ) 4307.75 50.2761219932958 85.6818272613473 Trimmed Mean ( 17 / 28 ) 4303.92 49.2649963908225 87.3626370710903 Trimmed Mean ( 18 / 28 ) 4300.52083333333 48.321461518125 88.9981531647225 Trimmed Mean ( 19 / 28 ) 4297.5 47.3074102313996 90.8420050681108 Trimmed Mean ( 20 / 28 ) 4294.34090909091 46.2425577485357 92.8655575767085 Trimmed Mean ( 21 / 28 ) 4292.04761904762 45.4164105935001 94.504333630934 Trimmed Mean ( 22 / 28 ) 4289.8 44.3994715838272 96.6182669967314 Trimmed Mean ( 23 / 28 ) 4286.21052631579 43.4106423142713 98.736399597264 Trimmed Mean ( 24 / 28 ) 4282.25 42.1143073189193 101.681596412634 Trimmed Mean ( 25 / 28 ) 4278.94117647059 40.9459219287612 104.502255045453 Trimmed Mean ( 26 / 28 ) 4275.34375 39.5905100578806 107.989105059509 Trimmed Mean ( 27 / 28 ) 4271.2 37.7064097115243 113.275170791309 Trimmed Mean ( 28 / 28 ) 4269.75 36.3959568441767 117.313854895483 Median 4212 Midrange 4434 Midmean - Weighted Average at Xnp 4281.72093023256 Midmean - Weighted Average at X(n+1)p 4292.04761904762 Midmean - Empirical Distribution Function 4281.72093023256 Midmean - Empirical Distribution Function - Averaging 4292.04761904762 Midmean - Empirical Distribution Function - Interpolation 4292.04761904762 Midmean - Closest Observation 4281.72093023256 Midmean - True Basic - Statistics Graphics Toolkit 4292.04761904762 Midmean - MS Excel (old versions) 4294.34090909091 Number of observations 84

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Jan/10/t1263137894xhyrtu9yrwzeo1u/18vai1263137720.png (open in new window) http://www.freestatistics.org/blog/date/2010/Jan/10/t1263137894xhyrtu9yrwzeo1u/18vai1263137720.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Jan/10/t1263137894xhyrtu9yrwzeo1u/2rn731263137720.png (open in new window) http://www.freestatistics.org/blog/date/2010/Jan/10/t1263137894xhyrtu9yrwzeo1u/2rn731263137720.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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