Huurprijzen niet sociale huur - Charlotte Van Opstal

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

Title produced by software: Central Tendency

Date of computation: Tue, 15 Apr 2008 05:12:59 -0600

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2008/Apr/15/t12082580609j0rdaf2ejwlhpj.htm/, Retrieved Tue, 15 Apr 2008 13:14:23 +0200

User-defined keywords:

Dataseries X:

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103,6 103,7 103,8 104 104 104,1 104,2 104,3 104,4 104,5 104,7 104,7 104,9 105 105,2 105,3 105,4 105,5 105,7 105,8 105,9 106 106,1 106,2 106,6 106,8 107 107,1 107,3 107,4 107,6 107,7 107,9 108,2 108,3 108,5 108,92 109,23 109,41 109,65 109,91 110,01 110,2 110,49 110,57 110,72 110,94 111,09 111,28 111,41 111,62 111,76 111,89 112,04 112,12 112,3 112,47 112,59 112,78 112,73 112,99 113,1 113,33 113,38 113,68 113,65 113,81 113,88 114,02 114,25 114,28 114,38 114,73 114,97 115,05 115,29 115,37 115,54 115,76 115,92 116,02 116,21 116,26 116,51

Text written by user:

Output produced by software:

Summary of compuational 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 109.832261904762 0.43756751306608 251.006435864391 Geometric Mean 109.759854264147 Harmonic Mean 109.687424863131 Quadratic Mean 109.904583059038 Winsorized Mean ( 1 / 28 ) 109.830476190476 0.436827210902427 251.427734924253 Winsorized Mean ( 2 / 28 ) 109.831666666667 0.436217173713911 251.782078480703 Winsorized Mean ( 3 / 28 ) 109.832023809524 0.433862979411983 253.149102415652 Winsorized Mean ( 4 / 28 ) 109.827261904762 0.433050241321512 253.613210258489 Winsorized Mean ( 5 / 28 ) 109.823690476190 0.430492579004991 255.111692587196 Winsorized Mean ( 6 / 28 ) 109.815119047619 0.426778936773391 257.311478110571 Winsorized Mean ( 7 / 28 ) 109.809285714286 0.423198649040215 259.474565817555 Winsorized Mean ( 8 / 28 ) 109.811190476190 0.420512364198862 261.136650964822 Winsorized Mean ( 9 / 28 ) 109.796190476190 0.414877543980382 264.647224390102 Winsorized Mean ( 10 / 28 ) 109.810476190476 0.409808769221808 267.955408565310 Winsorized Mean ( 11 / 28 ) 109.779047619048 0.405110873494543 270.985191466420 Winsorized Mean ( 12 / 28 ) 109.757619047619 0.393607942311079 278.850112635366 Winsorized Mean ( 13 / 28 ) 109.757619047619 0.389139075758900 282.052422603846 Winsorized Mean ( 14 / 28 ) 109.785952380952 0.383582365130362 286.212199415479 Winsorized Mean ( 15 / 28 ) 109.762738095238 0.375330542835604 292.442861873127 Winsorized Mean ( 16 / 28 ) 109.755119047619 0.368993704304866 297.444421861839 Winsorized Mean ( 17 / 28 ) 109.761190476190 0.36422563054688 301.354932961158 Winsorized Mean ( 18 / 28 ) 109.776190476190 0.354522454200676 309.645240168771 Winsorized Mean ( 19 / 28 ) 109.792023809524 0.350503726513055 313.24067479047 Winsorized Mean ( 20 / 28 ) 109.751547619048 0.338827984612908 323.915239009649 Winsorized Mean ( 21 / 28 ) 109.764047619048 0.333806911966198 328.824969418736 Winsorized Mean ( 22 / 28 ) 109.73 0.322583384818007 340.160111042007 Winsorized Mean ( 23 / 28 ) 109.727261904762 0.315106387301405 348.2229060619 Winsorized Mean ( 24 / 28 ) 109.781547619048 0.292452167119687 375.382917145966 Winsorized Mean ( 25 / 28 ) 109.826190476190 0.282874805551255 388.250166932208 Winsorized Mean ( 26 / 28 ) 109.844761904762 0.269610941094681 407.419526295065 Winsorized Mean ( 27 / 28 ) 109.838333333333 0.260824074317066 421.120380167861 Winsorized Mean ( 28 / 28 ) 109.848333333333 0.245585688250506 447.291265691688 Trimmed Mean ( 1 / 28 ) 109.826829268293 0.434069379683785 253.016762777186 Trimmed Mean ( 2 / 28 ) 109.823 0.430729378459787 254.969838353511 Trimmed Mean ( 3 / 28 ) 109.818333333333 0.427077142528005 257.139337130720 Trimmed Mean ( 4 / 28 ) 109.813289473684 0.423674005271013 259.192889125779 Trimmed Mean ( 5 / 28 ) 109.809324324324 0.419812167369169 261.567750673986 Trimmed Mean ( 6 / 28 ) 109.805972222222 0.415856708522973 264.047615372679 Trimmed Mean ( 7 / 28 ) 109.804142857143 0.411970646246581 266.533899581332 Trimmed Mean ( 8 / 28 ) 109.803235294118 0.408016758485835 269.114522897543 Trimmed Mean ( 9 / 28 ) 109.801969696970 0.403704478894623 271.986008175131 Trimmed Mean ( 10 / 28 ) 109.8028125 0.399503627332078 274.848098960385 Trimmed Mean ( 11 / 28 ) 109.801774193548 0.395232463722819 277.815676271354 Trimmed Mean ( 12 / 28 ) 109.804666666667 0.390734963467672 281.020837480676 Trimmed Mean ( 13 / 28 ) 109.810344827586 0.387131942998262 283.650953670024 Trimmed Mean ( 14 / 28 ) 109.816428571429 0.383234137900958 286.551790957123 Trimmed Mean ( 15 / 28 ) 109.819814814815 0.379131606482886 289.661460392573 Trimmed Mean ( 16 / 28 ) 109.825961538462 0.375189168939947 292.721567226373 Trimmed Mean ( 17 / 28 ) 109.8334 0.371036453459655 296.01781435727 Trimmed Mean ( 18 / 28 ) 109.840833333333 0.366295165604398 299.869732520473 Trimmed Mean ( 19 / 28 ) 109.847391304348 0.361695341784838 303.701426626867 Trimmed Mean ( 20 / 28 ) 109.852954545455 0.356131816871073 308.461500324818 Trimmed Mean ( 21 / 28 ) 109.863095238095 0.350784666816146 313.192410133699 Trimmed Mean ( 22 / 28 ) 109.873 0.344317459360563 319.103771862301 Trimmed Mean ( 23 / 28 ) 109.887368421053 0.337643217431444 325.454096951805 Trimmed Mean ( 24 / 28 ) 109.903611111111 0.329809505570605 333.233606839095 Trimmed Mean ( 25 / 28 ) 109.916176470588 0.324109644171381 339.13269304775 Trimmed Mean ( 26 / 28 ) 109.925625 0.317868067548371 345.821541143866 Trimmed Mean ( 27 / 28 ) 109.934333333333 0.311782669419247 352.599243370731 Trimmed Mean ( 28 / 28 ) 109.945 0.304518659127177 361.045199381636 Median 110.105 Midrange 110.055 Midmean - Weighted Average at Xnp 109.770930232558 Midmean - Weighted Average at X(n+1)p 109.863095238095 Midmean - Empirical Distribution Function 109.770930232558 Midmean - Empirical Distribution Function - Averaging 109.863095238095 Midmean - Empirical Distribution Function - Interpolation 109.863095238095 Midmean - Closest Observation 109.770930232558 Midmean - True Basic - Statistics Graphics Toolkit 109.863095238095 Midmean - MS Excel (old versions) 109.852954545455 Number of observations 84

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Apr/15/t12082580609j0rdaf2ejwlhpj/16b4n1208257977.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Apr/15/t12082580609j0rdaf2ejwlhpj/16b4n1208257977.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Apr/15/t12082580609j0rdaf2ejwlhpj/2vvvi1208257977.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Apr/15/t12082580609j0rdaf2ejwlhpj/2vvvi1208257977.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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