Central tendency - bouwvergunningen voor woningen in Vlaanderen

*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: Mon, 20 Oct 2008 10:23:45 -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/Oct/20/t12245199632zf64ym7lcds1qf.htm/, Retrieved Mon, 20 Oct 2008 16:26:03 +0000

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/2008/Oct/20/t12245199632zf64ym7lcds1qf.htm/}, year = {2008}, } @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 = {2008}, note = {{ISBN} 3-900051-07-0}, url = {http://www.R-project.org}, }

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Dataseries X:

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2319 2383 2513 2553 2341 2540 2371 2122 2301 2512 3145 2741 2548 1987 2281 2016 2434 2637 1831 1851 1839 2609 2417 2394 2372 2717 2998 2538 3007 2475 2175 2465 2279 2323 2746 2601 2486 2718 2646 2551 2712 2606 2365 3533 3509 2912 3599 2719 2869 4085 2686 2545 3071 3388 2652 3190 2884 3295 3818 3226 3953 3810 2877 3515 3708 3450 3360 4110 4384 3729 4263 3505 3674 3911 2951 3317 3417 3498 2768 2899 3171 3004 3481 3016 2595 3509 2833 3125 2556 3628 2876 2575 2903 3438 2926 3068 3015

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 3 seconds R Server 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 Central Tendency - Ungrouped Data Measure Value S.E. Value/S.E. Arithmetic Mean 2909.9381443299 57.7515337533662 50.3872010872834 Geometric Mean 2856.07522932221 Harmonic Mean 2803.32014609952 Quadratic Mean 2964.44311976285 Winsorized Mean ( 1 / 32 ) 2908.77319587629 57.4163995297153 50.6610170561266 Winsorized Mean ( 2 / 32 ) 2905.86597938144 56.6312388536885 51.3120680070056 Winsorized Mean ( 3 / 32 ) 2909.29896907217 55.689329023092 52.2415877531188 Winsorized Mean ( 4 / 32 ) 2905.05154639175 54.3383296997274 53.4622901080143 Winsorized Mean ( 5 / 32 ) 2908.35051546392 53.0193649404154 54.854495498624 Winsorized Mean ( 6 / 32 ) 2905.87628865979 51.4247236562446 56.5073778146969 Winsorized Mean ( 7 / 32 ) 2912.80412371134 50.2686033488174 57.9447991323568 Winsorized Mean ( 8 / 32 ) 2906.28865979381 49.0416642041539 59.2616239060592 Winsorized Mean ( 9 / 32 ) 2906.19587628866 48.4595489704640 59.9715832695838 Winsorized Mean ( 10 / 32 ) 2904.54639175258 47.6229057873534 60.9905326802612 Winsorized Mean ( 11 / 32 ) 2899.78350515464 46.7019048661619 62.0913325369667 Winsorized Mean ( 12 / 32 ) 2898.42268041237 45.8406300854906 63.2282469723246 Winsorized Mean ( 13 / 32 ) 2892.79381443299 44.0620509485644 65.6527272824834 Winsorized Mean ( 14 / 32 ) 2891.0618556701 43.5637686167021 66.3639062338075 Winsorized Mean ( 15 / 32 ) 2890.28865979381 43.4064418280762 66.5866294971065 Winsorized Mean ( 16 / 32 ) 2892.10309278350 43.1821853892883 66.9744494566715 Winsorized Mean ( 17 / 32 ) 2893.32989690722 42.8424868247656 67.5341258489853 Winsorized Mean ( 18 / 32 ) 2896.29896907217 42.1372995263352 68.7348026956976 Winsorized Mean ( 19 / 32 ) 2896.29896907217 41.2521429333733 70.2096609562806 Winsorized Mean ( 20 / 32 ) 2896.29896907217 39.5783678336478 73.1788380270158 Winsorized Mean ( 21 / 32 ) 2895.86597938144 38.9560551519768 74.3367357932927 Winsorized Mean ( 22 / 32 ) 2893.59793814433 37.9891993258562 76.168963534193 Winsorized Mean ( 23 / 32 ) 2892.88659793814 36.326160887694 79.636452827531 Winsorized Mean ( 24 / 32 ) 2886.20618556701 35.3231551167521 81.7086179314207 Winsorized Mean ( 25 / 32 ) 2881.56701030928 33.0855521359551 87.0944211076893 Winsorized Mean ( 26 / 32 ) 2876.20618556701 32.2239963431461 89.2566569006195 Winsorized Mean ( 27 / 32 ) 2858.39175257732 29.5235052430164 96.8174926740265 Winsorized Mean ( 28 / 32 ) 2848.86597938144 28.0958511755522 101.398101861402 Winsorized Mean ( 29 / 32 ) 2844.08247422680 27.2818340414415 104.248214027935 Winsorized Mean ( 30 / 32 ) 2836.65979381443 26.217767342799 108.196085376948 Winsorized Mean ( 31 / 32 ) 2831.22680412371 25.3318079712710 111.765682391664 Winsorized Mean ( 32 / 32 ) 2819.68041237113 22.5078525166733 125.275408228412 Trimmed Mean ( 1 / 32 ) 2905.77894736842 55.7139775686207 52.1552952091688 Trimmed Mean ( 2 / 32 ) 2902.65591397849 53.7710340126541 53.9817760115121 Trimmed Mean ( 3 / 32 ) 2900.94505494505 52.033429103162 55.7515640415244 Trimmed Mean ( 4 / 32 ) 2897.91011235955 50.4526766820595 57.4381837186057 Trimmed Mean ( 5 / 32 ) 2895.91954022989 49.1097114420685 58.9683680720872 Trimmed Mean ( 6 / 32 ) 2893.08235294118 47.9477896832411 60.3381797587299 Trimmed Mean ( 7 / 32 ) 2893.08235294118 47.0136094117651 61.5371248695742 Trimmed Mean ( 8 / 32 ) 2886.79012345679 46.1857418676705 62.5039245169624 Trimmed Mean ( 9 / 32 ) 2883.79746835443 45.4799297669021 63.4081337226054 Trimmed Mean ( 10 / 32 ) 2880.66233766234 44.7631978972029 64.3533633204151 Trimmed Mean ( 11 / 32 ) 2877.57333333333 44.0727170343148 65.2914893150986 Trimmed Mean ( 12 / 32 ) 2874.89041095890 43.4200202547257 66.2111715769181 Trimmed Mean ( 13 / 32 ) 2872.21126760563 42.7882433480278 67.1261786618315 Trimmed Mean ( 14 / 32 ) 2872.21126760563 42.3242995346293 67.861991791633 Trimmed Mean ( 15 / 32 ) 2867.80597014925 41.8361054478528 68.5485883413281 Trimmed Mean ( 16 / 32 ) 2865.56923076923 41.2612745036873 69.4493629980612 Trimmed Mean ( 17 / 32 ) 2863.01587301587 40.5892434406485 70.5363202248968 Trimmed Mean ( 18 / 32 ) 2860.18032786885 39.8167695963787 71.8335605038382 Trimmed Mean ( 19 / 32 ) 2856.88135593220 38.9765630003861 73.2974160883274 Trimmed Mean ( 20 / 32 ) 2853.35087719298 38.0835752494036 74.9233983024655 Trimmed Mean ( 21 / 32 ) 2849.56363636364 37.2540171484166 76.4901037386447 Trimmed Mean ( 22 / 32 ) 2845.52830188679 36.3148784193301 78.3570928981037 Trimmed Mean ( 23 / 32 ) 2841.37254901961 35.3015576036327 80.4885886600997 Trimmed Mean ( 24 / 32 ) 2836.93877551020 34.3152081494913 82.6729292490759 Trimmed Mean ( 25 / 32 ) 2836.93877551020 33.2497197291383 85.3221861303107 Trimmed Mean ( 26 / 32 ) 2828.48888888889 32.3178129295239 87.5210489972522 Trimmed Mean ( 27 / 32 ) 2824.3488372093 31.2741403320947 90.309399625954 Trimmed Mean ( 28 / 32 ) 2824.3488372093 30.5106290175376 92.5693415099984 Trimmed Mean ( 29 / 32 ) 2818.92307692308 29.7971184066161 94.603882108854 Trimmed Mean ( 30 / 32 ) 2816.64864864865 28.9958114458921 97.1398456602836 Trimmed Mean ( 31 / 32 ) 2816.64864864865 28.1419511008868 100.087184380044 Trimmed Mean ( 32 / 32 ) 2813.24242424242 27.1632630665464 103.567911460061 Median 2833 Midrange 3107.5 Midmean - Weighted Average at Xnp 2826.04166666667 Midmean - Weighted Average at X(n+1)p 2836.93877551020 Midmean - Empirical Distribution Function 2836.93877551020 Midmean - Empirical Distribution Function - Averaging 2836.93877551020 Midmean - Empirical Distribution Function - Interpolation 2836.93877551020 Midmean - Closest Observation 2830.44 Midmean - True Basic - Statistics Graphics Toolkit 2836.93877551020 Midmean - MS Excel (old versions) 2836.93877551020 Number of observations 97

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Oct/20/t12245199632zf64ym7lcds1qf/113j81224519819.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Oct/20/t12245199632zf64ym7lcds1qf/113j81224519819.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Oct/20/t12245199632zf64ym7lcds1qf/2dyz21224519819.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Oct/20/t12245199632zf64ym7lcds1qf/2dyz21224519819.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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FreeStatistics.org is safe. There is no need to download any software to use the applications and services contained in this website. Hence, your system's security is not compromised by their use, and your personal data - other than data you submit in the account application form, and the user-agent information that is transmitted by your browser - is never transmitted to our servers.

As a general rule, we do not log on-line behavior of individuals (other than normal logging of webserver 'hits'). However, in cases of abuse, hacking, unauthorized access, Denial of Service attacks, illegal copying, hotlinking, non-compliance with international webstandards (such as robots.txt), or any other harmful behavior, our system engineers are empowered to log, track, identify, publish, and ban misbehaving individuals - even if this leads to ban entire blocks of IP addresses, or disclosing user's identity.

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