Central Tendency: bouwvergunningen woongebouwen

*Unverified author*

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 16:35:59 -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/Oct/21/t1224542204abmxb3dk1yi3nd9.htm/, Retrieved Mon, 20 Oct 2008 22:36:46 +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/21/t1224542204abmxb3dk1yi3nd9.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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IsPrivate?

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User-defined keywords:

Dataseries X:

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2173 2363 2126 1905 2121 1983 1734 2074 2049 2406 2558 2251 2059 2397 1747 1707 2319 1631 1627 1791 2034 1997 2169 2028 2253 2218 1855 2187 1852 1570 1851 1954 1828 2251 2277 2085 2282 2266 1878 2267 2069 1746 2299 2360 2214 2825 2355 2333 3016 2155 2172 2150 2533 2058 2160 2259 2498 2695 2799 2945 2930 2318 2540 2570 2669 2450 2842 3439 2677 2979 2257 2842 2546 2455 2293 2379 2478 2054 2272 2351 2271 2542 2304 2194 2722 2395 2146 1894 2548 2087 2063 2481 2476 2212 2834 2148 2598

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 2278.55670103093 34.886493564415 65.3134341754285 Geometric Mean 2253.35927816577 Harmonic Mean 2228.43405345994 Quadratic Mean 2304.05275838078 Winsorized Mean ( 1 / 32 ) 2274.78350515464 33.5019657152805 67.9000009876165 Winsorized Mean ( 2 / 32 ) 2274.10309278350 33.3133729472932 68.2639700393436 Winsorized Mean ( 3 / 32 ) 2275.40206185567 32.6352876098618 69.7221390862842 Winsorized Mean ( 4 / 32 ) 2275.89690721650 32.3056623074879 70.4488546173213 Winsorized Mean ( 5 / 32 ) 2271.9793814433 31.2879253694158 72.6152135246455 Winsorized Mean ( 6 / 32 ) 2272.0412371134 31.2771013668999 72.6423209894339 Winsorized Mean ( 7 / 32 ) 2274.63917525773 30.6284658098040 74.2655276755532 Winsorized Mean ( 8 / 32 ) 2276.94845360825 29.9982723268776 75.9026529527223 Winsorized Mean ( 9 / 32 ) 2276.67010309278 29.2156916955211 77.9262776599537 Winsorized Mean ( 10 / 32 ) 2268.83505154639 27.7846934935124 81.6577318758674 Winsorized Mean ( 11 / 32 ) 2266.11340206186 27.2198944495027 83.2521010052359 Winsorized Mean ( 12 / 32 ) 2266.73195876289 26.414976241067 85.8123792380639 Winsorized Mean ( 13 / 32 ) 2267.80412371134 25.9163198691808 87.5048670165616 Winsorized Mean ( 14 / 32 ) 2259.14432989691 24.0960767974746 93.7556909734649 Winsorized Mean ( 15 / 32 ) 2262.39175257732 22.3420936524757 101.261403150847 Winsorized Mean ( 16 / 32 ) 2265.19587628866 21.3860142698932 105.919497092900 Winsorized Mean ( 17 / 32 ) 2265.89690721650 20.8033899137155 108.91959996013 Winsorized Mean ( 18 / 32 ) 2271.27835051546 19.9984360549818 113.572798606402 Winsorized Mean ( 19 / 32 ) 2271.67010309278 19.7383155312359 115.089360056985 Winsorized Mean ( 20 / 32 ) 2274.35051546392 19.2971988047230 117.859101648850 Winsorized Mean ( 21 / 32 ) 2273.91752577320 18.9493450622112 119.999795154285 Winsorized Mean ( 22 / 32 ) 2266.88659793814 17.7339109375522 127.82778744749 Winsorized Mean ( 23 / 32 ) 2263.09278350515 17.1644316919623 131.847813205777 Winsorized Mean ( 24 / 32 ) 2263.34020618557 16.9441350548586 133.576615085853 Winsorized Mean ( 25 / 32 ) 2264.37113402062 16.6865387517246 135.700468965536 Winsorized Mean ( 26 / 32 ) 2260.08247422680 15.7885354009817 143.147063158643 Winsorized Mean ( 27 / 32 ) 2261.75257731959 15.2364879503716 148.443170413456 Winsorized Mean ( 28 / 32 ) 2249.62886597938 13.5836573622170 165.612898352157 Winsorized Mean ( 29 / 32 ) 2257.10309278350 12.0241692147167 187.713849703726 Winsorized Mean ( 30 / 32 ) 2258.03092783505 11.7676482730433 191.884637902343 Winsorized Mean ( 31 / 32 ) 2259.30927835052 10.4149760912476 216.928897249141 Winsorized Mean ( 32 / 32 ) 2254.69072164948 9.71718153661973 232.031347068341 Trimmed Mean ( 1 / 32 ) 2273.8 32.5863504425146 69.777682039331 Trimmed Mean ( 2 / 32 ) 2272.77419354839 31.5435691957101 72.0519031770661 Trimmed Mean ( 3 / 32 ) 2272.06593406593 30.467496250349 74.5734377185623 Trimmed Mean ( 4 / 32 ) 2270.85393258427 29.5312525999666 76.896634333311 Trimmed Mean ( 5 / 32 ) 2269.44827586207 28.5705734752339 79.4330669571374 Trimmed Mean ( 6 / 32 ) 2268.87058823529 27.7684190177219 81.7068694759789 Trimmed Mean ( 7 / 32 ) 2268.87058823529 26.8447766705403 84.518139825882 Trimmed Mean ( 8 / 32 ) 2267.16049382716 25.9294892466 87.4356016914002 Trimmed Mean ( 9 / 32 ) 2265.6582278481 25.0041469204294 90.611298800079 Trimmed Mean ( 10 / 32 ) 2264.11688311688 24.0895385895044 93.9875570760555 Trimmed Mean ( 11 / 32 ) 2263.50666666667 23.3130854747791 97.0916813699075 Trimmed Mean ( 12 / 32 ) 2263.19178082192 22.5105814585175 100.539019171607 Trimmed Mean ( 13 / 32 ) 2262.78873239437 21.7157965804602 104.200125655552 Trimmed Mean ( 14 / 32 ) 2262.78873239437 20.8652295214447 108.447823690065 Trimmed Mean ( 15 / 32 ) 2262.56716417910 20.1887097147390 112.070914691853 Trimmed Mean ( 16 / 32 ) 2262.58461538462 19.6887303316137 114.917751285955 Trimmed Mean ( 17 / 32 ) 2262.33333333333 19.2483300025042 117.534005965141 Trimmed Mean ( 18 / 32 ) 2262 18.8113440951641 120.246591022781 Trimmed Mean ( 19 / 32 ) 2261.15254237288 18.4090925739868 122.828028230355 Trimmed Mean ( 20 / 32 ) 2260.21052631579 17.9561345351645 125.874002664075 Trimmed Mean ( 21 / 32 ) 2258.96363636364 17.4675835143045 129.323190841695 Trimmed Mean ( 22 / 32 ) 2257.66037735849 16.9199417602418 133.431923664389 Trimmed Mean ( 23 / 32 ) 2256.86274509804 16.4655319036130 137.065887595336 Trimmed Mean ( 24 / 32 ) 2256.32653061224 15.9976982760611 141.040697960193 Trimmed Mean ( 25 / 32 ) 2256.32653061224 15.4400066063258 146.135075466083 Trimmed Mean ( 26 / 32 ) 2254.97777777778 14.7708930571563 152.663604634607 Trimmed Mean ( 27 / 32 ) 2254.53488372093 14.1034129072957 159.857397534937 Trimmed Mean ( 28 / 32 ) 2254.53488372093 13.3494224264412 168.886324194474 Trimmed Mean ( 29 / 32 ) 2254.28205128205 12.7591595379943 176.679509694133 Trimmed Mean ( 30 / 32 ) 2254.02702702703 12.3490578166388 182.526234834694 Trimmed Mean ( 31 / 32 ) 2254.02702702703 11.8413846891545 190.351642666544 Trimmed Mean ( 32 / 32 ) 2253.12121212121 11.4956149063588 195.998320270358 Median 2259 Midrange 2504.5 Midmean - Weighted Average at Xnp 2251.70833333333 Midmean - Weighted Average at X(n+1)p 2256.32653061224 Midmean - Empirical Distribution Function 2256.32653061224 Midmean - Empirical Distribution Function - Averaging 2256.32653061224 Midmean - Empirical Distribution Function - Interpolation 2256.32653061224 Midmean - Closest Observation 2252.38 Midmean - True Basic - Statistics Graphics Toolkit 2256.32653061224 Midmean - MS Excel (old versions) 2256.32653061224 Number of observations 97

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Oct/21/t1224542204abmxb3dk1yi3nd9/1qxym1224542156.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Oct/21/t1224542204abmxb3dk1yi3nd9/1qxym1224542156.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Oct/21/t1224542204abmxb3dk1yi3nd9/2gt721224542156.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Oct/21/t1224542204abmxb3dk1yi3nd9/2gt721224542156.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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