Opgave 5 oef 2 stap1 - Sophie Berns - centrummaten

*Unverified author*

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

Title produced by software: Central Tendency

Date of computation: Mon, 04 Apr 2011 14:33:25 +0000

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2011/Apr/04/t1301927594uz3e8tklc331te2.htm/, Retrieved Mon, 04 Apr 2011 16:33:15 +0200

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords:

KDGP1W52

Dataseries X:

» Textbox « » Textfile « » CSV «

41 39 50 40 43 38 44 35 39 35 29 49 50 59 63 32 39 47 53 60 57 52 70 90 74 62 55 84 94 70 108 139 120 97 126 149 158 124 140 109 114 77 120 133 110 92 97 78 99 107 112 90 98 125 155 190 236 189 174 178 136 161 171 149 184 155 276 224 213 279 268 287 238 213 257 293 212 246 353 339 308 247 257 322 298 273 312 249 286 279 309 401 309 328 353 354 327 324 285 243 241 287 355 460 364 487 452 391 500 451 375 372 302 316 398 394 431 431

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' @ www.wessa.org Central Tendency - Ungrouped Data Measure Value S.E. Value/S.E. Arithmetic Mean 196.28813559322 11.7873690411105 16.6524128419693 Geometric Mean 150.591705333384 Harmonic Mean 109.547926428759 Quadratic Mean 234.062500707158 Winsorized Mean ( 1 / 39 ) 196.203389830508 11.760537233945 16.6831995790292 Winsorized Mean ( 2 / 39 ) 195.796610169492 11.6618265201796 16.7895320540642 Winsorized Mean ( 3 / 39 ) 195.593220338983 11.6229592738401 16.8281773798525 Winsorized Mean ( 4 / 39 ) 195.661016949153 11.6046668239998 16.860545840446 Winsorized Mean ( 5 / 39 ) 194.85593220339 11.4452970592849 17.0249781367898 Winsorized Mean ( 6 / 39 ) 194.85593220339 11.4452970592849 17.0249781367898 Winsorized Mean ( 7 / 39 ) 193.076271186441 11.1463091711311 17.3219913625317 Winsorized Mean ( 8 / 39 ) 192.940677966102 11.1060517464005 17.3725714927121 Winsorized Mean ( 9 / 39 ) 192.71186440678 11.0492628324344 17.4411512631491 Winsorized Mean ( 10 / 39 ) 192.627118644068 10.9900511856424 17.5274086890258 Winsorized Mean ( 11 / 39 ) 191.228813559322 10.7551429673773 17.7802205083987 Winsorized Mean ( 12 / 39 ) 191.228813559322 10.6753238650127 17.9131627271801 Winsorized Mean ( 13 / 39 ) 190.567796610169 10.5240732351187 18.1077984115738 Winsorized Mean ( 14 / 39 ) 189.618644067797 10.3623746863219 18.2987635370962 Winsorized Mean ( 15 / 39 ) 189.491525423729 10.3450659288286 18.3170921023975 Winsorized Mean ( 16 / 39 ) 189.627118644068 10.2955372514916 18.4183801206289 Winsorized Mean ( 17 / 39 ) 189.771186440678 10.2791151031414 18.461821327663 Winsorized Mean ( 18 / 39 ) 187.940677966102 9.96093552197611 18.8677737699899 Winsorized Mean ( 19 / 39 ) 186.491525423729 9.69891327400198 19.2280846477534 Winsorized Mean ( 20 / 39 ) 186.661016949153 9.63927258073447 19.3646372571954 Winsorized Mean ( 21 / 39 ) 186.305084745763 9.55303826663527 19.5021813527585 Winsorized Mean ( 22 / 39 ) 186.305084745763 9.46522802538023 19.6831058106789 Winsorized Mean ( 23 / 39 ) 185.330508474576 9.3014608760773 19.9248817947762 Winsorized Mean ( 24 / 39 ) 185.940677966102 9.04613613277877 20.5547070303689 Winsorized Mean ( 25 / 39 ) 185.305084745763 8.9708310009464 20.6564012549354 Winsorized Mean ( 26 / 39 ) 186.186440677966 8.87480281697605 20.9792199914371 Winsorized Mean ( 27 / 39 ) 186.64406779661 8.77400290418977 21.2723964004484 Winsorized Mean ( 28 / 39 ) 185.457627118644 8.58183707474953 21.6104810081188 Winsorized Mean ( 29 / 39 ) 185.949152542373 8.31192249418973 22.3713770998655 Winsorized Mean ( 30 / 39 ) 186.203389830508 8.007923420502 23.2523939169783 Winsorized Mean ( 31 / 39 ) 184.627118644068 7.82999500383805 23.5794682568212 Winsorized Mean ( 32 / 39 ) 185.169491525424 7.7742047480555 23.8184479990366 Winsorized Mean ( 33 / 39 ) 185.449152542373 7.68582717526531 24.128717483941 Winsorized Mean ( 34 / 39 ) 186.025423728814 7.56618832919755 24.5864120261123 Winsorized Mean ( 35 / 39 ) 184.245762711864 7.36888321746365 25.0032138214943 Winsorized Mean ( 36 / 39 ) 184.550847457627 7.33806885007538 25.1497841227984 Winsorized Mean ( 37 / 39 ) 183.923728813559 7.20333550609676 25.5331337347663 Winsorized Mean ( 38 / 39 ) 185.533898305085 6.84151080222696 27.1188489894209 Winsorized Mean ( 39 / 39 ) 184.21186440678 6.62950148764117 27.7866842250795 Trimmed Mean ( 1 / 39 ) 195.112068965517 11.6090990237265 16.8068226971577 Trimmed Mean ( 2 / 39 ) 193.982456140351 11.4399465620006 16.9565876107054 Trimmed Mean ( 3 / 39 ) 193.026785714286 11.3082288279293 17.0695861086171 Trimmed Mean ( 4 / 39 ) 192.109090909091 11.1761343596573 17.1892252479132 Trimmed Mean ( 5 / 39 ) 191.138888888889 11.0332693206782 17.3238668733176 Trimmed Mean ( 6 / 39 ) 190.311320754717 10.9149893490615 17.4357770464596 Trimmed Mean ( 7 / 39 ) 189.451923076923 10.7811576688706 17.5725027771316 Trimmed Mean ( 8 / 39 ) 188.852941176471 10.691790541589 17.6633596067815 Trimmed Mean ( 9 / 39 ) 188.25 10.5969823701625 17.7644911942146 Trimmed Mean ( 10 / 39 ) 187.65306122449 10.4982150310803 17.8747587726997 Trimmed Mean ( 11 / 39 ) 187.041666666667 10.3944666946168 17.9943495093918 Trimmed Mean ( 12 / 39 ) 186.563829787234 10.311767355179 18.0923233972627 Trimmed Mean ( 13 / 39 ) 186.065217391304 10.2271829447851 18.1932031915182 Trimmed Mean ( 14 / 39 ) 185.611111111111 10.1499702581244 18.2868625612515 Trimmed Mean ( 15 / 39 ) 185.227272727273 10.0813660430428 18.373231557751 Trimmed Mean ( 16 / 39 ) 184.837209302326 10.0022276652149 18.4796042930657 Trimmed Mean ( 17 / 39 ) 184.416666666667 9.914916414581 18.5999214673622 Trimmed Mean ( 18 / 39 ) 183.963414634146 9.81367279766193 18.7456234202117 Trimmed Mean ( 19 / 39 ) 183.6375 9.73544424278781 18.8627755878774 Trimmed Mean ( 20 / 39 ) 183.410256410256 9.674358828732 18.9583888356036 Trimmed Mean ( 21 / 39 ) 183.157894736842 9.60646808111787 19.066101421484 Trimmed Mean ( 22 / 39 ) 182.918918918919 9.53385512098253 19.1862490669008 Trimmed Mean ( 23 / 39 ) 182.666666666667 9.45545937805659 19.3186453839127 Trimmed Mean ( 24 / 39 ) 182.471428571429 9.37974385548132 19.4537752184774 Trimmed Mean ( 25 / 39 ) 182.220588235294 9.31722765432542 19.5573828391646 Trimmed Mean ( 26 / 39 ) 182 9.24718819482385 19.6816584853194 Trimmed Mean ( 27 / 39 ) 181.703125 9.169931228416 19.8151022591025 Trimmed Mean ( 28 / 39 ) 181.354838709677 9.08448205813148 19.9631456751403 Trimmed Mean ( 29 / 39 ) 181.066666666667 9.00216128056372 20.1136883714361 Trimmed Mean ( 30 / 39 ) 180.724137931034 8.93235291942846 20.2325344241546 Trimmed Mean ( 31 / 39 ) 180.339285714286 8.88107855805588 20.3060117682106 Trimmed Mean ( 32 / 39 ) 180.037037037037 8.83476563534995 20.3782470829409 Trimmed Mean ( 33 / 39 ) 179.673076923077 8.77465159844493 20.4763773133647 Trimmed Mean ( 34 / 39 ) 179.26 8.70223100646012 20.599315263744 Trimmed Mean ( 35 / 39 ) 178.770833333333 8.61860512151147 20.7424323092763 Trimmed Mean ( 36 / 39 ) 178.369565217391 8.53627432877418 20.8954818399101 Trimmed Mean ( 37 / 39 ) 177.909090909091 8.42331520797073 21.1210297271959 Trimmed Mean ( 38 / 39 ) 177.452380952381 8.29145358384438 21.4018421689221 Trimmed Mean ( 39 / 39 ) 176.825 8.17578409162207 21.6278950151334 Median 166 Midrange 264.5 Midmean - Weighted Average at Xnp 179.084745762712 Midmean - Weighted Average at X(n+1)p 181.066666666667 Midmean - Empirical Distribution Function 181.066666666667 Midmean - Empirical Distribution Function - Averaging 181.066666666667 Midmean - Empirical Distribution Function - Interpolation 180.724137931034 Midmean - Closest Observation 181.066666666667 Midmean - True Basic - Statistics Graphics Toolkit 181.066666666667 Midmean - MS Excel (old versions) 181.066666666667 Number of observations 118

Charts produced by software:

http://www.freestatistics.org/blog/date/2011/Apr/04/t1301927594uz3e8tklc331te2/10vqd1301927603.png (open in new window) http://www.freestatistics.org/blog/date/2011/Apr/04/t1301927594uz3e8tklc331te2/10vqd1301927603.ps (open in new window) http://www.freestatistics.org/blog/date/2011/Apr/04/t1301927594uz3e8tklc331te2/2k2qw1301927603.png (open in new window) http://www.freestatistics.org/blog/date/2011/Apr/04/t1301927594uz3e8tklc331te2/2k2qw1301927603.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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