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

Title produced by software: Central Tendency

Date of computation: Mon, 03 Dec 2007 02:03:03 -0700

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2007/Dec/03/t11966719622xksulwo25stdto.htm/, Retrieved Mon, 03 Dec 2007 09:52:47 +0100

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ex012008

Dataseries X:

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122302.01 109264.65 103674.75 103890.3 75512.66 83121.3 125096.81 74206.73 88481.63 111598.17 146919.48 150790.85 113780.5 110870.76 118785.32 112820.5 102188.92 97092.73 114067.82 89690.15 89267.9 96198.64 129599.75 169424.7 152510.91 121850.2 144737.64 121381.88 106894.86 94305.06 116800.42 77584.28 100680.88 106634.05 168390.77 211971.89 136163.28 168950.25 89816.88 85406.93 66055.52 73311.68 85674.51 82822.59 94277.63 100991.65 149245.88 208517.17 40733.51 121352.23 104020.11 99566.82 101352.17 106628.41 109696.95 248696.37 105628.33 120449.17 136547.7 140896.42 131509.91 95450.31 133592.64 110332.9 88110.54 64931.25 98446.22 84212.38 77519.55 124806.02 102185.94 151348.79 124378.28 101433.13 126724.22 87461.88 95288.27 129055.33 107753.06 96364.03 71662.75 125666.24 456841.51 167642.32 167154.73 139685.18 119275.2 122746.05 107337.43 112584.89 133183.08 121152.57 119815.6 122858.44 152077.17 157221.96 140435.08 101455.09 104791.29 77226.59 84477.43 66227.74 89076.23 108924.43 83926.11 91764.8 120892.76 129952.42 135865.14 105512.77 96486.62 78064.88 92370.22 98454.46 96703.93 83170.95

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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 115972.247758621 4137.24876571305 28.0312483792917 Geometric Mean 110454.863836818 Harmonic Mean 106012.699646020 Quadratic Mean 124169.228858712 Winsorized Mean ( 1 / 38 ) 114386.494310345 3078.37327431317 37.1580975136507 Winsorized Mean ( 2 / 38 ) 113772.697586207 2860.03966660323 39.7801117637403 Winsorized Mean ( 3 / 38 ) 113687.805344828 2833.04998853622 40.1291208432111 Winsorized Mean ( 4 / 38 ) 112527.203275862 2470.56810161295 45.547096314567 Winsorized Mean ( 5 / 38 ) 112577.827413793 2456.42831745827 45.8298850463832 Winsorized Mean ( 6 / 38 ) 112595.184482759 2444.28979331071 46.0645807182512 Winsorized Mean ( 7 / 38 ) 112628.825517241 2424.72521155174 46.4501399913943 Winsorized Mean ( 8 / 38 ) 112713.400689655 2402.63654525605 46.9123808643488 Winsorized Mean ( 9 / 38 ) 111965.484396552 2256.26647323696 49.6242291079742 Winsorized Mean ( 10 / 38 ) 111564.939568966 2187.00532833955 51.0126510087973 Winsorized Mean ( 11 / 38 ) 111569.383189655 2174.19310755665 51.3153053433401 Winsorized Mean ( 12 / 38 ) 111986.210431034 2099.18471703610 53.3474779623734 Winsorized Mean ( 13 / 38 ) 111957.158793103 2084.98829035771 53.6967806058497 Winsorized Mean ( 14 / 38 ) 111776.689137931 2054.37703587042 54.4090433188533 Winsorized Mean ( 15 / 38 ) 111573.511551724 1995.55058944927 55.9111415875035 Winsorized Mean ( 16 / 38 ) 111312.053620690 1945.1108885282 57.2265850122898 Winsorized Mean ( 17 / 38 ) 110787.959741379 1858.60431371165 59.6081473200365 Winsorized Mean ( 18 / 38 ) 110860.605258621 1830.93826899463 60.5485215618408 Winsorized Mean ( 19 / 38 ) 110781.604568966 1808.48191269672 61.2566837363463 Winsorized Mean ( 20 / 38 ) 110548.826982759 1698.00078080987 65.1052863061887 Winsorized Mean ( 21 / 38 ) 110596.663534483 1674.95234400631 66.0297374610355 Winsorized Mean ( 22 / 38 ) 110610.498879310 1659.26889193512 66.6621904484156 Winsorized Mean ( 23 / 38 ) 110277.811810345 1586.96309592679 69.4898401187724 Winsorized Mean ( 24 / 38 ) 110232.731120690 1571.56656203982 70.141942303489 Winsorized Mean ( 25 / 38 ) 109963.136293103 1515.80430471088 72.544414837295 Winsorized Mean ( 26 / 38 ) 109642.448706897 1469.93147001950 74.5901771226395 Winsorized Mean ( 27 / 38 ) 110013.756896552 1407.87408377055 78.1417586734137 Winsorized Mean ( 28 / 38 ) 110028.481034483 1375.62972999268 79.9840819339287 Winsorized Mean ( 29 / 38 ) 109922.556034483 1254.07271652457 87.6524579365008 Winsorized Mean ( 30 / 38 ) 109656.034482759 1221.76847240409 89.7518940450203 Winsorized Mean ( 31 / 38 ) 109766.613620690 1176.04929938357 93.3350444392289 Winsorized Mean ( 32 / 38 ) 109731.096379310 1162.19801505457 94.4168678296684 Winsorized Mean ( 33 / 38 ) 109822.298706897 1125.91939801789 97.5401071339844 Winsorized Mean ( 34 / 38 ) 109425.304741379 1071.45961431882 102.127325453089 Winsorized Mean ( 35 / 38 ) 109428.382327586 1063.84865651350 102.860854932327 Winsorized Mean ( 36 / 38 ) 109358.017844828 1041.77437941983 104.972842493717 Winsorized Mean ( 37 / 38 ) 109337.919827586 1013.18434850482 107.915129155853 Winsorized Mean ( 38 / 38 ) 109627.889310345 950.708963273342 115.311723719202 Trimmed Mean ( 1 / 38 ) 113642.155438596 2866.73975666263 39.6416016397998 Trimmed Mean ( 2 / 38 ) 112871.233035714 2617.69075571998 43.118627664126 Trimmed Mean ( 3 / 38 ) 112395.915363636 2470.00945909506 45.5042449128170 Trimmed Mean ( 4 / 38 ) 111933.386851852 2311.73153222280 48.419717121834 Trimmed Mean ( 5 / 38 ) 111770.927641509 2259.5843108317 49.4652609799583 Trimmed Mean ( 6 / 38 ) 111590.926923077 2204.84562383085 50.6116735416566 Trimmed Mean ( 7 / 38 ) 111400.577450980 2146.07367751008 51.9090181378255 Trimmed Mean ( 8 / 38 ) 111197.0392 2083.89699575767 53.3601418046916 Trimmed Mean ( 9 / 38 ) 110972.679591837 2017.74727874722 54.9983046740808 Trimmed Mean ( 10 / 38 ) 110839.386354167 1971.3408011445 56.2253803552469 Trimmed Mean ( 11 / 38 ) 110749.85 1931.05932434804 57.3518630958637 Trimmed Mean ( 12 / 38 ) 110655.911413043 1887.34833607800 58.6303594825487 Trimmed Mean ( 13 / 38 ) 110513.027444444 1849.15959290781 59.7639207931546 Trimmed Mean ( 14 / 38 ) 110366.594545455 1807.58108490603 61.0576175348683 Trimmed Mean ( 15 / 38 ) 110230.738255814 1764.60245853614 62.467746048171 Trimmed Mean ( 16 / 38 ) 110107.117857143 1724.03101653657 63.8660887194121 Trimmed Mean ( 17 / 38 ) 110000.583902439 1684.72670020200 65.2928358583323 Trimmed Mean ( 18 / 38 ) 109933.425375 1651.89144726551 66.5500300016567 Trimmed Mean ( 19 / 38 ) 109856.820769231 1617.48855658414 67.9181440400602 Trimmed Mean ( 20 / 38 ) 109782.530657895 1580.49394818156 69.4608990968964 Trimmed Mean ( 21 / 38 ) 109722.469594595 1552.69800818333 70.6656858038805 Trimmed Mean ( 22 / 38 ) 109655.401805556 1522.97287530950 72.000889564938 Trimmed Mean ( 23 / 38 ) 109583.459428571 1489.88088516023 73.551825867466 Trimmed Mean ( 24 / 38 ) 109531.960147059 1460.94917268874 74.97314909695 Trimmed Mean ( 25 / 38 ) 109480.641060606 1428.48311626579 76.6411865943509 Trimmed Mean ( 26 / 38 ) 109445.66015625 1397.7189712622 78.3030511901944 Trimmed Mean ( 27 / 38 ) 109431.499193548 1367.36539028332 80.0309119794777 Trimmed Mean ( 28 / 38 ) 109389.806666667 1339.55316956504 81.6614145313743 Trimmed Mean ( 29 / 38 ) 109344.187068966 1310.25847884279 83.4523789272 Trimmed Mean ( 30 / 38 ) 109302.875 1292.64947780043 84.557242220056 Trimmed Mean ( 31 / 38 ) 109302.875 1275.16934520199 85.7163602711025 Trimmed Mean ( 32 / 38 ) 109242.396538462 1259.61782981138 86.7266197357814 Trimmed Mean ( 33 / 38 ) 109206.9658 1241.33745111581 87.9752445250372 Trimmed Mean ( 34 / 38 ) 109161.903541667 1223.25428362382 89.2389301252071 Trimmed Mean ( 35 / 38 ) 109142.367391304 1208.73825641257 90.2944593771931 Trimmed Mean ( 36 / 38 ) 109120.823409091 1189.96890277217 91.7005672626248 Trimmed Mean ( 37 / 38 ) 109102.625952381 1168.49475379904 93.3702317427306 Trimmed Mean ( 38 / 38 ) 109084.184 1144.78541631524 95.2878875336421 Median 107545.245 Midrange 248787.51 Midmean - Weighted Average at Xnp 109056.492711864 Midmean - Weighted Average at X(n+1)p 109344.187068966 Midmean - Empirical Distribution Function 109056.492711864 Midmean - Empirical Distribution Function - Averaging 109344.187068966 Midmean - Empirical Distribution Function - Interpolation 109344.187068966 Midmean - Closest Observation 109056.492711864 Midmean - True Basic - Statistics Graphics Toolkit 109344.187068966 Midmean - MS Excel (old versions) 109389.806666667 Number of observations 116

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Dec/03/t11966719622xksulwo25stdto/1mjl21196672580.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Dec/03/t11966719622xksulwo25stdto/1mjl21196672580.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Dec/03/t11966719622xksulwo25stdto/2h0y21196672580.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Dec/03/t11966719622xksulwo25stdto/2h0y21196672580.ps (open in new window)

Parameters:

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

Disclaimer

Information provided on this web site is provided "AS IS" without warranty of any kind, either express or implied, including, without limitation, warranties of merchantability, fitness for a particular purpose, and noninfringement. We use reasonable efforts to include accurate and timely information and periodically update the information, and software without notice. However, we make no warranties or representations as to the accuracy or completeness of such information (or software), and we assume no liability or responsibility for errors or omissions in the content of this web site, or any software bugs in online applications. Your use of this web site is AT YOUR OWN RISK. Under no circumstances and under no legal theory shall we be liable to you or any other person for any direct, indirect, special, incidental, exemplary, or consequential damages arising from your access to, or use of, this web site.

Privacy Policy

We may request personal information to be submitted to our servers in order to be able to:

• personalize online software applications according to your needs
• enforce strict security rules with respect to the data that you upload (e.g. statistical data)
• manage user sessions of online applications
• alert you about important changes or upgrades in resources or applications

We NEVER allow other companies to directly offer registered users information about their products and services. Banner references and hyperlinks of third parties NEVER contain any personal data of the visitor.

We do NOT sell, nor transmit by any means, personal information, nor statistical data series uploaded by you to third parties.

We carefully protect your data from loss, misuse, alteration, and destruction. However, at any time, and under any circumstance you are solely responsible for managing your passwords, and keeping them secret.

We store a unique ANONYMOUS USER ID in the form of a small 'Cookie' on your computer. This allows us to track your progress when using this website which is necessary to create state-dependent features. The cookie is used for NO OTHER PURPOSE. At any time you may opt to disallow cookies from this website - this will not affect other features of this website.

We examine cookies that are used by third-parties (banner and online ads) very closely: abuse from third-parties automatically results in termination of the advertising contract without refund. We have very good reason to believe that the cookies that are produced by third parties (banner ads) do NOT cause any privacy or security risk.

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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