ct bel 20

*Unverified author*

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

Title produced by software: Central Tendency

Date of computation: Mon, 28 Dec 2009 06:11:11 -0700

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2009/Dec/28/t1262006101rock4r86jrlnikr.htm/, Retrieved Mon, 28 Dec 2009 14:15:03 +0100

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/2009/Dec/28/t1262006101rock4r86jrlnikr.htm/}, year = {2009}, } @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 = {2009}, note = {{ISBN} 3-900051-07-0}, url = {http://www.R-project.org}, }

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords:

Dataseries X:

» Textbox « » Textfile « » CSV «

3032,93 3045,78 3110,52 3013,24 2987,1 2995,55 2833,18 2848,96 2794,83 2845,26 2915,02 2892,63 2604,42 2641,65 2659,81 2638,53 2720,25 2745,88 2735,7 2811,7 2799,43 2555,28 2304,98 2214,95 2065,81 1940,49 2042 1995,37 1946,81 1765,9 1635,25 1833,42 1910,43 1959,67 1969,6 2061,41 2093,48 2120,88 2174,56 2196,72 2350,44 2440,25 2408,64 2472,81 2407,6 2454,62 2448,05 2497,84 2645,64 2756,76 2849,27 2921,44 2981,85 3080,58 3106,22 3119,31 3061,26 3097,31 3161,69 3257,16 3277,01 3295,32 3363,99 3494,17 3667,03 3813,06 3917,96 3895,51 3801,06 3570,12 3701,61 3862,27 3970,1 4138,52 4199,75 4290,89 4443,91 4502,64 4356,98 4591,27 4696,96 4621,4 4562,84 4202,52 4296,49 4435,23 4105,18 4116,68 3844,49 3720,98 3674,4 3857,62 3801,06 3504,37 3032,6 3047,03 2962,34 2197,82 2014,45 1862,83 1905,41 1810,99 1670,07 1864,44 2052,02 2029,60 2070,83 2293,41 2443,27 2513,17 2466,92

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 2953.23162162162 77.2965527716302 38.2065113608214 Geometric Mean 2844.29285103833 Harmonic Mean 2739.55109411931 Quadratic Mean 3062.48270014500 Winsorized Mean ( 1 / 37 ) 2952.86459459460 77.1117625729395 38.2933095557439 Winsorized Mean ( 2 / 37 ) 2954.04837837838 76.7536494962933 38.487399592915 Winsorized Mean ( 3 / 37 ) 2954.49864864865 76.4370333323024 38.6527121716545 Winsorized Mean ( 4 / 37 ) 2953.13756756757 75.9191159475709 38.8984714944123 Winsorized Mean ( 5 / 37 ) 2951.81684684685 75.2592957094303 39.221956823029 Winsorized Mean ( 6 / 37 ) 2951.43468468468 75.1634673757229 39.2668777496815 Winsorized Mean ( 7 / 37 ) 2949.08369369369 73.9579469122907 39.875142791499 Winsorized Mean ( 8 / 37 ) 2945.08585585586 73.1681793271631 40.250910750249 Winsorized Mean ( 9 / 37 ) 2947.0690990991 72.7820655336912 40.4916936265691 Winsorized Mean ( 10 / 37 ) 2939.67720720721 71.401836161793 41.1708909074277 Winsorized Mean ( 11 / 37 ) 2940.67711711712 71.1973334342461 41.3031917808125 Winsorized Mean ( 12 / 37 ) 2935.13117117117 70.0134293006445 41.9224026088971 Winsorized Mean ( 13 / 37 ) 2935.59144144144 69.239765057299 42.3974783711659 Winsorized Mean ( 14 / 37 ) 2936.54747747748 68.7198633358323 42.7321495551678 Winsorized Mean ( 15 / 37 ) 2920.34072072072 65.730862769861 44.42875991063 Winsorized Mean ( 16 / 37 ) 2914.61243243243 64.4330388767261 45.2347504206451 Winsorized Mean ( 17 / 37 ) 2912.70873873874 63.7601291783812 45.6822904261985 Winsorized Mean ( 18 / 37 ) 2908.84117117117 62.8237929536 46.301584708831 Winsorized Mean ( 19 / 37 ) 2908.79837837838 62.6218051168603 46.4502480078655 Winsorized Mean ( 20 / 37 ) 2907.33711711712 62.186162390293 46.7521552282013 Winsorized Mean ( 21 / 37 ) 2905.67603603604 60.8537842621293 47.7484855094592 Winsorized Mean ( 22 / 37 ) 2908.72828828829 59.8771835376455 48.5782416011524 Winsorized Mean ( 23 / 37 ) 2919.85117117117 58.568340134597 49.8537463151765 Winsorized Mean ( 24 / 37 ) 2907.32792792793 55.678133276259 52.2166918474546 Winsorized Mean ( 25 / 37 ) 2903.21306306306 55.0720553926644 52.7166281040924 Winsorized Mean ( 26 / 37 ) 2900.85198198198 53.7689629631233 53.9503055688742 Winsorized Mean ( 27 / 37 ) 2918.14414414414 51.3701865181249 56.8061815994096 Winsorized Mean ( 28 / 37 ) 2896.61693693694 47.8593707316245 60.5235065287416 Winsorized Mean ( 29 / 37 ) 2891.31594594595 44.35455914126 65.1864431058306 Winsorized Mean ( 30 / 37 ) 2904.00783783784 42.3260454598046 68.6104219350154 Winsorized Mean ( 31 / 37 ) 2867.94171171171 37.8148448459972 75.84168924642 Winsorized Mean ( 32 / 37 ) 2857.25774774775 34.4855553817340 82.853754742229 Winsorized Mean ( 33 / 37 ) 2852.71207207207 33.7614089921528 84.4962386710558 Winsorized Mean ( 34 / 37 ) 2848.09603603604 32.9088829336751 86.5449016235562 Winsorized Mean ( 35 / 37 ) 2820.06450450450 29.3792562611105 95.9882877715132 Winsorized Mean ( 36 / 37 ) 2810.30882882883 27.4979389226106 102.200708087180 Winsorized Mean ( 37 / 37 ) 2809.34216216216 26.9768073633356 104.139163850069 Trimmed Mean ( 1 / 37 ) 2949.32568807339 76.0990693456429 38.7563962796643 Trimmed Mean ( 2 / 37 ) 2945.65448598131 74.9646874733801 39.2938940354725 Trimmed Mean ( 3 / 37 ) 2941.21771428571 73.9002080297222 39.7998570329163 Trimmed Mean ( 4 / 37 ) 2936.44689320388 72.8308575845802 40.3187191609506 Trimmed Mean ( 5 / 37 ) 2931.86108910891 71.791487065165 40.8385619098218 Trimmed Mean ( 6 / 37 ) 2927.38616161616 70.7940620597312 41.3507302229138 Trimmed Mean ( 7 / 37 ) 2927.38616161616 69.6849407757334 42.0088778009778 Trimmed Mean ( 8 / 37 ) 2918.41231578947 68.6823712516481 42.4914321186813 Trimmed Mean ( 9 / 37 ) 2914.43279569892 67.6947997417103 43.0525358937312 Trimmed Mean ( 10 / 37 ) 2910.00956043956 66.6333484903446 43.6719694622766 Trimmed Mean ( 11 / 37 ) 2906.30943820225 65.6585155896954 44.2640137703383 Trimmed Mean ( 12 / 37 ) 2902.32321839080 64.568948231651 44.9492100750701 Trimmed Mean ( 13 / 37 ) 2898.75294117647 63.5044880468766 45.6464264232273 Trimmed Mean ( 14 / 37 ) 2898.75294117647 62.3914817313016 46.4607164429976 Trimmed Mean ( 15 / 37 ) 2890.89283950617 61.1772691623918 47.2543622670122 Trimmed Mean ( 16 / 37 ) 2888.13443037975 60.2188357389841 47.9606487727236 Trimmed Mean ( 17 / 37 ) 2885.74883116883 59.28543020927 48.6755147256671 Trimmed Mean ( 18 / 37 ) 2883.40173333333 58.2836401762418 49.4718882453861 Trimmed Mean ( 19 / 37 ) 2881.25273972603 57.2370292526256 50.3389637328855 Trimmed Mean ( 20 / 37 ) 2878.9861971831 56.0261127711725 51.3865063054034 Trimmed Mean ( 21 / 37 ) 2876.70579710145 54.6530285359402 52.6357984939428 Trimmed Mean ( 22 / 37 ) 2874.42029850746 53.2189399689086 54.0112279610745 Trimmed Mean ( 23 / 37 ) 2871.75723076923 51.6489840997287 55.601427226994 Trimmed Mean ( 24 / 37 ) 2868.07301587302 49.9532456808561 57.4151484409384 Trimmed Mean ( 25 / 37 ) 2865.09672131148 48.3838272547846 59.216000136247 Trimmed Mean ( 26 / 37 ) 2862.22830508475 46.5732287862504 61.4565143898666 Trimmed Mean ( 27 / 37 ) 2859.33543859649 44.5791850521819 64.140594657563 Trimmed Mean ( 28 / 37 ) 2859.33543859649 42.5206175460313 67.2458586825809 Trimmed Mean ( 29 / 37 ) 2851.82226415094 40.6555277320307 70.1459905513443 Trimmed Mean ( 30 / 37 ) 2848.85823529412 38.9955466142179 73.0559892768734 Trimmed Mean ( 31 / 37 ) 2848.85823529412 37.2621619668017 76.4544536581714 Trimmed Mean ( 32 / 37 ) 2842.92276595745 36.0241948846359 78.9170382589157 Trimmed Mean ( 33 / 37 ) 2841.81777777778 35.0962311955314 80.9721637045636 Trimmed Mean ( 34 / 37 ) 2840.96558139535 34.0232490837855 83.5007137148836 Trimmed Mean ( 35 / 37 ) 2840.39780487805 32.7869925530266 86.6318495142322 Trimmed Mean ( 36 / 37 ) 2842.05128205128 31.9287612637992 89.0122625982861 Trimmed Mean ( 37 / 37 ) 2844.69648648649 31.1559564032599 91.305060569055 Median 2848.96 Midrange 3166.105 Midmean - Weighted Average at Xnp 2844.91232142857 Midmean - Weighted Average at X(n+1)p 2859.33543859649 Midmean - Empirical Distribution Function 2859.33543859649 Midmean - Empirical Distribution Function - Averaging 2859.33543859649 Midmean - Empirical Distribution Function - Interpolation 2854.93963636364 Midmean - Closest Observation 2844.91232142857 Midmean - True Basic - Statistics Graphics Toolkit 2859.33543859649 Midmean - MS Excel (old versions) 2859.33543859649 Number of observations 111

Charts produced by software:

http://www.freestatistics.org/blog/date/2009/Dec/28/t1262006101rock4r86jrlnikr/1hu3t1262005868.png (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/28/t1262006101rock4r86jrlnikr/1hu3t1262005868.ps (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/28/t1262006101rock4r86jrlnikr/2w11j1262005868.png (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/28/t1262006101rock4r86jrlnikr/2w11j1262005868.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

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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